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• Volume 23, Issue 2
• Dementia care and treatment issues
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• http://orcid.org/0000-0003-2221-1573 Roberta Heale
• School of Nursing , Laurentian University , Sudbury , Ontario , Canada
• Correspondence to Dr Roberta Heale, School of Nursing, Laurentian University, Sudbury, ON P3E 2C6, Canada; rheale{at}laurentian.ca

https://doi.org/10.1136/ebnurs-2020-103260

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This perspectives article expands on the one published in EBN July 2019, Vol 22-3 about Care of the Older Person by focusing on commentaries specifically related to research with dementia. Dementia rates are growing internationally and along with this are the complexities of caring for this growing cohort of people. 1 It is helpful to explore the literature related specifically to this issue. Commentaries related to dementia and cognitive decline were found from January 2017 to January 2020. Key themes were identified followed by a summary and discussion.

The 13 commentaries are grouped into three themes (see box 1 ).

Pain management and dementia.

Carers of those with dementia.

Treatment issues for those with dementia.

Evidence-based nursing commentaries on dementia and cognitive decline (2017–2020)

Theme 1: pain management and dementia.

Pain-related palliative care challenges in people with advanced dementia call for education and practice development in all care settings https://ebn.bmj.com/content/20/4/118

Assessment and treatment of persistent pain in nursing home residents should be implemented systematically to prevent suffering https://ebn.bmj.com/content/20/3/91

Theme 2: Carers of those with dementia

Help seeking increases stress among caregivers of partners with young-onset dementia https://ebn.bmj.com/content/23/1/28

Better support and education is imperative to bolster informal at-home carers of people with cognitive impairment and reduce incidences of involuntary treatment of older adults in their homes https://ebn.bmj.com/content/22/2/51

Spouses with partners with dementia living in institutional care develop visiting routines that help to maintain the spousal relationship https://ebn.bmj.com/content/20/2/58

Theme 3: Treatment issues for those with dementia

International study reveals aged patients with dementia frequently receive ‘inappropriate prescriptions’ https://ebn.bmj.com/content/22/2/50

Deprescribing in nursing homes is safe and should be pursued https://ebn.bmj.com/content/21/2/53

Effective dietary recommendations could help to prevent age-related cognitive decline https://ebn.bmj.com/content/21/1/26

Cognitively impaired patients with heart failure may not perceive weight gain as a risk for decompensation https://ebn.bmj.com/content/20/4/115

Risk of injury higher in older adults with dementia than in those without https://ebn.bmj.com/content/20/4/117

More research needed on animal-assisted interventions in dementia (Olsen) https://ebn.bmj.com/content/20/2/60

Nursing home residents prefer fewer interventions and the nursing home instead of hospital for place of death https://ebn.bmj.com/content/20/1/24

Literature demonstrates that there is very poor pain management for those with dementia. There is a lack of understanding about the signs of pain for people with dementia and there are some alarming findings, such as one where the majority of healthcare staff in a study thought that people with dementia had reduced pain sensation. 2 Three commentaries from the past 3 years reflected various aspects of pain management for people with dementia. The first was based on a study by Blytt et al , 3 a double-blinded, placebo-controlled trial of 106 long-term patients with depression and dementia. The research group studied the effects of pain treatment versus non-treatment and found that treatment for pain was significantly associated with better sleep. 3

The second commentary reviewed qualitative research by De Witt Jansen et al 4 where 24 nurses practising in long-term care were interviewed about their experiences in caring for patients dying of advanced dementia. Three themes were identified including patient-related challenges , such as the patient’s refusal to take medication; the nurse–physician relationship , where if a difficult relationship with physicians was identified, nurses gave examples such as waiting for prescriptions and physician refusal to assess complex cases; and interactive learning and practice development , where some nurses were not able to access appropriate professional development activities. The overall message was that achieving pain management for people dying of advanced dementia is extremely challenging. 4

The final commentary in this theme was a cross-sectional study by Fain et al 5 of 18 536 nursing home residents with persistent pain living in the USA. The findings showed that pain in nursing homes is undertreated, especially for those with dementia and cognitive decline. 5

The second theme explores the experiences and challenges of carers for those with dementia and cognitive decline. The first commentary about research by Kobiske et al 6 describes the outcomes of a cross-sectional, correlational study that investigated the experiences of caregivers for people with young-onset dementia. The survey design reflected the theoretical framework of Resilience Theory and examined the effects of personal and social relationships, pre-death grief and stress of this caregiving role. There was a large positive correlation between pre-death, grief and caregiver perceived stress, which was positively impacted by social resourcefulness. 6

The outcomes of caregiver stress are examined in research by Moermans et al. 7 In this cross-sectional study, older adults who were receiving care in their home were randomly selected for the study. The district nurses caring for this group were asked to complete an online questionnaire that identified the use of involuntary treatment. The findings demonstrated that non-consensual care, psychotropic drugs and physical restraints were often used, in part, to address informal caregiver burden. 7

The final commentary in this theme reflects research by Førsund et al 8 , a qualitative, grounded theory design consisting of 15 interviews with the spouses of nursing home residents with dementia. The findings demonstrate that it is important for the spouses to remain involved with the resident and they did so by establishing visiting routines. 8

The final theme includes a variety of commentaries, all with a focus on a treatment issue related to the care of people with dementia. The first two commentaries are of studies related to prescription medication for those with dementia. In the first, Renom-Guiteras et al 9 conducted a survey of people with dementia from across the EU to explore a variety of issues. The findings showed that 60% of the participants had at least one inappropriately prescribed medication. 9 The next study, by Wouters et al , 10 included a randomised controlled trial of the discontinuation of one mediation for nursing home residents in the Netherlands. Results showed that the 3MR process of multidisciplinary, multistep medication review was significantly better than usual care for successful discontinuation of one medication. 10

Next, McEvoy et al conducted a population-based cross-sectional study that showed an association between neuroprotective diets, such as the Mediterranean Diet, and better cognitive health. 11 In the next research, also related to diet, Dolansky et al 12 conducted an observational study which demonstrated that adults with cognitive decline may be at risk for gaining significant amounts of weight, thus negatively impacting their heart failure status. 12

The final cluster of commentaries gives an overview of three different topics. Meuleners et al 13 analysed 29 671 hospital admissions and identified that older adults with dementia are at greater risk for admission to hospital with an injury. 13 Next, Olsen et al found in their randomised trial that when a dog was added to activities of those with severe dementia in nursing homes, there was a significant decrease in the levels of depression and a positive impact on quality of life of the residents. 14 Finally, Ng et al 15 conducted a cross-sectional study of nursing home residents in Singapore to determine their wishes at end of life. Their findings determined that the majority would prefer to die at home. 15

Conclusions

There is a wealth of research related to dementia. Commentaries about dementia research give nurses efficient summaries, which may be of benefit to them in expanding knowledge and improving practice that includes those with dementia.

• Sevenants A ,
• Smets T , et al
• Au K-ming , et al
• Bjorvatn B ,
• Husebo B , et al
• De Witt Jansen B ,
• Passmore P , et al
• Alexander GC ,
• Dore DD , et al
• Kobiske KR ,
• Bekhet AK ,
• Garnier-Villarreal M , et al
• Moermans VRA ,
• Bleijlevens MHC ,
• Verbeek H , et al
• Førsund LH ,
• Skovdahl K , et al
• Renom-Guiteras A ,
• Thürmann PA ,
• Miralles R , et al
• Wouters H ,
• Scheper J ,
• Koning H , et al
• McEvoy CT ,
• Langa KM , et al
• Dolansky MA ,
• Hawkins MAW ,
• Schaefer JT , et al
• Meuleners LB ,
• Pedersen I ,
• Bergland A , et al
• Cheong SK ,
• Govinda Raj A , et al

Twitter @robertaheale

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests None declared.

Patient consent for publication Not required.

Provenance and peer review Commissioned; internally peer reviewed.

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Understanding stigma of dementia during COVID-19: a scoping review

Affiliations.

• 1 School of Nursing, Thompson Rivers University, Kamloops, BC, Canada.
• 2 Department of Computer Science, University of Saskatchewan, Saskatoon, SK, Canada.
• 3 School of Nursing, Clemson University, Clemson, SC, United States.
• 4 Caregiver Crosswalk Inc, Montreal, QC, Canada.
• 5 Engagement of People with Lived Experience of Dementia (EPLED), Maple Ridge, BC, Canada.
• 6 Department of Psychology, Thompson Rivers University, Kamloops, BC, Canada.
• PMID: 38600982
• PMCID: PMC11004454
• DOI: 10.3389/fpsyt.2024.1261113

Introduction: Stigma of dementia is one of the greatest challenges for people living with dementia. However, there is little research on the different types of stigma of dementia in the COVID-19 pandemic. The purpose of this scoping review is to synthesize the existing literature on dementia-related stigma (self, public, and structural stigma), during the pandemic.

Methods: Guided by Arksey and O'Malley's scoping review framework and PRISMA guidelines, CINAHL, EMBASE, Google Scholar, Medline, PsycINFO, and Web of Science were searched for English language literature from January 2020 to June 2023. Inclusion criteria consisted of peer-reviewed, original research articles addressing stigma of dementia during the COVID-19 pandemic. Thematic analysis was used to analyze the data and steps were taken to ensure rigor.

Results: Fifteen articles met our inclusion criteria. Four primary themes were identified including: 1) COVID-19 stereotypes and assumptions of dementia; 2) human rights issues and deprived dignity; 3) disparate access to health services and supports; and 4) cultural inequities and distrust.

Discussion: The COVID-19 pandemic has contributed to the stigmatization of people living with dementia. Further research is needed to develop, implement, and evaluate interventions targeted towards the different types of dementia-related stigma (including self, public, and structural stigma). Moreover, our findings highlight the need for more collaborative research that prioritizes the lived experience and input of diverse people living with dementia. Research partnerships with diverse people living with dementia are vital to improving future pandemic planning. Only through evidence-informed research and lived experience can we begin to fully address the different types of dementia-related stigma and enhance the quality of life of people living with dementia.

Keywords: COVID-19; dementia; discrimination; negative attitudes; prejudice; stereotypes; stigma.

Copyright © 2024 Bacsu, Spiteri, Nanson, Rahemi, Webster, Norman and Stone.

Publication types

• Systematic Review

Grants and funding

• Open access
• Published: 19 April 2024

A longitudinal cohort study on the use of health and care services by older adults living at home with/without dementia before and during the COVID-19 pandemic: the HUNT study

• Tanja Louise Ibsen 1 ,
• Bjørn Heine Strand 1 , 2 , 3 ,
• Sverre Bergh 1 , 4 ,
• Gill Livingston 5 , 6 ,
• Hilde Lurås 7 , 8 ,
• Svenn-Erik Mamelund 9 ,
• Richard Oude Voshaar 10 ,
• Anne Marie Mork Rokstad 1 , 11 ,
• Pernille Thingstad 12 , 13 ,
• Debby Gerritsen 14 &
• Geir Selbæk 1 , 15 , 16  

BMC Health Services Research volume  24 , Article number:  485 ( 2024 ) Cite this article

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Metrics details

Older adults and people with dementia were anticipated to be particularly unable to use health and care services during the lockdown period following the COVID-19 pandemic. To better prepare for future pandemics, we aimed to investigate whether the use of health and care services changed during the pandemic and whether those at older ages and/or dementia experienced a higher degree of change than that observed by their counterparts.

Data from the Norwegian Trøndelag Health Study (HUNT4 70 + , 2017–2019) were linked to two national health registries that have individual-level data on the use of primary and specialist health and care services. A multilevel mixed-effects linear regression model was used to calculate changes in the use of services from 18 months before the lockdown, (12 March 2020) to 18 months after the lockdown.

The study sample included 10,607 participants, 54% were women and 11% had dementia. The mean age was 76 years (SD: 5.7, range: 68–102 years). A decrease in primary health and care service use, except for contact with general practitioners (GPs), was observed during the lockdown period for people with dementia ( p  < 0.001) and those aged ≥ 80 years without dementia ( p  = 0.006), compared to the 6-month period before the lockdown. The use of specialist health services decreased during the lockdown period for all groups ( p  ≤ 0.011), except for those aged < 80 years with dementia. Service use reached levels comparable to pre-pandemic data within one year after the lockdown.

Older adults experienced an immediate reduction in the use of health and care services, other than GP contacts, during the first wave of the COVID-19 pandemic. Within primary care services, people with dementia demonstrated a more pronounced reduction than that observed in people without dementia; otherwise, the variations related to age and dementia status were small. Both groups returned to services levels similar to those during the pre-pandemic period within one year after the lockdown. The increase in GP contacts may indicate a need to reallocate resources to primary health services during future pandemics.

Trial registration

The study is registered at ClinicalTrials.gov, with the identification number NCT 04792086.

Peer Review reports

In Norway, similar to most European countries [ 1 , 2 , 3 ], the first wave of the COVID-19 pandemic lasted from 12 March to 15 June 2020 [ 4 ]. During this period, strict infection control measures were introduced to minimise the number of infected people. Health and care services were reduced or locked down, because health professionals were transferred to COVID-19-related services, or hospital wards were reserved for COVID-19 patients. Facilities such as day care services were closed to prevent the spread of infection through social contact, and some services were employed with digital technology. People were urged to stay at home to maintain social distancing and prevent the spread of the virus [ 4 ].

The strict infection control measures aimed mainly to prevent people from hospitalisation and/or death by COVID-19. By 13 November 2022 (last published data), Norway recorded 4,399 cumulative COVID-19-related deaths, of which approximately two-thirds occurred in 2022 (in people of an average age of 85.6 years in 2022) [ 5 ]. From March 2020 to March 2021, compared to the mean all-cause mortality from 2016 to 2019 as a reference, Norway recorded significantly lower all-cause mortality than those recorded by other European Union countries [ 6 ], indicating that Norway had a successful public health strategy. The topic being raised in the present paper, is how infection control measures affected the use of health and care services by the older population, to better prepare ourselves for future health crisis like a pandemic.

Older adults are particularly vulnerable to COVID-19 and at a higher risk of hospitalisation and death [ 7 ]. People with dementia are anticipated to have an even higher risk of mortality than that of people without dementia, because of an impaired immune system [ 8 ]. Fearing the virus, some older adults personally imposed strict infection control measures and cancelled scheduled healthcare appointments. A German study, including participants aged ≥ 73 years, has reported that approximately 30% of the participants reduced or cancelled their medical consultations during the first wave of the pandemic [ 1 ]. A qualitative study including participants aged 65–79 years from Portugal, Brazil, and the United Kingdom has reported that the majority refrained from face-to-face contact with their family doctors in the first wave of the pandemic, as it implied using public transport making social distancing difficult [ 2 ]. Some health and care services have been replaced with online or telephone consultations, which have been beneficial for some parts of the population and challenging for others, especially older adults [ 2 , 3 , 9 ].

People with dementia often need health and care services and practical assistance in their homes to manage their everyday lives [ 10 ]. A Norwegian study including 105 caregivers of people with dementia has reported that 60% experienced a reduction or full cessation of formal care during the first wave of the pandemic as the services were cancelled by the service provider [ 11 ]. This is in line with studies from Sweden and the USA, which reported a significant drop in the use of health and care services during this period [ 12 , 13 ]. However, how the use of primary and specialist healthcare services affected older adults, including people with dementia, as society began a cautious reopening after the first wave of the pandemic remains unclear. A study from the USA conducted a predictive analysis for the post-lockdown period (June 2020–October 2021) on inpatient, outpatient, and emergency services. They found that people with mild cognitive impairment (MCI), Alzheimer’s disease, and related dementia experienced greater and more sustained disruptions in primary and specialist health and care service use than those experienced by people without MCI or dementia [ 13 ].

In the present study, we used a large population-based dataset from the Norwegian Trøndelag Health Study (HUNT) [ 14 ], linked to national registry data on primary and specialist health and care services, to investigate whether the use of health and care services changed during the pandemic, and those with older ages and/or dementia had a higher degree of change than that observed in their counterparts.

Study design and setting

We used a longitudinal cohort design, linking participant data on sex, year of birth, and cognitive status from the HUNT4 70 + survey with later registry data on the use of health and care services from 12 September 2018 to 11 September 2021. This time period equals 18 months before- and 18 months after the Norwegian lockdown on 12 March 2020. This 36-month period was grouped into six periods of six months each, including three pre-lockdown periods (pre1, pre2, and pre3), one lockdown period, and two post-lockdown periods (post1 and post2) (Fig.  1 ). We included a longer lockdown period than the generally denoted period from March to June 2020, as the reopening started slowly, and many older adults imposed strict social distancing on themselves. The next period, 12 September 2020 to 11 March 2021 also included periods with restrictions on social life and activity, such as a maximum of five people gathering and recommendations for wearing a face mask where maintaining distance is difficult. In the last period from 12 March to 11 September 2021, all infection control measures were gradually lifted until Norway was completely reopened on 25 September 2021 [ 4 ]. Trøndelag, the county where the study was conducted, followed national infection control regulations.

Flow-chart of the study periods

Participants

The study included participants aged > 70 years in the fourth wave of the HUNT Study (HUNT4 70 +), which took place between September 2017 and March 2019. The HUNT is a population-based study that has invited the entire adult population from the same geographic area, North-Trøndelag, in four waves, first time in 1984 [ 14 ]. As North-Trøndelag does not comprise any large cities, a random sample of people aged > 70 years from a city in Trondheim (212,000 inhabitants) was also invited. In total, 11,675 participants were included, with 9,930 from North-Trøndelag (response rate 51%) and 1,745 from Trondheim (response rate 34%). We do not judge that there is likely to be any systematic bias introduced by the difference in response rates in different municipalities as the people living at home are similar populations.”. The participants answered a questionnaire that included socio-demographic and clinical data, and they attended a comprehensive clinical evaluation by health professionals [ 15 ]. Participants without sufficient information on their cognitive status ( n  = 202) and nursing home residents ( n  = 866) were excluded (Fig.  2 ). The mean age (76 years, SD 5.7 years) of those included was lower than that of those excluded (82 years, SD 7.9) ( p  < 0.001). The study population included 10,607 participants with complete data on cognitive status. We do not have information on dementia status on the population not included in HUNT4 70 + .

Flow-chart of included participants. HUNT4 70 + : The fourth wave of the Trøndelag health study, 70 year and older cohort

Dementia diagnosis

Two specialists from a diagnostic workgroup of nine medical doctors with comprehensive scientific and clinical expertise (geriatrics, old-age psychiatry, or neurology) independently diagnosed each patient with dementia using the Diagnostic and Statistical Manual of Mental Disorders-5 [ 16 ]. Discrepancies were resolved and consensuses were obtained by the involvement of a third expert. During the diagnostic process, the experts had access to all relevant information from the HUNT4 70 + dataset, such as education, function in activities of daily living, neuropsychiatric symptoms, onset and course of cognitive symptoms, cognitive tests (the Montreal Cognitive Assessment (MoCA) scale [ 17 ] and the Word List Memory Task (WLMT) [ 18 ], and structured interviews with the closest family proxy. A more comprehensive description of the diagnostic process has been published [ 15 ].

Health and care services

Data from two national registries were collected for the entire study period, from September 2018 to September 2021. Health and care services used in primary health care were obtained from The Norwegian Registry of Primary Health Care [ 19 ]. This registry includes individual-level data on municipal health services (contacts with general practitioners (GPs), emergency rooms, and physiotherapists) and care services (care, such as home nurses, and practical assistance in the recipient’s home, day care, respite services and short-term nursing home stays, municipal housing, and nursing home admission) [ 20 ]. Information on the use of specialist health services was based on data from the Norwegian Patient Registry (NPR) [ 21 ]. The NPR holds individual-level data on patients’ use of specialist health services (contacts with somatic hospitals, mental health care, and rehabilitation institutions). The NPR also registers whether the contact was an outpatient consultation, hospitalisation, or day-treatment [ 20 ].

Data were analysed using the STATA 16 software [ 22 ]. Participant characteristics are reported as means with SD, frequencies, or percentages, as appropriate. Those who were admitted to a nursing home ( n  = 364) or died ( n  = 821) during the study period were censored and participated in only half of the person-time during the study period. Duplicates were removed (3,293 observations). The mean number of health and care services per person in each period (with 95% confidence interval [CI]) was predicted from a multilevel mixed-effects linear regression model with random intercept, where random effects varied across the individuals. In the regression model, the number of services per person was the outcome variable and sex, age, cognitive status (no dementia/dementia), and period were covariates.Age and cognitive status are relevant confounders to address the aim of the present study, and sex is included as a key sociodemographic measure in epidemiological research. [ 23 , 24 ]. To allow for different time trends by cognitive status group, the interaction term period by cognitive status was included in the regression model. In the predictions, the adjusted variables were fixed at their mean values. The significance level was set at p  < 0.05. To investigate the use of health and care services before and during the pandemic, the number of care services implemented within each period and the number of contacts within each period for primary and specialist health services were aggregated. Hence, for care services, we used the date on which the service was implemented, for example the date on which practical assistance at home was implemented. For health services, we used the date when the service occurred, for example, the date a person had contact with a GP or the date a person had contact with a hospital, either for outpatient consultation, hospitalisation, or day-treatment.

In the Results section, we report significant differences between the lockdown period and all the pre- and post-lockdown periods, and between pre2 and post2, as these periods comprise the same seasonal months, one year before and one year after the lockdown, respectively.

The study included 10,607 participants, of whom 54% were women, and 11% had dementia (Table  1 ). The mean age of the participants on 1 January 2017 was 76 years (SD 5.7, range: 68–102 years), and 7,769 participants (73%) were < 80 years old. During the 36-month follow-up period, the study sample was reduced by 10% (from 10,607 to 9,568) due to censoring for death and/or nursing home admission (Table  2 ). The dropout rate was higher in those with dementia than in those without dementia (37% vs. 7%, p  < 0.001). During these 36-months, the total number of contacts with primary health services was 554,061, which corresponded to 9.2 contacts per person per 6-month period (Table  3 ). People with dementia had more contact with health services in the municipality than the contact made by those without dementia (11.3 vs. 8.8 contacts per person per 6-month period, p  < 0.001). The total number of care services implemented for our study population was 20,411, which corresponded to 0.3 care services per person per 6-month period. People with dementia received more care services than those received by people without dementia (1.2 vs. 0.2 care services per person per 6-month period, p  < 0.001). The total number of contacts with specialist health services was 141,994, which corresponded to 2.3 contacts per person per 6-month period. People with dementia had less contact with specialist health services than the contact made by those without dementia (2.2 vs. 2.6 contacts per person per 6-month period, p  < 0.001).

Primary health and care services

Health services.

During the 36-month study period, contact with GPs was the most used health service (66%), followed by physiotherapy services (30%), and contact with GPs in emergency rooms (4%).

The following model only presents contact with GPs, including GPs in emergency rooms, as contact with GPs was the most frequently used primary health service.

The age- and sex-adjusted model (Fig.  3 ) shows that for those aged < 80 years with dementia, the mean number of GP contacts during the lockdown period was higher than that during pre1 (1.27, p  < 0.001) and pre3 (0.82, p  = 0.002) and lower than that during post1 (1.67, p  < 0.001) and post2 (0.84, p  < 0.002). The mean number of GP contacts during post2 was higher than that during pre2 (0.32, p  < 0.001).

Mean number of registered contacts with general practitioners (GPs) per period, pre-lockdown, during lockdown and post-lockdown, including GPs at emergency rooms, for participants < 80 versus ≥ 80 years, divided in people with- or without dementia. Mean number of contacts was predicted in a mixed-effects linear regression model adjusted by period, cognitive status, sex, age, and the interaction period*cognitive status. In the predictions, the adjustment variables age and sex were fixed at the mean values

For those without dementia, the mean number of GP contacts during the lockdown was higher than that during pre1 (0.45, p  < 0.001) and pre2 (0.51, p  < 0.001) and lower than that during post1 (1.18, p  < 0.001) and post2 (0.59, p  < 0.001). The mean number of GP contacts during post2 was higher than that during pre2 (1.11, p  < 0.001).

For those aged ≥ 80 years with dementia, the mean number of GP contacts during the lockdown was higher than that during pre1 (1.45, p  < 0.001) and pre2 (0.96, p  = 0.015) and lower than that during post1 (2.31, p  < 0.001). The mean number of GP contacts during post2 was higher than that during pre2 (1.72, p  < 0.001).

For those without dementia, the mean number of GP contacts during the lockdown was higher than that during pre1 (1.15, p  < 0.001) and pre2 (0.91, p  < 0.001) and lower than that during post1 (1.86, p  < 0.001) and post2 (0.60, p  < 0.002). The mean number of GP contacts during post2 was higher than that during pre2 (1.51, p  < 0.001).

Care services

During the 36-month study period, care and practical assistance at home represented the largest service group (69%), followed by short-term nursing home stays and respite services (21%), nursing home admissions (4%), municipal housing (3%), and day care services (4%). The following model presents all combined care services.

The age- and sex-adjusted model (Fig.  4 ) shows that for those aged < 80 years with dementia, the mean number of care services implemented during the lockdown was lower than that during pre3 (0.37, p  < 0.001) and post1 (0.43, p  < 0.001). The mean number of care services implemented in post2 was higher than that during pre2 (0.13, p  = 0.039).

Mean number of care services implemented per period, pre-lockdown, during lockdown and post-lockdown, as health care and practical assistance in the home, day- and respite services, short-term institutional stay, and nursing home admission, for participants < 80 versus ≥ 80 years, divided in people with- and without dementia. Mean number of care services implemented was predicted in a mixed-effects linear regression model adjusted by period, cognitive status, sex, age, and the interaction period*cognitive status. In the predictions, the adjustment variables age and sex were fixed at the mean values

For those without dementia, the mean number of care services implemented during the lockdown was higher than that during pre1 (0.5, p  = 0.001) and pre2 (0.04, p  = 0.005) and lower than that during post1 (0.03, p  = 0.044). The mean number of care services implemented during post2 was higher than that during pre2 (0.07, p  < 0.001).

For those aged ≥ 80 years with dementia, the mean number of care services implemented during the lockdown was lower than that during pre3 (0.76, p  < 0.001).

For those without dementia, the mean number of care services implemented during the lockdown was higher than that during pre1 (0.22, p  = 0.001) and pre2 (0.17, p  = 0.011) and lower than that during pre3 (0.18, p  = 0.006) and post1 (0.18, p  = 0.007). The mean number of care services implemented during post2 was higher than that during pre2 (0.24, p  < 0.001).

Specialist health services

During the study period, service provision from somatic hospitals was the most used service (96%), followed by mental health care (3%), and treatment at a rehabilitation institution (1%). Somatic hospital services included outpatient consultations (88%), hospitalisation (9%), and daily treatment (3%). The following model only presents contacts with somatic hospital services, as this is the most frequently used specialist health service.

The age- and sex-adjusted models (Fig.  5 ) show that for those aged < 80 years with dementia, the mean number of contacts with somatic hospital services during the lockdown was lower than that during post1 (0.67, p  = 0.002) and post2 (0.48, p  = 0.025). The mean number of contacts with somatic hospital services in post2 was higher than that during pre2 (0.61, p  = 0.004).

Mean number of registered contacts with somatic hospital services per period, pre-lockdown, during lockdown and post-lockdown, for participants < 80 versus ≥ 80 years, divided in people with- or without dementia. Mean number of contacts was predicted in a mixed-effects linear regression model adjusted by period, cognitive status, sex, age, and the interaction period*cognitive status. In the predictions, the adjustment variables age and sex were fixed at the mean values

For those without dementia, the mean number of contacts with somatic hospital services during the lockdown was lower than that during pre1 (0.16, p  = 0.002), pre3 (0.40, p  < 0.001), post1 (0.43, p  < 0.001), and post2 (0.34, p  < 0.001). The mean number of contacts with somatic hospital services in post2 was higher than that during pre2 (0.25, p  < 0.001).

For those aged ≥ 80 years with dementia, the mean number of contacts with somatic hospital services during the lockdown was lower than that during pre2 (0.54, p  = 0.003), pre3 (0.46, p  = 0.011), post1 (0.44, p  = 0.022), and post2 (0.42, p  = 0.040).

For those without dementia, the mean number of contacts with somatic hospital services during the lockdown was lower than that during pre3 (0.49, p  < 0.001), post1 (0.41, p  < 0.001), and post2 (0.41, p  < 0.001). The mean number of contacts with somatic hospital services in post2 was higher than that during pre2 (0.29, p  = 0.001).

This population-based study revealed that people with dementia experienced a larger decrease in the use of primary care services implemented during the lockdown than that experienced by people without dementia. Contact with GPs was maintained at a normal level or increased in both groups during the lockdown. The use of specialist health services decreased in both groups during the lockdown period except for those aged < 80 years with dementia. The use of primary health and care services, and specialist health services was at the same or higher-level post-lockdown (post2) as pre-lockdown (pre2). Collectively, these results indicate an increased burden on primary health services during the lockdown.

Both cognitive groups had a similar number of GP contacts during lockdown as pre-lockdown. Those aged < 80 years with dementia experienced an increased number of GP contacts during the lockdown compared to the numbers during the 6-month period before the lockdown (pre3). Furthermore, all the groups had an increased number of GP contacts in the first 6-months period post-lockdown (post1). Unfortunately, we were unable to identify whether the consultations were digital in our material; however, digital consultations may have contributed to maintaining contact with GPs during the pandemic. This corresponds with the results of a previous study which has reported that the Norwegian population experienced an increased use of telephone and video consultations during the pandemic [ 3 ]. However, a survey during the pandemic in the same study population as that of the present study (HUNT4 70 +) revealed that only 8% reported contact with healthcare professionals via screen-based media or telephone at least once a month during the pandemic [ 9 ]. In addition, a survey of video consultations among Norwegian GPs during the pandemic revealed that video consultations were unsuitable for the oldest population [ 25 ].

The results of the present study may indicate that GPs managed to serve older adults in Norway during the pandemic and that the cancellations of medical consultations described among older adults in other countries [ 1 , 2 ] have been less extensive in Norway. Meanwhile, contact with GPs may have shifted towards more severe cases, where patients in need of specialist health services who postponed contact because of COVID-19 used the primary care service. In addition, the increase in GP contact post-lockdown may imply an increased stress level among older adults and an increase in health problems during the lockdown, which will be discussed in more detail in a later section.

Our finding that people with dementia experienced a larger decrease in the number of care services implemented during the lockdown than that experienced by people without dementia is in line with those of earlier studies [ 11 , 13 ]. This is most likely a consequence of the fact that people with dementia use care services more often and thus, are more affected when such services are reduced or locked down. Interestingly, those with dementia in both age groups experienced a significant increase in new services implemented in the 6-month period before the lockdown (pre3). However, the possible cause for the increase in care services implemented, such as a reduction in other services or societal changes during this period, remains unconfirmed. The most likely explanation is an increase in service needs related to dementia progression, although some random fluctuations cannot be ruled out.

Care service providers have reported a deterioration in older adults’ health during the pandemic related to the absence of social support, which, in turn, has led to less support with meals, practical help, and physical activity [ 26 ]. Next of kin reported that people with dementia had a reduction in cognitive- and functional abilities because of the limited possibility of meaningful activities and mental stimulation when they had to stay at home [ 27 , 28 ]. Furthermore, a lack of social connections [ 29 ] and perceived social support [ 30 ] are associated with cognitive decline and depression. Based on these findings, it can be assumed that the need for care services may be the same or higher post-lockdown than that in the 6-month period before the pandemic (pre3). However, the number of care services implemented post-lockdown (post2) was at the same level as that at pre-lockdown (pre2).

This study revealed that somatic hospital services for those aged ≥ 80 years were the only services with a lower level of contact during the lockdown period than during the comparable pre-lockdown period (pre2). Both those with and without dementia had a decrease in somatic hospital services during the lockdown period, compared to the 6-months period before the lockdown. This corresponds with findings from an Italian study conducted in the autumn of 2020, reporting that hospitalisations and outpatient visits among older adults aged ≥ 65 years were reduced by 18.3% during the pandemic [ 31 ].

The decrease in the use of somatic hospital services during the lockdown observed in the present study was most likely related to strict infection control measures that prevented a widespread COVID-19 outbreak. Furthermore, it may be interpreted as a precautionary measure taken to minimize the risk of exposing older adults to hospitals, where a considerable number were affected by COVID-19. Hospital services experienced the greatest decline in activity during the lockdown due to preparedness for COVID-19 patients [ 32 ]. In the present study, all the groups returned to the same or a higher level of contact with somatic hospital services post-lockdown (post2), than they had pre-lockdown (pre2). Conversely, a study from the USA has suggested that people with dementia or MCI would experience more sustained disruption in primary and specialist health services than that experienced by people without such diagnoses [ 13 ]. Another study from the USA has revealed that those with comorbidities, often present among people with dementia, were at a higher risk of delayed or missed care during the pandemic [ 33 ]. The contrast in the findings may be related to differences in the healthcare system. In addition, the World Health Organization has reported disruptions in both primary and specialist health services worldwide two years into the pandemic. High-income countries reported fewer service disruptions than those reported by low-income ones [ 34 ]. The increase in GP contact post-lockdown in the present study may indicate that primary health services have been able to relieve specialist health services in Norway, so that people with dementia and others in need of specialist health services may be prioritised.

The variation in the frequency of contact with both somatic hospital services and GPs may be observed in the context of normal seasonal variations, where contact might be higher in the autumn and winter months (pre1, pre3, and post2) than in the spring and summer months (pre2, lockdown, and post2). However, the Norwegian Institute of Public Health has reported that the seasonal flu outbreak from December 2019 to March 2020, which corresponds with the 6-month period before the lockdown (pre3), was limited compared to those in previous years [ 35 ]. Thus, normal variations due to seasonal flu cannot provide a full explanation for more contact with GPs and somatic hospital services in the 6-month period before lockdown (pre3). The next seasonal flu, expected from December 2020 to March 2021 (post1), did not appear as expected, most likely because of the infection control measures in connection with the COVID-19 outbreak [ 36 , 37 ]. The increase in the frequency of contact with GPs and somatic hospital services detected in the 6-month period after the lockdown (post1) may be explained by the fact that people had less contact with these services for diseases other than COVID-19 during the first wave of the pandemic [ 32 ], and that these consultations accumulated when society started reopening. Furthermore, the increase in contact with GPs and somatic hospital services after the lockdown may be explained by the increased contact between people, which may have caused an increased spread of infections [ 37 ].

Finally, the increase in mental health problems during the pandemic [ 27 , 28 , 30 ], may have required additional medical supervision. Studies have reported an increase in depression among older adults during the pandemic, a related increase in the prescription of antidepressant medication [ 30 , 38 ], and the need for primary health services, such as GPs, and specialist services, such as hospital services [ 38 ].

Strength and limitations

The main strength of the present study is its large population-based survey sample merged with unique national registry data on primary and specialist health care services. This provided objective data regarding the participants’ service use. Despite the large study sample, all the participants were from the middle region of Norway, which may differ from the population in other parts of the country and outside Norway. Furthermore, the study sample was a homogenous group of participants mainly born in Norway, and the results cannot be generalised to other ethnic groups. Although the diagnostic process for dementia was thorough, the diagnosis was based on collected research data without access to imaging or biomarker data which may have caused misclassification. As our goal was to estimate the actual change in service use based on dementia status among younger and older adults, the analysis does not include health-related covariates such as comorbidity and functional level. Finally, the information on dementia status was collected from 2017 to 2019 and may have changed during the study period from September 2018 to September 2021.

The use of primary care and specialist health services was immediately reduced during the COVID-19 lockdown period. Within primary care services, people with dementia experienced a more pronounced reduction than that experienced by people without dementia; however, age and dementia status only demonstrated small variations. One year after the lockdown, service provisions returned to a level similar to or higher than that of one year before the lockdown for all groups. Our findings indicate that infection control and management limited the scope of action within care services and specialist health services during the lockdown, leaving GPs on the front line to manage medical problems and psychological stress in the population. In any future pandemic, the reallocation of resources for primary health services could make us better equipped to meet the needs of the population.

Availability of data and materials

The data that support the findings of this study are available from the HUNT database and the Norwegian registry database, Helsedata, but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of the HUNT database and the Norwegian registry database Helsedata.

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Acknowledgements

HUNT is a collaborative project between the HUNT Research Centre at the Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, the Trøndelag County Council, the Central Norway Regional Health Authority and the Norwegian Institute of Public Health. We would like to thank everyone who participated in HUNT 70+ for their valuable contributions to this research.

This study was supported by the Norwegian Health Association (grant no. 22687).

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Tanja Louise Ibsen, Bjørn Heine Strand, Sverre Bergh, Anne Marie Mork Rokstad & Geir Selbæk

Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway

Bjørn Heine Strand

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Sverre Bergh

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Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Science, Norwegian University of Science and Technology, Trondheim, Norway

Pernille Thingstad

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GS led the study project and is responsible for the concept and design of the study, together with BHS, SB and TLI. BHS was a major contributor in the analysis prosses together with TLI. TLI, BHS, SB, GL, HL, SEM, ROV, AMMR, PT og GS contributed to interpreting the data. TLI drafted the paper, with substantially contributions from all the authors in revising the drafted work. DG made significant contributions on the revised version after peer review. All authors read and approved the final manuscript.

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This study was approved by the Regional Committee for Medical and Health Research Ethics of Norway (REK Southeast B 182575). All methods were carried out in accordance with REK’s guidelines which correspond to the Declaration of Helsinki. The present study is part of a larger project registered at ClinicalTrials.gov (identification number: NCT 04792086). Informed written consent was obtained from all participants in the HUNT4 70 + study. Participants with reduced capacity to consent were included if they had a next of kin who consented on their behalf. In the consent form, it was thoroughly described that collected data can be linked to other registers in order to carry out approved research projects, as has been done in the present project.

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Ibsen, T.L., Strand, B.H., Bergh, S. et al. A longitudinal cohort study on the use of health and care services by older adults living at home with/without dementia before and during the COVID-19 pandemic: the HUNT study. BMC Health Serv Res 24 , 485 (2024). https://doi.org/10.1186/s12913-024-10846-y

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• Published: 15 February 2023

Dementia research needs a global approach

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The international community needs to prioritize research on interventions and preventative measures for dementia that are likely to produce the greatest global impact.

Dementia is the seventh leading cause of death worldwide, and the number of people living with this disorder is expected to triple by 2050 . The burden of dementia is not equal across all countries, with around two thirds of people with dementia living in low- and middle-income countries (LMICs), where increases are predicted to occur more rapidly than in higher-income countries (HICs). Women are disproportionately affected by dementia, with greater prevalence rates than men in all age groups and a higher proportion of deaths. Women are also responsible for providing roughly 70% of informal care hours globally, with the highest proportions being in LMICs.

Although progress has been made, research into dementia remains fragmented and siloed to areas unlikely to generate the greatest global impact. Even the recent approval of lecanemab by the US Food and Drug Administration is tempered by the fact that the cost and infrastructure requirements of this treatment are likely to be prohibitive for LMICs — where most people with dementia reside. The World Health Organization (WHO) global status report on the public health response to dementia in 2017–2025 highlights the need for increased efforts globally to reach the dementia targets set for 2025 by Member States. The report’s bottom line is unequivocal: it is time for the international community to prioritize research on interventions and preventative measures that are likely to benefit all people at risk of dementia.

On 4 October 2022, the WHO released a dementia research blueprint to support implementation of the Global action plan on the public health response to dementia in 2017–2025, representing a first-of-its-kind publication in the context of non-infectious diseases. Leveraging key lessons learned from previous WHO efforts to prioritize and coordinate research into infectious diseases, the blueprint emphasizes key objectives across the entire dementia research spectrum that will have the greatest impact on the global burden of this devastating disorder. For example, a better understanding of the prevalence and incidence of dementia, the costs of illness and the prevalence and impact of risk factors is needed in LMICs and other ethnic and regional groups. Research into the mechanisms of dementia, such as biomarkers and genetic and epigenetic markers, should include and account for differences in these groups. This may require improved engagement and collaboration with communities that may be less willing or unable to participate in these types of studies.

Studies in HICs have reported a decrease in the prevalence of dementia, linked to modifiable dementia risk factors. These exciting findings suggest that modification of risk factors could slow cognitive decline and delay the onset of dementia, or prevent it altogether. Given the costs of dementia care, primary prevention is likely to be the cheapest and easiest way to reduce the projected global impact of dementia. Yet there are little data available on modifiable risk factors in LMICs or in culturally, ethnically and sexually diverse sub-populations in both HICs and LMICs. Furthermore, the data used to calculate these risk factors are from HICs, despite studies showing that some risk factors are more prevalent than others in LMICs and account for more cases of dementia there than in the rest of the world . Differing environmental and social exposures also influence dementia risk. This includes exposure to air pollution and pesticides, which is associated with an increased dementia risk, whereas proximity to green spaces is linked to positive cognitive outcomes.

There are also few robust studies on sex-specific risk factors such as early menopause and complications during pregnancy and on the differential effect of risk factors in men and women, as recently shown for cardiovascular events. It is now generally accepted that longevity alone is not responsible for sex differences seen in dementia, and studies are increasingly highlighting a biological component. Men and women with Alzheimer’s disease (AD) exhibit different cognitive and psychiatric symptoms, and women show faster cognitive decline after a diagnosis of mild cognitive impairment or AD dementia. Epidemiological studies demonstrate that the allele encoding apolipoprotein E confers different AD risk profiles on the basis of sex, with women who have the allele encoding apolipoprotein E-ε4 being at greater risk for developing AD than age-matched men are. Despite these findings, little to no data are available on sex differences in the efficacy and safety of drugs used in recently completed phase 3 clinical trials for mild to moderate AD. Furthermore, women remain under-represented in clinical trials for AD . Systematic studying and reporting of sex differences in disease symptomatology, biomarkers, progression, risk factors and treatment responses will be crucial for efforts to reduce the global impact of dementia.

Funding is obviously the key driver of research. Data for 2019 indicate that although funding for dementia has increased, it is directed mainly toward research in HICs. Of the 50 organizations and institutions that received the most grants for dementia research in 2019, 41 were in the United States, 6 were in the United Kingdom and 3 were in Canada. Furthermore, the vast majority of funding is directed toward research into AD, despite the fact that dementia is caused by several diseases. Although increased funding for dementia research is a step in the right direction, this needs to happen in a more structured and equitable fashion.

Dementia is highly complex, and the challenge of tackling the global burden of this disorder cannot be overcome by people working in silos. Considerable research gaps exist in the understanding of this disorder, particularly in areas in which its burden is greatest. Closing these gaps requires implementation of a harmonized global research plan with equitable inclusion and research capacity-building in under-resourced settings. Only such a level of global research prioritization can ensure that ongoing research efforts deliver the greatest impact possible.

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Dementia research needs a global approach. Nat Med 29 , 279 (2023). https://doi.org/10.1038/s41591-023-02249-z

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• Multiple adverse...

Multiple adverse outcomes associated with antipsychotic use in people with dementia: population based matched cohort study

Linked editorial.

Use of antipsychotics in adults with dementia

• Related content
• Peer review
• Pearl L H Mok , research fellow 1 2 ,
• Matthew J Carr , research fellow 1 2 3 ,
• Bruce Guthrie , professor 4 ,
• Daniel R Morales , Wellcome Trust clinical research fellow 5 ,
• Aziz Sheikh , professor 6 7 ,
• Rachel A Elliott , professor 3 8 ,
• Elizabeth M Camacho , senior research fellow 8 ,
• Tjeerd van Staa , professor 9 ,
• Anthony J Avery , professor 3 10 ,
• Darren M Ashcroft , professor 1 2 3
• 1 Centre for Pharmacoepidemiology and Drug Safety, Division of Pharmacy and Optometry, University of Manchester, Manchester, M13 9PT, UK
• 2 Manchester Academic Health Science Centre, Manchester, UK
• 3 NIHR Greater Manchester Patient Safety Research Collaboration, University of Manchester, Manchester, UK
• 4 Advanced Care Research Centre, Usher Institute, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK
• 5 Population Health and Genomics, University of Dundee, Dundee, UK
• 6 Usher Institute, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK
• 7 Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
• 8 Manchester Centre for Health Economics, Division of Population Health, Manchester, UK
• 9 Division of Informatics, Imaging and Data Sciences, University of Manchester, Manchester, UK
• 10 Centre for Primary Care, School of Medicine, University of Nottingham, Nottingham, UK
• Correspondence to: P L H Mok pearl.mok{at}manchester.ac.uk
• Accepted 29 February 2024

Objective To investigate risks of multiple adverse outcomes associated with use of antipsychotics in people with dementia.

Design Population based matched cohort study.

Setting Linked primary care, hospital and mortality data from Clinical Practice Research Datalink (CPRD), England.

Population Adults (≥50 years) with a diagnosis of dementia between 1 January 1998 and 31 May 2018 (n=173 910, 63.0% women). Each new antipsychotic user (n=35 339, 62.5% women) was matched with up to 15 non-users using incidence density sampling.

Main outcome measures The main outcomes were stroke, venous thromboembolism, myocardial infarction, heart failure, ventricular arrhythmia, fracture, pneumonia, and acute kidney injury, stratified by periods of antipsychotic use, with absolute risks calculated using cumulative incidence in antipsychotic users versus matched comparators. An unrelated (negative control) outcome of appendicitis and cholecystitis combined was also investigated to detect potential unmeasured confounding.

Results Compared with non-use, any antipsychotic use was associated with increased risks of all outcomes, except ventricular arrhythmia. Current use (90 days after a prescription) was associated with elevated risks of pneumonia (hazard ratio 2.19, 95% confidence interval (CI) 2.10 to 2.28), acute kidney injury (1.72, 1.61 to 1.84), venous thromboembolism (1.62, 1.46 to 1.80), stroke (1.61, 1.52 to 1.71), fracture (1.43, 1.35 to 1.52), myocardial infarction (1.28, 1.15 to 1.42), and heart failure (1.27, 1.18 to 1.37). No increased risks were observed for the negative control outcome (appendicitis and cholecystitis). In the 90 days after drug initiation, the cumulative incidence of pneumonia among antipsychotic users was 4.48% (4.26% to 4.71%) versus 1.49% (1.45% to 1.53%) in the matched cohort of non-users (difference 2.99%, 95% CI 2.77% to 3.22%).

Conclusions Antipsychotic use compared with non-use in adults with dementia was associated with increased risks of stroke, venous thromboembolism, myocardial infarction, heart failure, fracture, pneumonia, and acute kidney injury, but not ventricular arrhythmia. The range of adverse outcomes was wider than previously highlighted in regulatory alerts, with the highest risks soon after initiation of treatment.

Introduction

Dementia is a clinical syndrome characterised by progressive cognitive decline and functional disability, with estimates suggesting that by 2050 around 152.8 million people globally will be affected. 1 Behavioural and psychological symptoms of dementia are common aspects of the disease and include features such as apathy, depression, aggression, anxiety, irritability, delirium, and psychosis. Such symptoms can negatively impact the quality of life of patients and their carers and are associated with early admission to care. 2 3 Antipsychotics are commonly prescribed for the management of behavioural and psychological symptoms of dementia, despite longstanding concerns about their safety. 4 5 6 During the covid-19 pandemic, the proportion of people with dementia prescribed antipsychotics increased, possibly owing to worsened behavioural and psychological symptoms of dementia linked to lockdown measures or reduced availability of non-pharmaceutical treatment options. 7 According to guidelines from the UK’s National Institute for Health and Care Excellence, antipsychotics should only be prescribed for the treatment of behavioural and psychological symptoms of dementia if non-drug interventions have been ineffective, if patients are at risk of harming themselves or others or are experiencing agitation, hallucinations, or delusions causing them severe distress. 8 Antipsychotics should at most be prescribed at the lowest effective dose and for the shortest possible time. Only two antipsychotics, risperidone (an atypical, or second generation, antipsychotic) and haloperidol (a typical, or first generation, antipsychotic), are licensed in the UK for the treatment of behavioural and psychological symptoms of dementia, 9 although others have been commonly prescribed off-label. 5 10

Based on evidence from clinical trials of risperidone, the US Food and Drug Administration (FDA) first issued a warning in 2003 about the increased risks of cerebrovascular adverse events (eg, stroke, transient ischaemic attack) associated with use of atypical antipsychotics in older adults with dementia. 11 A meta-analysis of 17 trials among such patients subsequently found a 1.6-1.7-fold increased risk of mortality with atypical antipsychotics compared with placebo, which led the FDA to issue a “black box” warning in 2005 for all atypical antipsychotics. 11 This warning was extended to typical antipsychotics in 2008, after two observational studies reported that the risk of death associated with their use among older people might be even greater than for atypical antipsychotics. 12 13 14 The increased risks for stroke and mortality have been consistently reported by many observational studies and meta-analyses since, 11 15 16 17 18 19 20 21 and they have led to regulatory safety warnings and national interventions in the UK, US, and Europe, aiming to reduce inappropriate prescribing of these drugs for the treatment of behavioural and psychological symptoms of dementia. 8 11 22 23 24 25 26 Other adverse outcomes have also been investigated in observational studies, 27 28 29 although, with the exception of pneumonia, 14 30 31 32 the evidence is less conclusive or is more limited among people with dementia. For example, inconsistent or limited evidence has been found for risks of myocardial infarction, 33 34 ventricular arrhythmia, 35 36 venous thromboembolism, 37 38 39 40 fracture, 41 42 43 and acute kidney injury. 44 45 46 Most studies also reported only one outcome or type of outcomes. Examining multiple adverse events in a single cohort is needed to give a more comprehensive estimate of the total potential harm associated with use of antipsychotics in people with dementia.

Using linked primary and secondary care data in England, we investigated the risks of a range of adverse outcomes potentially associated with antipsychotic use in a large cohort of adults with dementia—namely, stroke, venous thromboembolism, myocardial infarction, heart failure, ventricular arrhythmia, fracture, pneumonia, and acute kidney injury. We report both relative and absolute risks.

Data sources

The study used anonymised electronic health records from Clinical Practice Research Datalink (CPRD). In the UK, residents are required to be registered with a primary care general practice to receive care from the NHS. The NHS is a publicly funded healthcare service, free at the point of use. More than 98% of the UK population are registered with a general practice, and their electronic health records are transferred when they change practice. 47 48 Community prescribing is most often done by the general practitioner, including antipsychotic treatment recommended by specialists. CPRD data are sourced from more than 2000 general practices covering around 20% of the UK population, and include information on diagnoses, primary healthcare contacts, prescribed drugs, laboratory test results, and referrals to secondary healthcare services. 47 48 CPRD contains two databases: Aurum and GOLD. CPRD Aurum includes data from contributing general practices in England that use the EMIS Web patient management software, and CPRD GOLD consists of patient data from practices across all four UK nations that use the Vision system. Both datasets are broadly representative of the UK population. 47 48 49 Primary care data from general practices in England can be linked to other datasets, including hospital admissions in Hospital Episode Statistics, and mortality and index of multiple deprivation data from the Office for National Statistics (ONS). Individual patients can opt-out of sharing their records with CPRD, and individual patient consent was not required as all data were deidentified.

Study population

We delineated two cohorts, one each from Aurum and GOLD. For the latter, we included patients from English practices only because linkage to hospital admission and mortality data were required in our analyses. To ensure that the study dataset would not contain any duplicate patient records, we used the bridging file provided by CPRD to identify English practices that have migrated from the GOLD to the Aurum dataset, and removed such practices from the GOLD dataset. For both cohorts, we included patients who had a first dementia diagnosis code between 1 January 1998 and 31 May 2018. Dementia was identified from Read, SNOMED, or EMIS codes used in the databases (see supplementary appendix). We defined the date of first dementia diagnosis as the date of first dementia code. Patients needed to be aged 50 years or over at the time of dementia diagnosis, have been registered with the CPRD practice for at least a year, not be prescribed an antipsychotic in the 365 days before their first dementia code, and have records that were eligible for linkage to Hospital Episodes Statistics, mortality, and index of multiple deprivation data. In addition, because anticholinesterases (such as donepezil, rivastigmine, and galantamine) may sometimes be prescribed to patients showing signs of dementia before their first dementia code, we excluded patients with an anticholinesterase prescription before their first dementia code. Supplementary figures S1 and S2 show how the two cohorts for Aurum and GOLD, respectively, were delineated.

Study design

Matched cohort design —We implemented a matched cohort design. Supplementary figure S3 shows the study design graphically. 50 For the Aurum and GOLD cohorts separately, patients who used antipsychotics were defined as patients in each cohort issued with an antipsychotic prescription after (or on the same day as) the date of their first dementia diagnosis, with the date of first antipsychotic prescription being the index date after which outcomes were measured. For each outcome, follow-up began from the date of the first antipsychotic prescription (the index date) and ended on the earliest of date of first diagnosis of outcome (ie, the earliest recording of the outcome whether it was from the patient’s primary or secondary care or mortality records), death, transfer out of the general practice, last data collection date of the general practice, two years from the date of antipsychotics initiation, or 31 May 2018. Because patients who have experienced an outcome were potentially at higher risk of subsequently experiencing the same event, which could confound any risks associated with antipsychotic use, we excluded those with a history of the specific outcome under investigation before the index date from the analysis of that outcome. For example, we excluded patients with a record of stroke before the index date from the analysis of stroke, but they would still be eligible for the study of other outcomes. For the analysis of acute kidney injury, patients with a diagnosis of end stage kidney disease before the index date were also excluded, and a diagnosis of end stage kidney disease after the index date was an additional condition for end of follow-up. 44

Matched comparators —Each patient who used antipsychotics on or after the date of their first dementia diagnosis was matched using incidence density sampling with up to 15 randomly selected patients who had the same date of first dementia diagnosis (or up to 56 days after) and who had not been prescribed an antipsychotic before diagnosis. Incidence density sampling involves matching on sampling time, with each antipsychotic user in our study being matched to one or more comparators who were eligible for an antipsychotic but had not become a user at the time of matching. 51 The selection of comparators was done with replacement—that is, an individual could be used as a comparator in multiple matched sets. In our study, this meant that patients were eligible to be a non-user matched comparator up to the date of their first antipsychotic prescription. We excluded matched comparators with a history of the specific outcome under investigation before the index date from the analysis of that event. For each outcome, follow-up of matched comparators began on the same day as the patient to whom they were matched (the index date) and ended on the earliest of date of their first antipsychotic prescription (if any), or date of one of the end of follow-up events described earlier for the antipsychotic users.

Use of antipsychotics

We included both typical and atypical antipsychotics, identified by product codes in Aurum and GOLD (see supplementary appendix for list of drugs included). Senior author DMA (pharmacist) reviewed the code lists. As previous studies have shown a temporal association between antipsychotic use and development of adverse outcomes, 30 31 52 we treated use of antipsychotics as a time varying variable, classified as current, recent, and past use. Current use was defined as the first 90 days from the date of an antipsychotic prescription, recent use as up to 180 days after current use ended, and past use as the time after the recent use period had ended. If a patient was issued another prescription during the 90 days after their last prescription, their current use period would be extended by 90 days from the date of their latest prescription. For example, if a patient had two prescriptions and the second was issued 60 days after the first, their current use period would be a total of 150 days: 60 days after the first prescription plus 90 days after the second. At the end of the 150 days current use period, the next 180 days would be the recent use period, and the time after this recent use period would be past use. As patients could have multiple prescriptions over time, they could move between the three antipsychotic use categories during follow-up, and they could therefore be defined as current, recent, or past users more than once. See the supplementary appendix for further information on how this definition is applied.

In post hoc analyses, we also investigated typical versus atypical antipsychotics, and specific drug substances: haloperidol, risperidone, quetiapine, and other antipsychotics (as a combined category).

Outcomes were stroke, venous thromboembolism (including deep vein thrombosis and pulmonary embolism), myocardial infarction, heart failure, ventricular arrhythmia, fracture, pneumonia, and acute kidney injury. With the exceptions of pneumonia and acute kidney injury, outcomes were identified by Read, SNOMED, or EMIS codes in the primary care records, and by ICD-10 (international classification of diseases, 10th revision) codes from linked secondary care data from Hospital Episodes Statistics, and cause of death data from the ONS mortality records. For pneumonia and acute kidney injury, we only included those that were diagnosed in hospitals or as a cause of death, ascertained from Hospital Episodes Statistics and ONS data.

We also investigated appendicitis and cholecystitis combined as an unrelated (negative control) outcome to detect potential unmeasured confounding. 53 These outcomes were chosen because evidence of an association with antipsychotic use is lacking from the literature. We identified appendicitis and cholecystitis from Read, SNOMED, EMIS, and ICD-10 codes. Clinicians (BG, AJA, DRM) checked all code lists (see supplementary appendix).

We used propensity score methods to control for imbalances in measurable patient characteristics between antipsychotic users and their matched non-users, with personal characteristics, lifestyle, comorbidities, and prescribed drugs included in the propensity score models. A counterfactual framework for causal inference was applied to estimate the average treatment effect adjusting for inverse probability of treatment weights generated from the propensity score models. 54 55 Selection of covariates was informed by the literature, based on their potential associations with antipsychotic initiation and study outcomes. 31 34 44 56 57 All variables were assessed before the index date (see supplementary figure S3). Variables for personal characteristics included sex, age at dementia diagnosis, age at start of follow-up, ethnicity, and index of multiple deprivation fifths based on the location of the general practice. Comorbidities were derived as dichotomous variables and included a history of hypertension, types 1 and 2 diabetes mellitus, chronic obstructive pulmonary disease, rheumatoid arthritis, moderate or severe renal disease, moderate or severe liver disease, atrial fibrillation, cancer, and serious mental illness (bipolar disorders, schizophrenia, schizoaffective disorders, and other psychotic disorders). Lifestyle factors included smoking status and alcohol use. Medication covariates were represented as dichotomous indicators, defined by at least two prescriptions for each of the following drugs in the 12 months before the index date: antiplatelets, oral anticoagulants, angiotensin converting enzyme inhibitors or angiotensin II receptor blockers, alpha blockers, beta blockers, calcium channel blockers, diuretics, lipid lowering drugs, insulin and antidiabetic drugs, non-steroidal anti-inflammatory drugs, antidepressants, benzodiazepines, and lithium. We also included the following potential confounders for the investigations of venous thromboembolism and fracture: prescriptions for hormone replacement therapy and selective oestrogen receptor modulators (for venous thromboembolism), 58 59 a history of inflammatory bowel disease (for pneumonia and fracture), 60 61 and prescriptions for immunosuppressants, oral corticosteroids, and inhaled corticosteroids (for pneumonia). 62 63

Statistical analysis

For each patient included in the study, we derived a propensity score representing the patient’s probability of receiving antipsychotic treatment. Propensity scores were estimated using multivariable logistic regression, with antipsychotic use as the dependent variable. Predictors included personal characteristics, lifestyle, comorbidities, and prescribed drugs. Patients with missing information on ethnicity, index of multiple deprivation, smoking, or alcohol use were grouped into an unknown category for each of these variables and included in the propensity score models. We used the Hosmer-Lemeshow test and likelihood ratio test to test the fit of the models, and interaction terms were included to improve the model fit. 64 The derived scores were used as inverse probability of treatment weights to reweigh the data, balancing the distribution of baseline covariates between antipsychotic users and non-users (matched comparators)—that is, standardised differences <0.1 after weighting. 65 Propensity score models were run for each outcome, and for the Aurum and GOLD cohorts separately. For further information, see the supplementary appendix section on propensity score methods to control for potential confounding.

Analyses for estimating harms were then conducted after combining (appending) the Aurum and GOLD datasets. We used Cox regression survival analyses to estimate the risks of each outcome associated with antipsychotic use relative to the comparator cohort, and we report the results as hazard ratios. Use of an antipsychotic was treated as a time varying variable. To account for the matched design, we fitted stratified models according to the matched sets and used robust variance estimation. In all models, we also included a covariate indicating whether the patient was from the Aurum or GOLD cohort and calculated hazard ratios with adjustments for inverse probability of treatment weights. Cox regression assumes proportional hazards—that is, the relative hazard of the outcome remains constant during the follow-up period. 66 We assessed this assumption using the Grambsch-Therneau test based on the Schoenfeld residuals. 67 Because this assumption did not hold for all outcomes examined, in addition to reporting the hazard ratios pertaining to the whole follow-up period, we estimated hazard ratios separately for the several time windows: the first seven days, 8-30 days, 31-180 days, 181-365 days, and 366 days to two years (see supplementary appendix for an illustration of stratification of follow-up time). For each outcome, we calculated the incidence rate and the number needed to harm (NNH) over the first 180 days as well as two years after start of follow-up. The NNH represents the number of patients needed to be treated with an antipsychotic for one additional patient to experience the outcome compared with no treatment. We also calculated cumulative incidence percentages (absolute risks) for each outcome accounting for competing mortality risks based on previous recommendations. 68 These were calculated at 90 days, 180 days, 365 days, and two years after start of follow-up for antipsychotic users and their matched comparators separately. We also reported the difference in cumulative incidence between antipsychotic users and their matched comparators at these time points. Analyses were conducted using Stata/MP v16.1.

Sensitivity analyses

We investigated two other definitions of antipsychotic use as sensitivity analyses: the first 60 days as current use followed by 120 days of recent use, and a current use period of 30 days followed by a recent use period of 60 days. We also conducted the following post hoc sensitivity analyses. Firstly, as levomepromazine is often prescribed in palliative care to treat distressing symptoms in the last days of life, 69 we censored individuals at the time of their first levomepromazine prescription. Secondly, we used Fine-Gray subdistribution hazard regression models to estimate the hazard of each adverse outcome, accounting for the competing risks of death. 70 These results were reported as subhazard ratios. Thirdly, we compared the incidence rates and hazards of adverse outcomes for male versus female individuals. For these sex specific analyses, we modified the existing matched cohort by excluding non-user comparators who were of a different sex from the antipsychotic user to whom they were matched. We then derived a new propensity score for each individual by excluding sex as a covariate in the propensity score models. Incidence rate ratios and corresponding 95% confidence intervals (CIs) for male versus female individuals were calculated using the ‘iri’ command in Stata. To investigate whether hazards of each adverse outcome associated with antipsychotic use differed by sex, we fitted Cox regression models with sex, antipsychotic use, and their interaction as covariates. Sex specific hazard ratios and ratios of male to female hazard ratios were reported.

Patient and public involvement

This study is part of a National Institute of Health and Care Research funded programme (RP-PG-1214-20012): Avoiding patient harm through the application of prescribing safety indicators in English general practices (PRoTeCT). Two patient and public involvement members in the project team contributed to the study design and protocol of this study. Our study was not, however, coproduced with people with dementia or their carers.

Characteristics of study population

A total of 173 910 adults (63.0% women) with dementia were eligible for inclusion in the study: 139 772 (62.9% women) in the Aurum dataset and 34 138 (63.4% women) in GOLD. The mean age at dementia diagnosis for individuals in both cohorts was 82.1 years (standard deviation (SD) 7.9 years), and the median age was 83 years (interquartile range (IQR) 78-88 years in Aurum and 78-87 years in GOLD). A total of 35 339 individuals (62.5% women; 28 187 in Aurum, 62.6% women; 7152 in GOLD, 62.5% women) were prescribed an antipsychotic during the study period, and a matched set was generated for each of these individuals. The mean number of days between first dementia diagnosis and date of a first antipsychotic prescription was 693.8 ((SD 771.1), median 443 days) in Aurum and 576.6 ((SD 670.0), median 342 days) in GOLD. A total of 544 203 antipsychotic prescriptions (433 694 in Aurum, 110 509 in GOLD) were issued, of which 25.3% were for a typical antipsychotic and 74.7% for an atypical antipsychotic. The most prescribed antipsychotics were risperidone (29.8% of all prescriptions), quetiapine (28.7%), haloperidol (10.5%), and olanzapine (8.8%), which together accounted for almost 80% of all prescriptions (see supplementary table S1).

Since we excluded people with a history of the event before the start of follow-up, the number of individuals and matched sets included in analysis varies by outcome. Table 1 shows the baseline characteristics of patients for the analysis of stroke, before and after inverse probability of treatment weighting. Antipsychotic users were more likely than their matched comparators to have a history of serious mental illness and to be prescribed antidepressants or benzodiazepines in the 12 months before start of follow-up. After inverse probability of treatment weighting, standardised differences were <0.1 for all covariates. Baseline characteristics of individuals included in the analyses of other outcomes were similar to those reported for stroke (see supplementary tables S2-S9).

Baseline characteristics of antipsychotic users and matched comparators included in the analysis of stroke (CPRD Aurum and GOLD combined data). Values are number (percentage) unless stated otherwise

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Incidence rates and relative hazards of adverse outcomes

All antipsychotics.

In the two years after initiation of antipsychotics, the highest incidence rates of adverse outcomes were for pneumonia, fracture, and stroke, and ventricular arrhythmias were rare ( table 2 ). Figure 1 shows the hazard ratios of adverse outcomes associated with current, recent, past, and any use of antipsychotics versus non-use (ie, matched comparators). Except for ventricular arrhythmia, any use of antipsychotics was associated with increased risks for all adverse outcomes, ranging from a hazard ratio of 2.03 (95% CI 1.96 to 2.10) for pneumonia to 1.16 (1.09 to 1.24) for heart failure. Current use (ie, prescribed in the previous 90 days) was associated with high risks for pneumonia (2.19, 2.10 to 2.28), acute kidney injury (1.72, 1.61 to 1.84), venous thromboembolism (1.62, 1.46 to 1.80), and stroke (1.61, 1.52 to 1.71). Recent antipsychotic use (ie, in the 180 days after current use ended) was also associated with increased risk for these outcomes, as well as for fracture, but past use of antipsychotics (ie, after recent use ended) was not associated with increased risks of the adverse outcomes examined, except for pneumonia. For the negative control outcome (appendicitis and cholecystitis), no significant associations were found with current, recent, or any antipsychotic use, but a statistically significant association was observed with past use (1.90, 1.01 to 3.56).

Incidence rate (per 10 000 person years) and number needed to harm of adverse outcomes associated with antipsychotic use during the first 180 days and two years of follow-up period

Hazard ratios (adjusted for inverse probability of treatment weights) of adverse outcomes associated with current, recent, and past antipsychotic use; with current use being defined as the first 90 days from the date of an antipsychotic prescription, recent use as up to 180 days after current use ended, and past use as after recent use. CI=confidence interval

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Table 2 shows that the NNH ranged from 9 (95% CI 9 to 10) for pneumonia to 167 (116 to 301) for myocardial infarction during the first 180 days after initiation of antipsychotics, and from 15 (14 to 16) for pneumonia to 254 (183 to 413) for myocardial infarction after two years. These figures suggest that over the 180 days after drug initiation, use of antipsychotics might be associated with one additional case of pneumonia for every nine patients treated, and one additional case of myocardial infarction for every 167 patients treated. At two years, there might be one additional case of pneumonia for every 15 patients treated, and one additional case of myocardial infarction for every 254 patients treated.

Table 3 shows hazard ratios stratified by follow-up time (except for ventricular arrhythmia and the negative control where the number of patients was very low). For almost all outcomes, relative hazards were highest in the first seven days after initiation of antipsychotic treatment. Risks for pneumonia were particularly increased in the first seven days (9.99, 8.78 to 11.40) and remained substantial afterwards (3.39, 3.04 to 3.77, 8-30 days). No increased risks for heart failure were found for current users after 180 days from start of treatment, nor for myocardial infarction one year after drug initiation. However, risks for stroke, venous thromboembolism, fracture, pneumonia, and acute kidney injury remained increased among continuous antipsychotic users up to two years after initiation of treatment.

Hazard ratios (adjusted for IPT weights) of adverse outcomes associated with current, recent, and past antipsychotic use stratified by follow-up period

Types of antipsychotics

During the current use period of 90 days after a prescription, both typical and atypical antipsychotics were associated with increased risks of all adverse outcomes compared with non-use, except for ventricular arrhythmia and the negative control (see supplementary table S10). Hazards were higher when current use of typical antipsychotics was directly compared with atypical antipsychotics for stroke (1.23, 1.09 to 1.40), heart failure (1.18, 1.01 to 1.39), fracture (1.22, 1.08 to 1.38), pneumonia (1.92, 1.77 to 2.08), and acute kidney injury (1.22, 1.05 to 1.42), but no significant differences between the two types of drug were found for the risks of venous thromboembolism or myocardial infarction.

Supplementary table S11 shows the risks of adverse outcomes associated with haloperidol (the most prescribed typical antipsychotic) and with risperidone and quetiapine (the two most prescribed atypical antipsychotics). Current use of risperidone and haloperidol compared with non-use was associated with increased risks of all adverse outcomes except for ventricular arrhythmia and the negative control. Current use of quetiapine compared with non-use was associated with increased risks for fracture, pneumonia, and acute kidney injury. Among current users of haloperidol or risperidone, risks for fracture, pneumonia, and acute kidney injury were higher for haloperidol versus risperidone, but risks for stroke, venous thromboembolism, myocardial infarction, and heart failure were similar for both drugs. With the exceptions of myocardial infarction, ventricular arrhythmia, and the negative control, risks of all adverse outcomes were higher for haloperidol than for quetiapine, especially for pneumonia (2.53, 2.21 to 2.89) and venous thromboembolism (1.99, 1.33 to 2.97). Among current users of quetiapine compared with risperidone, there were no significant differences in risks for myocardial infarction, heart failure, or fracture. However, risks for stroke (0.64, 0.53 to 0.78), venous thromboembolism (0.49, 0.36 to 0.68), pneumonia (0.72, 0.63 to 0.81), and acute kidney injury (0.81, 0.67 to 0.96) were lower for quetiapine than for risperidone.

Absolute risks of adverse outcomes

Cumulative incidence for all outcomes examined was higher for antipsychotic users versus matched comparators, except for ventricular arrhythmia and the negative control ( table 4 ). The absolute risk, as well as risk difference, was particularly large for pneumonia. In the 90 days after initiation of an antipsychotic, the cumulative incidence of pneumonia among antipsychotic users was 4.48% (95% CI 4.26% to 4.71%) v 1.49% (1.45% to 1.53%) in the matched cohort of non-users (difference 2.99%, 95% CI 2.77% to 3.22%). At one year, this increased to 10.41% (10.05% to 10.78%) for antipsychotic users compared with 5.63% (5.55% to 5.70%) for non-users (difference 4.78%, 4.41% to 5.16%).

Cumulative incidence of adverse outcomes associated with antipsychotic use at 90, 180, and 365 days and at two years after start of follow-up

Similar results were found in sensitivity analysis using two other definitions of antipsychotic use (see supplementary figures S4 and S5). Of the 544 203 antipsychotic prescriptions issued, 1.3% were for levomepromazine (see supplementary table S1). Results remained similar when patients were censored at the time of their first levomepromazine prescription (see supplementary figure S6). Results of the Fine-Gray models accounting for the competing risks of death also showed broadly similar patterns of hazards to those from the Cox models (see supplementary table S12 and figure S7). Sex specific analyses showed that male patients had higher incidence rates of all adverse outcomes than female patients, except for fracture and venous thromboembolism where incidence was higher for female patients than for male patients (see supplementary table S13). Compared with female antipsychotic users, male users had increased hazards for pneumonia and acute kidney injury (male to female hazard ratio 1.16, 95% CI 1.08 to 1.25 for pneumonia and 1.22, 1.08 to 1.37 for acute kidney injury), but lower hazards for stroke (0.81, 0.73 to 0.91). No significant differences were found by sex in the hazards for venous thromboembolism, myocardial infarction, heart failure, ventricular arrhythmia, or fracture (see supplementary table S14).

In this population based cohort study of adults (≥50 years) with dementia, use of antipsychotics compared with non-use was associated with increased risks for stroke, venous thromboembolism, myocardial infarction, heart failure, fracture, pneumonia, and acute kidney injury. Increased risks were observed among current and recent users and were highest in the first week after initiation of treatment. In the 90 days after a prescription, relative hazards were highest for pneumonia, acute kidney injury, stroke, and venous thromboembolism, with increased risks ranging from 1.5-fold (for venous thromboembolism) to twofold (for pneumonia) compared with non-use. No increased risk was found for ventricular arrhythmia or the negative control outcome (appendicitis and cholecystitis). Absolute risk differences between antipsychotic users and their matched comparators were substantial for most adverse events, and largest for pneumonia. In the 90 days after a prescription, risks of stroke, heart failure, fracture, pneumonia, and acute kidney injury were higher for typical antipsychotics versus atypical antipsychotics, whereas no significant differences between these two drug classes were found for risks of venous thromboembolism or myocardial infarction. Haloperidol was associated with higher risks for fracture, pneumonia, and acute kidney injury than risperidone, but no significant differences between the two drugs were found for the other outcomes. Risks of almost all adverse outcomes were higher for haloperidol than for quetiapine. No significant differences were found between risperidone and quetiapine for risks of myocardial infarction, heart failure, or fracture, but risks for stroke, venous thromboembolism, pneumonia, and acute kidney injury were lower for quetiapine versus risperidone.

Comparison with other studies

A population based study in Wales reported no increased risks for non-fatal acute cardiac events associated with antipsychotic use in patients with all cause dementia, although those with Alzheimer’s disease showed increased risks. 37 Systematic reviews and meta-analyses of studies not limited to patients with dementia have also reported inconsistent evidence for myocardial infarction, or lack of robustness of these data. 33 34 71 Our findings for myocardial infarction were similar to those in a study that first documented a modest and time limited increase in risk of this outcome associated with antipsychotic use among patients with dementia. 56 In a study of nursing home residents in the US, users of typical, but not atypical, antipsychotics were more likely than non-users to be admitted to hospital for ventricular arrhythmia or cardiac arrest, 35 and a study not limited to older people reported increased risks for ventricular arrhythmia or sudden cardiac death associated with both typical and atypical antipsychotics. 36 We did not find any association with ventricular arrhythmia, but the number of events was low and we did not examine cardiac arrest or sudden death.

Increased risks of venous thromboembolism associated with antipsychotic use have been reported in the general population, 38 but meta-analyses found increased risks of venous thromboembolism only among younger users. 39 40 Our findings are consistent with those of the Welsh study, which reported increased risks of venous thromboembolism in the 12 months after drug initiation (prior event rate ratio 1.95, 95% CI 1.83 to 2.0). 37 In absolute terms, however, these risks were relatively low compared with other outcomes examined in this study.

We found that both the relative and the absolute risks for pneumonia were highest among all outcomes examined. Current users of antipsychotics had a twofold increased risk compared with non-users ( fig 1 ), and although this magnitude of increased risk was comparable to previous reports, 14 31 32 we additionally observed that risks were greater in the first week after drug initiation. One study also reported a particularly high risk for patients with hospital diagnosed pneumonia in the first week, but the magnitude of increase (odds ratio 4.5, 95% CI 2.8 to 7.3) was much lower than our observation. 30 The mechanisms linking antipsychotic use and development of pneumonia is not well understood, and substantial heterogeneity exists among the drug substances, but antipsychotic induced extrapyramidal symptoms, sedation, xerostomia (dry mouth), and dyskinesia or impaired swallowing are commonly considered as potential risk factors. 72 In addition, because elderly people with pneumonia may be less likely than younger patients to present with respiratory symptoms but more likely to show signs of delirium, 73 it is possible that reverse causality might have contributed to the high risks observed in the early days after drug initiation, as delirium from the onset of pneumonia might have been treated with antipsychotics before pneumonia was diagnosed. 30 However, although causality cannot be inferred, the particularly high increased risks observed for a range of outcomes and not only for pneumonia in the early days after drug initiation are consistent with other studies. 28 This could be partly explained by further prescriptions being given only to patients who tolerated the first days of drug use.

The use of atypical antipsychotics in older adults (≥65 years) has been shown to be associated with increased risk of acute kidney injury. 44 45 46 Two studies reported significantly increased risks in users compared with non-users in the 90 days after initiation of atypical antipsychotics. 44 45 In contrast, another study observed no increased risks from use of the broad category of atypical antipsychotics, although a significantly increased risk was found with olanzapine. 46 In our study, we found increased risks of acute kidney injury with both typical and atypical antipsychotics, with risks being higher for haloperidol than for risperidone and quetiapine.

In a meta-analysis of observational studies, antipsychotic use was associated with increased risks of hip fracture among people with dementia. 41 A self-controlled case series study of older adult patients (≥65 years) also reported increased risks of falls and fracture after initiation of antipsychotics, but incidence was found to be even higher in the 14 days before treatment started. 43 Similar findings were also reported in another study, suggesting that the risks observed during the treatment periods might not be attributable to the antipsychotics alone. 42 Although we cannot eliminate confounding in our study, we minimised this risk by adjusting for a large number of both clinical and non-clinical characteristics that might have influenced treatment assignment. We also found no increased risks associated with current or recent antipsychotic use for the negative control outcome (appendicitis and cholecystitis).

Our study found that the risks of stroke and heart failure were higher for typical antipsychotics than for atypical antipsychotics, but risks of venous thromboembolism and myocardial infarction were similar between the two drug classes. We also found no significant differences between haloperidol and risperidone in risks of these four outcomes, but significantly increased risks for stroke, venous thromboembolism, and heart failure for haloperidol versus quetiapine. Previous studies of elderly patients have reported similar risks for cardiovascular or cerebrovascular events associated with use of typical and atypical antipsychotics, 17 74 75 76 but risks of these outcomes and of all cause mortality were increased with haloperidol versus risperidone. 21 76 For fracture and pneumonia, we found that risks were higher in association with typical antipsychotics than atypical antipsychotics and for haloperidol versus risperidone or quetiapine. The findings from previous studies comparing these risks by antipsychotic types have been inconsistent. 30 31 32 74 75

Strengths and limitations of this study

A key strength of this study was the investigation of a wide range of adverse events in a large population based cohort, and the reporting of both relative and absolute risk differences over multiple periods. Previous studies commonly focused on a single outcome or type of outcome, such as cerebrovascular events, and on the reporting of relative risks. By examining the same cohort at risk, we were able to directly compare the hazards of multiple outcomes without differential biases between the cohorts. In addition, we only included patients with a clinician recorded diagnosis of dementia, and we adjusted for many variables that might have influenced the probability of antipsychotic initiation, seeking to minimise confounding by indication. CPRD is one of the largest primary care databases in the world, and it is broadly representative of the UK population. 47 48 49 The database includes all prescriptions issued in participating primary care practices in the UK, and it is recognised as a high quality resource to support international pharmacovigilance. 77 The longitudinal nature of CPRD, with linked data from secondary care and mortality records, enabled us to capture the study outcomes from multiple sources, as well as information on prescribing and comorbidities. 78 79 Our findings were also robust to different classifications of usage periods and we found no associations between current and recent antipsychotic use with the development of the negative control outcome (appendicitis and cholecystitis). However, a significant association with past use was observed that we are unable to explain.

As with all observational studies, residual confounding cannot be excluded. For example, polypharmacy is common among elderly people, which could lead to drug-drug interactions and potentially confound our findings. 80 81 We also did not have information on indications for antipsychotics treatment. We minimised the risk of confounding using propensity score methods to control for imbalances in measurable patient characteristics between antipsychotic users and their matched comparators. However, unlike randomised control trials, which, if properly conducted, could account for both observed and unobserved differences between treated and untreated groups, the propensity score method can only adjust for the observed differences between two groups. Additionally, our choice of covariates was based on the literature and discussions with clinical experts and was not formally structured using, for example, a directed acyclic graph. Although the strong associations with pneumonia in the first seven days of antipsychotic initiation may partially be attributed to reverse causality, however, it is less likely to explain associations over longer periods. We also found no increased risk for appendicitis and cholecystitis during current and recent use—our negative control outcome that was included to detect potential unmeasured confounding. 53 Another limitation of our study is that although prescriptions issued in primary care are reliable in CPRD, information on dosage is not well recorded and information on drug adherence or prescriptions issued while patients are in hospital is not available. 48 Misclassification of drug use is therefore a potential problem. As with other electronic health data that are routinely collected for administrative rather than research purposes, potential issues exist with coding errors, missing or incomplete information, and variations in data quality between practices and healthcare settings. Although the data undergo quality checks before being released and our use of the linked data would have helped to deal with such problems, we were restricted to data coded in patients’ electronic health records. In addition, despite the representativeness of the CPRD data, care should be taken in making inferences beyond the population studied. Our sex specific investigations were also conducted as post hoc analyses. By using existing matched sets but restricting the comparators to those of the same sex as the antipsychotic user to whom they were matched, the number of comparators was greatly reduced. Although we found some evidence of differences in hazards for stroke, pneumonia, and acute kidney injury between male and female antipsychotic users, further research is needed to validate these findings.

Policy implications

The mechanisms underlying the links between antipsychotics and the outcomes in our study are not fully understood. In the UK, US, and Europe, current regulatory warnings for using antipsychotics to treat behavioural and psychological symptoms of dementia were mostly based on evidence of increased risks for stroke and mortality. 8 11 22 23 24 25 26 We found a considerably wider range of harms associated with antipsychotic use in people with dementia, and the risks of harm were highest soon after initiation. Our findings must be seen in the context of trial evidence of at best modest benefit on behavioural and psychological symptoms of dementia. The efficacy of antipsychotics in the management of behavioural and psychological symptoms of dementia remains inconclusive. 82 83 84 85 Atypical antipsychotics, including risperidone, which is one of two antipsychotics licensed in the UK for the treatment of behavioural and psychological symptoms of dementia, have the strongest evidence base, but the benefits are only modest. 82 85

Any potential benefits of antipsychotic treatment therefore need to be weighed against the risk of serious harm across multiple outcomes. Although there may be times when an antipsychotic prescription is the least bad option, clinicians should actively consider the risks, considering patients’ pre-existing comorbidities and living support. The NNH reported in this study can help to inform clinical judgements on the appropriateness of treatments, taking account of the modest potential benefits reported in clinical trials. When prescriptions of such drugs are needed, treatment plans should be reviewed regularly with patients and their carers to reassess the need for continuing treatment. 9 In addition, given the higher risks of adverse events in the early days after drug initiation, clinical examinations should be taken before, and clinical reviews conducted shortly after, the start of treatment. Our study reaffirms that these drugs should only be prescribed for the shortest period possible. 9 Although regulators have made efforts to limit the use of these drugs to people with the most severe behavioural and psychological symptoms of dementia, 8 82 86 antipsychotic prescribing in dementia remains common and has even increased in recent years. 4 5 87 88 If such trends continue, further communication on the associated risks could be considered by guideline developers or regulators after a review of the totality of evidence. Greater accountability and monitoring in the use of these drugs may be called for, and additional legal reforms may be required to regulate adherence. 89 In recent years, other psychotropic drugs such as antidepressants, benzodiazepines, mood stabilisers, and anticonvulsants have been prescribed instead of antipsychotics for the treatment of behavioural and psychological symptoms of dementia. 28 90 91 These drugs, however, also pose their own risks. Further research is needed into safer drug treatment of behavioural and psychological symptoms of dementia and more efficacious, easy to deliver, initial non-drug treatments.

Conclusions

Antipsychotic use is associated with a wide range of serious adverse outcomes in people with dementia, with relatively large absolute risks of harm for some outcomes. These risks should be considered in future regulatory decisions, alongside cerebrovascular events and mortality. Any potential benefits of antipsychotic treatment need to be weighed against risk of serious harm, and treatment plans should be reviewed regularly. The effect of antipsychotics on behavioural and psychological symptoms of dementia is modest at best, but the proportion of people with dementia prescribed antipsychotics has increased in recent years. Our finding that antipsychotics are associated with a wider range of risks than previously known is therefore of direct relevance to guideline developers, regulators, and clinicians considering the appropriateness of antipsychotic prescribing for behavioural and psychological symptoms of dementia.

What is already known on this topic

Despite safety concerns, antipsychotics continue to be frequently prescribed for the management of behavioural and psychological symptoms of dementia

Current regulatory warnings for the treatment of behavioural and psychological symptoms of dementia using antipsychotics are based on evidence of increased risks of stroke and death

Evidence for other adverse outcomes is less conclusive or is more limited among people with dementia, and comparisons of risks for multiple adverse events are also difficult owing to different study designs and populations

What this study adds

Antipsychotic use in people with dementia was associated with increased risks of stroke, venous thromboembolism, myocardial infarction, heart failure, fracture, pneumonia, and acute kidney injury, compared with non-use, but not ventricular arrhythmia

Relative hazards were highest for pneumonia, acute kidney injury, stroke, and venous thromboembolism, and absolute risk and risk difference between antipsychotic users and their matched comparators was largest for pneumonia

Risks of these wide ranging adverse outcomes need to be considered before prescribing antipsychotic drugs to people with dementia

Ethics statements

Ethical approval.

This study was approved by the Clinical Practice Research Datalink’s (CPRD) independent scientific advisory committee (protocol 18_168). CPRD also has ethical approval from the Health Research Authority to support research using anonymised patient data (research ethics committee reference 21/EM/0265). 92 Individual patient consent was not required as all data were deidentified.

Data availability statement

Electronic health records are, by definition, considered sensitive data in the UK by the Data Protection Act and cannot be shared via public deposition because of information governance restriction in place to protect patient confidentiality. Access to Clinical Practice Research Datalink (CPRD) data is subject to protocol approval via CPRD’s research data governance process. For more information see https://cprd.com/data-access . Linked secondary care data from Hospital Episodes Statistics, mortality data from the Office for National Statistics, and index of multiple deprivation data can also be requested from CPRD.

Acknowledgments

We thank Hayley Gorton and Thomas Allen for their contribution to the protocol development, Evan Kontopantelis for his statistical advice, and members of our patient and public involvement team, Antony Chuter and Jillian Beggs, for their contributions to this project. This study is based on data from the Clinical Practice Research Datalink obtained under licence from the UK Medicines and Healthcare Products Regulatory Agency (MHRA). The data are provided by patients and collected by the NHS as part of its care and support. Hospital Episode Statistics and Office for National Statistics mortality data are subject to Crown copyright (2022) protection, reused with the permission of The Health and Social Care Information Centre, all rights reserved. The interpretation and conclusions contained in this study are those of the authors alone, and not necessarily those of the MHRA, National Institute of Health and Care Research, NHS, or Department of Health and Social Care. The study protocol was approved by Clinical Practice Research Datalink’s independent scientific advisory committee (reference: 18_168). We would like to acknowledge all the data providers and general practices who make anonymised data available for research.

Contributors: All authors conceived and designed the study and acquired, analysed, or interpreted the data. BG, DRM, TvS, AJA, and DMA reviewed the clinical codes. PLHM conducted the statistical analyses and wrote the first draft of the manuscript. All authors critically revised the manuscript for important intellectual content and approved the final version. AJA, DMA, RAE, BG, DRM, AS, and TvS obtained the funding. PLHM is the guarantor. The corresponding author (PLHM) attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

Funding: This study was funded by the National Institute for Health and Care Research (NIHR, RP-PG-1214-20012). MJC, AJA, and DMA were supported by the NIHR Greater Manchester Patient Safety Translational Research Centre (PSTRC-2016-003) at the time of this study and are now supported by the NIHR Greater Manchester Patient Safety Research Collaboration (NIHR204295). The funders had no role in the study design; in the collection, analysis, or interpretation of data; in the writing of the report; or in the decision to submit the article for publication. PLHM has full access to all data and all authors have full access to the statistical reports and tables in the study. PLHM takes responsibility for the integrity of the data and the accuracy of the data analysis.

Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: BG reports research grants from the National Institute for Health and Care Research (NIHR). DRM was awarded a Wellcome Trust Clinical Research Development Fellowship (214588/Z/18/Z). AS reports a research grant from the NIHR. RAE reports research grants from the NIHR and NHS England, and travel costs to attend a roundtable dinner discussion on medication errors, House of Commons, Westminster, on 29 March 2022. TvS reports research grants from the NIHR. AJA is national clinical director for prescribing for NHS England and reports research grants from the NIHR. DMA reports research grants from the NIHR, AbbVie, Almirall, Celgene, Eli Lilly, Janssen, Novartis, UCB, and the Leo Foundation. All other authors declare no support from any organisation for the submitted work (except those listed in the funding section); no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.

Transparency: The lead author (PLHM: the manuscript’s guarantor) affirms that the manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.

Dissemination to participants and related patient and public communities: This study used anonymised electronic health records from the CPRD and it is therefore not possible to disseminate the findings directly to individuals whose data we used. This study is part of a National Institute for Health and Care Research (NIHR) funded programme (RP-PG-1214-20012): Avoiding patient harm through the application of prescribing safety indicators in English general practices (PRoTeCT). We have experienced patient and public involvement members aligned to the programme who we will consult in the results dissemination. In addition, senior author DMA is director of NIHR Greater Manchester Patient Safety Research Collaboration (GMPSRC), and co-authors MJC and AJA are affiliated with it. The Patient Safety Research Collaboration has a community of public contributors including patients, carers, and people accessing health and social care services. The authors will work with this network to disseminate findings.

Provenance and peer review: Not commissioned; externally peer reviewed.

This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/ .

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• Introduction
• Article Information

The date filter allows for daily selection of dates from March 1, 2020, to July 1, 2022. A slider is included under the date selection box for viewing policy progression throughout the pandemic. The health care settings filter consists of 4 checkboxes, allowing for the selection of target health care settings (general health care settings, nursing homes, home health care agencies, and both). Comprehensive definitions are found in the eTable in Supplement 1. The COVID-19 burden parameter consists of 5 checkboxes, allowing for the selection of 5 distinct categories of COVID-19 burden (cases and deaths) at the community and nursing home levels. The policy type filter allows for the selection of 5 broad policy categories. The policy subtype filter contains 38 distinct subcategories related to the broader categories. On the map, the number of policies is indicated by a color gradient, ranging from the least (light gray) to the most (dark blue). COVID-19 burden is depicted as circles of varying size, with larger diameters signifying increasing severity. Circles are red if there were deaths recorded during that period, green if there were no deaths, and gray if no data were available. The central US map can be enlarged for ease of viewing, while the 5 US territories remain fixed in size.

Maps depict May 24, 2020 (during first wave and after mandatory case and death reporting in nursing homes begins), January 12, 2021 (Alpha and Delta variants), and January 16, 2022 (Omicron variant). On the maps, the number of COVID-19 policies is indicated by a color gradient, ranging from the least (light gray color) to the most (darker blue color). All targeted health care settings (general, nursing homes, home health agencies, and both) were selected for this visual. COVID-19 burden is depicted as circles of varying size, with larger circles signifying increasing severity. The 7-day average of COVID-19 community deaths per 100 000 population was selected for this visual. Circles are red if there were deaths recorded during that period and green if there were no deaths.

eMethods. Policy Dataset and Dashboard Development

eTable. Definitions of Post–Acute Care COVID-19 Policy Categories and Subcategories

eReferences

Data Sharing Statement

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Stone PW , Zhao S , Chastain AM, et al. State- and Territory-Level Nursing Home and Home Health Care COVID-19 Policies and Disease Burden. JAMA Netw Open. 2024;7(4):e247683. doi:10.1001/jamanetworkopen.2024.7683

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State- and Territory-Level Nursing Home and Home Health Care COVID-19 Policies and Disease Burden

• 1 Center for Health Policy, Columbia University School of Nursing, New York, New York
• 2 Department of Anesthesiology and Perioperative Medicine, University of Rochester School of Medicine, Rochester, New York
• 3 Department of Public Health Sciences, University of Rochester School of Medicine, Rochester, New York
• 4 RAND Health, RAND Corporation, Boston, Massachusetts

The COVID-19 pandemic disproportionately affected older persons, 1 many of whom were served by home health care agencies (HHAs) and nursing homes (NHs). The extent to which state- and territory-level COVID-19 policies reinforced or expanded federal policies is unknown. Building on the work of others, 2 we created a dataset and dashboard of state- and territory-specific NH and HHA policies linked with community and NH COVID-19 burden for researchers and public health officials to evaluate policy efficacy.

In this cross-sectional study, we used the Council of State Government’s 2020-2021 State Executive Orders website 3 and comprehensive searches of state and territory government websites to identify state- and territory-specific policies enacted from March 1, 2020, to July 1, 2022. We collected start and end dates and categorized policies as general or specific to NHs, HHAs, or both. Policies were grouped into 5 categories with 38 subcategories as (1) preventing virus transmission (n = 18), (2) expanding NH and/or HHA capacity (n = 5), (3) relaxing administrative requirements (n = 5), (4) reporting COVID-19 data (n = 3), and (5) admission and discharge policies (n = 7) (eMethods in Supplement 1 ).

We linked these policy data with community-level 4 and NH-specific COVID-19 burden (case and mortality counts) 5 and entered data into Tableau Desktop, version 2023.2. 6 We used a color gradient and circle size to visualize policy counts and COVID-19 burden, respectively. The interactive dashboard displays temporality with zoom capability of setting, policy, and COVID-19 burden.

This study was approved by the Columbia University Institutional Review Board, who waived the need for informed consent because the study was not deemed human participant research. We followed the STROBE reporting guideline.

We identified 1400 policies across 50 states and 5 territories. Most included all health care settings (n = 846), followed by NH-specific (n = 486), NH- and HHA-specific (n = 43), and HHA-specific (n = 25) policies. The most common policy category was preventing virus transmission (n = 736), followed by expanding NH and HHA capacity (n = 325), relaxing administrative requirements (n = 184), reporting COVID-19 data (n = 79), and admission and discharge (n = 54). The dashboard ( Figure 1 ) illustrates variation in the number of policies per state and severity of COVID-19 burden indicated by color gradient and circle diameter, respectively. Figure 2 highlights the dynamic change in NH and HHA policies and COVID-19 burden. For example, on May 24, 2020, Montana, Hawaii, and Alaska had no COVID-19 deaths or policies, in contrast with North Carolina’s moderate burden and several policies. By January 12, 2021, New York had a severe COVID-19 burden and the greatest number of policies, while Pennsylvania, Montana, and Florida had a similar COVID-19 burden but fewer policies.

The dataset and dashboard described in this study are potentially important tools for researchers and public health officials and could provide a template for visual platforms that may inform future efforts to manage public health crises. Variations in COVID-19 burden and state and territory policy responses displayed in the dashboard highlight the complexity of pandemic management. Exploratory analyses demonstrated that higher numbers of policies at the state and territory levels were not consistently associated with reductions in community- or NH-level COVID-19 burden, suggesting policy effectiveness may depend on implementation and compliance. We also found limited attention to HHAs compared with NHs, despite both settings serving vulnerable older populations. This suggests a gap in public health planning, raising questions about resource allocation and prioritization among health care settings during pandemics.

Study limitations include the primarily descriptive data, underlying data from various sources, and limited evaluation of efficacy of public health policies on population COVID-19 outcomes. Future public health planning and pandemic responses should include adaptive and targeted policy interventions and should consider specific needs of all health care settings. Dashboards have the potential to help formulate data-driven decision-making during public health crises.

Accepted for Publication: February 17, 2024.

Published: April 22, 2024. doi:10.1001/jamanetworkopen.2024.7683

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2024 Stone PW et al. JAMA Network Open .

Corresponding Author: Patricia W. Stone, PhD, RN, Center for Health Policy, Columbia University School of Nursing, 560 W 168th St, New York, NY 10032 ( [email protected] ).

Author Contributions: Dr Stone had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Stone, Shang, Glance, Dick.

Acquisition, analysis, or interpretation of data: Stone, Zhao, Chastain, Perera, Shang, Dick.

Drafting of the manuscript: Stone, Zhao, Chastain, Perera, Shang, Glance.

Critical review of the manuscript for important intellectual content: Stone, Shang, Glance, Dick.

Statistical analysis: Zhao, Shang, Glance, Dick.

Obtained funding: Stone, Shang, Dick.

Administrative, technical, or material support: Stone, Chastain, Perera.

Supervision: Stone, Chastain, Perera, Shang, Dick.

Conflict of Interest Disclosures: Dr Stone reported receiving grant funding from the National Institutes of Health outside the submitted work. Ms Zhao reported participating in an internship through EmblemHealth outside the submitted work. Dr Chastain reported receiving grant funding from the National Institutes of Health outside the submitted work. Dr Perera reported receiving grant funding from the National Institutes of Health outside the submitted work. Dr Shang reported receiving grant funding from the National Institutes of Health outside the submitted work. Dr Glance reported receiving grant funding from the National Institutes of Health outside the submitted work. Dr Dick reported receiving grant funding from the National Institutes of Health outside the submitted work. No other disclosures were reported.

Funding/Support: This work was funded by grant R01NR016865 from the National Institute of Nursing Research and by grant R01AG074492 from the National Institute on Aging, the National Institute of Minority Health and Health Disparities, and the National Institute of Allergy and Infectious Diseases.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 2 .

Additional Contributions: Albert Chavesta, MS, MPH, assisted in compiling and categorizing the state- and territory-level policies, as well as drafting the policy dataset development methodology. Tenzin Trinley, MPH, Jung A. Kang, MSN, RN, and Charity Ogunlusi, MD, MPH, assisted with compiling state-level policies. All those acknowledged were affiliated with the Columbia University School of Nursing during the conduct of the study and were compensated via the study funding.

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Antipsychotics May Do Great Harm to People With Dementia: Report

By Dennis Thompson HealthDay Reporter

THURSDAY, April 18, 2024 (HealthDay News) -- Antipsychotics can substantially increase dementia patients’ risk of many serious health problems, a new study warns.

Dementia patients prescribed antipsychotics have increased risk of stroke, blood clots, heart attack, heart failure, bone fractures , pneumonia and kidney damage, researchers reported April 17 in the BMJ .

“A move away from the overprescription of antipsychotics is overdue,” concluded the research team led by Pearl Mok , a research fellow with the University of Manchester in England.

The study adds impetus to an ongoing investigation by the U.S. Centers for Medicare and Medicaid Services into the overuse of antipsychotic drugs in nursing homes.

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The investigation, announced last year, was launched in response to reports that some nursing homes might be falsely labeling patients as schizophrenic so they can be given antipsychotic drugs.

For the new study, researchers analyzed data on nearly 174,000 people in England diagnosed with dementia between January 1988 and May 2018, at an average age of 82.

More than 35,500 of those dementia patients had been prescribed an antipsychotic, and their health profiles were compared against up to 15 randomly selected patients who hadn’t used an antipsychotic.

Antipsychotic use more than doubled the risk of pneumonia among dementia patients, researchers found.

About 4.5% of dementia patients on antipsychotic drugs wound up developing pneumonia within three months of starting the meds, versus 1.5%  of non-users.

The drugs were also associated with a 72% increased risk of kidney injury, a 62% increased risk of blood clots, a 61% increased risk of stroke, a 43% increased risk of bone fractures, a 28% increased risk of heart attack and a 27% increased risk of heart failure.

For all these outcomes, risks were highest during the first week on antipsychotics, particularly for pneumonia, researchers said.

The most commonly prescribed antipsychotics were risperidone , quetiapine , haloperidol , and olanzapine , researchers said. Together, these accounted for almost 80% of all prescriptions.

International guidelines advise restricting antipsychotic use to dementia patients with severe behavioral and psychological symptoms, the researchers noted.

However, the rate of antipsychotic prescriptions has risen in recent years, partly due to a scarcity of effective non-drug alternatives, as well as the substantial resources required to implement the alternatives that do exist, researchers said.

Antipsychotics can cause side effects like drowsiness, confusion, shaking and unsteadiness, the Alzheimer’s Society says. People taking them also have a higher risk of swollen lower limbs, infections and blood clots.

More information

The Alzheimer’s Society has more on antipsychotics and dementia .

SOURCE: BMJ , news release, April 17, 2024

Copyright © 2024 HealthDay . All rights reserved.

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NCBI Bookshelf. A service of the National Library of Medicine, National Institutes of Health.

StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

StatPearls [Internet].

Alzheimer disease (nursing).

Anil Kumar ; Jaskirat Sidhu ; Amandeep Goyal ; Jack W. Tsao ; Chaddie Doerr .

Affiliations

Last Update: June 5, 2022 .

• Learning Outcome
• Describe the symptoms of AD
• Recall the management of a patient with AD
• Describe the cognitive issues in AD
• Summarize the role of nurses in managing AD
• Introduction

Dementia is a general term that refers to a decline in cognitive ability severe enough to interfere with activities of daily living. Alzheimer disease (AD) is the most common type of dementia, accounting for at least two-thirds of cases of dementia in people age 65 and older. Alzheimer disease is a neurodegenerative disease that causes progressive and disabling impairment of cognitive functions including memory, comprehension, language, attention, reasoning, and judgment. It is the sixth leading cause of death in the United States. Alzheimer disease is typically a disease of old age. Onset before 65 years of age (early onset) is unusual and seen in less than 10% of Alzheimer disease patients. The most common presenting symptom is selective short-term memory loss. The disease is invariably progressive, eventually leading to severe cognitive decline. There is no cure for Alzheimer disease, although there are treatments available that may improve some symptoms.

Symptoms of Alzheimer disease depend on the stage of the disease. Alzheimer disease is classified into preclinical, mild, moderate, and late-stage depending on the degree of cognitive impairment. The initial presenting symptom is usually recent memory loss with relative sparing of long-term memory and can be elicited in most patients even when not the presenting symptom. Short-term memory impairment is followed by impairment in problem-solving, judgment, executive functioning, lack of motivation and disorganization, leading to problems with multitasking and abstract thinking. In the early stages, impairment in executive functioning may be subtle. This is followed by language disorder and impairment of visuospatial skills. Neuropsychiatric symptoms like apathy, social withdrawal, disinhibition, agitation, psychosis, and wandering are also common in mid to late stages. Difficulty performing learned motor tasks (dyspraxia), olfactory dysfunction, sleep disturbances, extrapyramidal motor signs like dystonia, akathisia, and parkinsonian symptoms occur late in the disease. This is followed by primitive reflexes, incontinence, and total dependence on caregivers. [1] , [2] , [3]

• Nursing Diagnosis
• Decline in memory
• Altered behavior
• Poor memory
• Unable to perform daily living activities
• Loss of bladder and bowel control
• Personality change

Alzheimer disease is a gradual and progressive neurodegenerative disease caused by neuronal cell death. It typically starts in the entorhinal cortex in the hippocampus. There is a genetic role identified for both early and late-onset Alzheimer disease. Several risk factors have been associated with Alzheimer disease. Increasing age is the most important risk factor for Alzheimer disease. Traumatic head injury, depression, cardiovascular and cerebrovascular disease, higher parental age, smoking, family history of dementia, and presence of APOE e4 allele are known to increase the risk of Alzheimer disease. Higher education, use of estrogen by women, use of anti-inflammatory agents, and regular aerobic exercise is known to decrease the risk of Alzheimer disease. Having a first-degree relative with Alzheimer disease increases the risk of developing Alzheimer disease by 10% to 30%. Individuals with 2 or more siblings with late-onset Alzheimer disease increases their risk of getting Alzheimer disease by 3-fold as compared to the general population. [4] , [5] , [6]

• Risk Factors

Alzheimer disease is typically a disease of old age. The global prevalence of dementia is reported to be as high as 24 million and is predicted to increase 4 times by the year 2050. Estimated health care cost of Alzheimer disease is $172 billion per year in the United States alone. In 2011, the United States had an estimated 4.5 million people age sixty-five and above, living with clinical Alzheimer disease. The incidence of dementia is predicted to double every 10 years after 60 years of age. Age-specific incidence increases significantly from less than 1% per year before 65 years of age to 6% per year after 85 years of age. Incidence rates of Alzheimer disease are slightly higher for women, especially after 85 years of age.

A good history and physical examination are the keys to diagnosis. It is also essential to take a history from the family and caregivers as some patients may lack insight into their disease. It is vital to characterize onset and early symptoms to differentiate from other types of dementia. It is important to obtain a good assessment of functional abilities like basic and individual activities of daily living.

A complete physical examination with a detailed neurological exam and mental status examination is needed to evaluate disease stage and rule out other conditions. Comprehensive clinical assessment can provide reasonable diagnostic accuracy in most patients.  A detailed neurological examination is essential to rule out other conditions. In Alzheimer disease, the neurological exam is usually normal. A mental status examination should assess concentration, attention, recent and remote memory, language, visuospatial functioning, praxis, and executive functioning.

Brief standard examinations like the mini-mental status examination are less sensitive and specific, although they can be used for screening.

All follow-up visits should include a full mental status examination to evaluate disease progression and development of neuropsychiatric symptoms.

Routine laboratory tests show no specific abnormality. Complete blood count (CBC), complete metabolic panel (CMP), thyroid-stimulating hormone (TSH), B12 are usually checked to rule out other causes. [7] , [8] , [9]

Brain imaging may help in the diagnosis and monitor clinical course of the disease. MRI or CT brain can help exclude other causes of dementia like stroke or tumors. Dilated lateral ventricles and widened cortical sulci, especially in the temporal area are typical for Alzheimer disease.

Cerebrospinal fluid (CSF) is usually normal, but total protein may be mildly elevated. Measurements of total-tau, beta-amyloid, and phosphorylated tau protein are sometimes helpful for differential diagnosis. Alzheimer disease is strongly predicted if CSF has decreased beta-amyloid 42 and increased tau protein.

EEG typically shows a generalized slowing with no focal features.

Most reliable method to detect mild cognitive impairment in early disease is neuropsychological testing.

More recently, volumetric MRI is being used to precisely measure volumetric changes in the brain. In Alzheimer disease, volumetric MRI shows shrinkage in the medial temporal lobe. However, hippocampal atrophy is also linked to normal age-related memory decline, so the use of volumetric MRI for early detection of Alzheimer disease is questionable. A definite role for volumetric MRI to aid diagnosis of Alzheimer disease is not fully established yet.

Functional brain imaging techniques like PET, fMRI, and SPECT are being used to map patterns of dysfunction in smaller brain areas of the medial temporal lobe. These studies may be helpful in early detection and monitoring clinical course; however, their role in the diagnosis of Alzheimer disease is not fully established yet.

Most recently, there have been developments in brain imaging techniques to detect core histological features of Alzheimer disease, that is amyloid plaques and neurofibrillary tangles. The utility of these techniques is still being investigated.

Genetic testing is usually not recommended for Alzheimer disease. It may sometimes be used in families with rare early-onset forms of Alzheimer disease.

It is important to understand that diagnosing the type of dementia with all certainty may not be entirely possible despite excellent clinical history, physical examination and relevant testing. Some patients will complain of cognitive impairment that can be verified objectively, but is not severe enough to impair activities of daily life and thus does not meet criteria for dementia, and is usually just classified as mild cognitive impairment. However, a significant proportion of people with mild cognitive impairment will develop dementia of some type in 5 to 7 years.

• Medical Management

There is no cure for Alzheimer disease. Only symptomatic treatment is available. [10] [11] [12]

Two categories of drugs are approved for treatment of Alzheimer disease: cholinesterase inhibitors and partial N-methyl D-aspartate (NMDA) antagonists.

Cholinesterase Inhibitors

Cholinesterase inhibitors act by increasing the level of acetylcholine; a chemical used by nerve cells to communicate with each other and is important for learning, memory and cognitive functions. Of this category, 3 drugs: donepezil, rivastigmine, and galantamine are FDA-approved for treatment of Alzheimer disease.

Donepezil can be used in all stages of Alzheimer disease. Galantamine and rivastigmine are approved for treatment in mild to moderate Alzheimer disease only. Donepezil and galantamine are rapid, reversible inhibitors of acetylcholinesterase. Rivastigmine is a slow, reversible inhibitor of acetylcholinesterase and butyrylcholinesterase. Donepezil is usually preferred of all because of once-daily dosing. Galantamine is available as a twice daily tablet or as a once-daily extended-release capsule. It cannot be used in end-stage renal disease or severe liver dysfunction. Rivastigmine is available in an oral and transdermal formulation. Most common side effects of cholinesterase inhibitors are gastrointestinal-like nausea, vomiting, and diarrhea. Sleep disturbances are more common with donepezil. Due to increased vagal tone, bradycardia, cardiac conduction defects, and syncope can occur, and these medications are contraindicated in patients with severe cardiac conduction abnormalities.

Partial N-Methyl D-Aspartate (NMDA)  Memantine

Partial N-Methyl D-aspartate (NMDA) antagonist memantine blocks NMDA receptors and slows intracellular calcium accumulation. It is approved by FDA for treating moderate to severe Alzheimer disease. Dizziness, body aches, headache, and constipation are common side effects. It can be taken in combination with cholinesterase inhibitors. [13]

It is also important to treat anxiety, depression, and psychosis, which is often found in mid to late stages of Alzheimer disease.

Environmental and behavioral approaches are beneficial especially in managing behavioral problems. Simple approaches such as maintaining a familiar environment, monitoring personal comfort, providing security object, redirecting attention, and avoiding confrontation can be very helpful in managing behavioral issues.

The expected benefits of treatment are modest. Treatment should be stopped or modified if no significant benefits or if intolerable side effects.

Regular aerobic exercise has been shown to slow the progression of Alzheimer disease.

• Nursing Management
• Obtain thorough history and physical exam
• Assess neurological and psychiatric status
• Assess mood
• Check behavior, nutrition ability to dress
• Ensure adequate nutrition
• Ensure patient is oriented
• Provide structure and maintain schedule
• Assist with daily living activities
• Encourage interaction with others
• Monitor wandering
• Educate family or caregiver about disease progression and available resources
• Administer medications
• Minimize agitation
• When To Seek Help
• Not sleeping
• Very confused
• Going downhill
• Behavior worsening
• Outcome Identification
• Has a  decent quality of life
• Is not agitated
• Is oriented and responsive
• Listening to orders
• Neurological and mental health status
• Coordination of Care

Alzheimer disease (AD) is a progressive neurodegenerative disorder marked by behavior and cognitive impairment that eventually interfere with daily functional living activities. The disorder has no cure, and its rate of progression is variable. Further, the diagnosis of Alzheimer disease in the early phase is difficult, and there are no specific laboratory or imaging tests to confirm the diagnosis. The drugs available to treat the condition only work for the mild disease but also have numerous side effects which are not well tolerated. Alzheimer disease is a systemic disorder and creates havoc in the family. These individuals often wander, fall, have significant behavior problems and loss of memory. The majority of patients end up in an institution because they become unmanageable at home. Because of the nature of the disease, an interprofessional approach to the disorder has been recommended. Many guidelines and recommendations have been made on how to approach, monitor and treat Alzheimer patients. No one measure can prevent or arrest the disease. Given this, the following health care workers have a critical role in ensuring that the patient with Alzheimer disease remains safe and lead a decent quality of life.

Physical therapy for exercise. There is now ample evidence that exercise can help reduce the progression of the disease. [14] (Level III)

Nurses to educate the patient and family on medications, lifestyle changes, and performing daily living activities. To educate the partner on self-reporting on the worsening of symptoms.

Pharmacist to ensure that polypharmacy does not occur and that the patient is not developing adverse effects.

Alzheimer disease is initially associated only with impaired memory, but with time, the individual may develop severe cognitive and behavioral symptoms like depression, anxiety, anger, irritability, insomnia, and paranoia. As the disease progresses most of them will require assistance with daily living activities. Eventually, even walking become difficult and many may not be able to eat or develop swallowing difficulties that lead to aspiration pneumonia.

The time from diagnosis to death is variable; some individuals may die within five years, and others may remain alive for ten years, but overall the quality of life is very poor. While an interprofessional approach to management of Alzheimer patients is recommended, an analysis of several studies reveals that this approach has no impact on the care of his patients. However, because of the heterogeneity in the previous studies, more robust studies will be required to determine what type of approach works best for managing these patients. [15]

• Health Teaching and Health Promotion
• Educate caregiver and family about prognosis and support systems
• Provide the name and contact information for a social worker
• Discharge Planning

Educate the family and caregiver about the support systems

• Review Questions
• Access free multiple choice questions on this topic.
• Comment on this article.

Health Versus AD Brain. An illustration of a healthy brain (left) compared to the brain of an individual with Alzheimer Disease (right). Contributed by National Institutes of Health (NIH)

Disclosure: Anil Kumar declares no relevant financial relationships with ineligible companies.

Disclosure: Jaskirat Sidhu declares no relevant financial relationships with ineligible companies.

Disclosure: Amandeep Goyal declares no relevant financial relationships with ineligible companies.

Disclosure: Jack Tsao declares no relevant financial relationships with ineligible companies.

Disclosure: Chaddie Doerr declares no relevant financial relationships with ineligible companies.

This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits others to distribute the work, provided that the article is not altered or used commercially. You are not required to obtain permission to distribute this article, provided that you credit the author and journal.

• Cite this Page Kumar A, Sidhu J, Goyal A, et al. Alzheimer Disease (Nursing) [Updated 2022 Jun 5]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

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