Underdiagnosis of dementia in primary care: variations in the observed prevalence and comparisons to the expected prevalence

Persons living with dementia and caregivers' communication preferences for receiving a dementia diagnosis

Objective

As the number of individuals diagnosed with dementia increases, so does the need to understand the preferences of persons living with dementia (PLWD) and caregivers for how clinicians can deliver a dementia diagnosis effectively, which can be a difficult process. This study describes the diagnostic communication preferences of PLWD and caregivers.

Methods

We conducted semi-structured individual phone interviews with two groups: PLWD who were diagnosed in the past two years (n = 11) and family caregivers of PLWD (n = 19) living in Florida. PLWD and caregivers were not recruited/enrolled as dyads.

Results

The groups' communication preferences were largely similar. Data were analyzed thematically into five themes: communicate the diagnosis clearly, meet information needs, discuss PLWD/caregiver resources, prepare for continued care, and communicate to establish and maintain relationships.

Conclusion

Participants wanted clear communication, information, and support, but differed in some details (e.g. the language used to describe the diagnosis and the amount/type of desired information). Clinicians can apply general principles but will need to tailor them to individual preferences of PLWD and caregivers.

Innovation

Limited research has elicited PLWD and caregivers' communication preferences for receiving dementia diagnoses, particularly through an individualized data collection method allowing for richer descriptions and deeper understanding.

Derivation and validation of an algorithm to predict transitions from community to residential long-term care among persons with dementia-A retrospective cohort study

OBJECTIVES

To develop and validate a model to predict time-to-LTC admissions among individuals with dementia.

DESIGN

Population-based retrospective cohort study using health administrative data.

SETTING AND PARTICIPANTS

Community-dwelling older adults (65+) in Ontario living with dementia and assessed with the Resident Assessment Instrument for Home Care (RAI-HC) between April 1, 2010 and March 31, 2017.

METHODS

Individuals in the derivation cohort (n = 95,813; assessed before March 31, 2015) were followed for up to 360 days after the index RAI-HC assessment for admission into LTC. We used a multivariable Fine Gray sub-distribution hazard model to predict the cumulative incidence of LTC entry while accounting for all-cause mortality as a competing risk. The model was validated in 34,038 older adults with dementia with an index RAI-HC assessment between April 1, 2015 and March 31, 2017.

RESULTS

Within one year of a RAI-HC assessment, 35,513 (37.1%) individuals in the derivation cohort and 10,735 (31.5%) in the validation cohort entered LTC. Our algorithm was well-calibrated (Emax = 0.119, ICIavg = 0.057) and achieved a c-statistic of 0.707 (95% confidence interval: 0.703-0.712) in the validation cohort.

CONCLUSIONS AND IMPLICATIONS

We developed an algorithm to predict time to LTC entry among individuals living with dementia. This tool can inform care planning for individuals with dementia and their family caregivers.

Association of Regular Opioid Use With Incident Dementia and Neuroimaging Markers of Brain Health in Chronic Pain Patients: Analysis of UK Biobank

OBJECTIVES

We aimed to investigate the association of regular opioid use, compared with non-opioid analgesics, with incident dementia and neuroimaging outcomes among chronic pain patients.

DESIGN

The primary design is a prospective cohort study. To triangulate evidence, we also conducted a nested case-control study analyzing opioid prescriptions and a cross-sectional study analyzing neuroimaging outcomes.

SETTING AND PARTICIPANTS

Dementia-free UK Biobank participants with chronic pain and regular analgesic use.

MEASUREMENTS

Chronic pain status and regular analgesic use were captured using self-reported questionnaires and verbal interviews. Opioid prescription data were obtained from primary care records. Dementia cases were ascertained using primary care, hospital, and death registry records. Propensity score-matched Cox proportional hazards analysis, conditional logistic regression, and linear regression were applied to the data in the prospective cohort, nested case-control, and cross-sectional studies, respectively.

RESULTS

Prospective analyses revealed that regular opioid use, compared with non-opioid analgesics, was associated with an increased dementia risk over the 15-year follow-up (Hazard ratio [HR], 1.18 [95% confidence interval (CI): 1.08-1.30]; Absolute rate difference [ARD], 0.44 [95% CI: 0.19-0.71] per 1000 person-years; Wald χ2 = 3.65; df = 1; p <0.001). The nested case-control study suggested that a higher number of opioid prescriptions was associated with an increased risk of dementia (1 to 5 prescriptions: OR = 1.21, 95% CI: 1.07-1.37, Wald χ2 = 3.02, df = 1, p = 0.003; 6 to 20: OR = 1.27, 95% CI: 1.08-1.50, Wald χ2 = 2.93, df = 1, p = 0.003; more than 20: OR = 1.43, 95% CI: 1.23-1.67, Wald χ2 = 4.57, df = 1, p < 0.001). Finally, neuroimaging analyses revealed that regular opioid use was associated with lower total grey matter and hippocampal volumes, and higher white matter hyperintensities volumes.

CONCLUSION

Regular opioid use in chronic pain patients was associated with an increased risk of dementia and poorer brain health when compared to non-opioid analgesic use. These findings imply a need for re-evaluation of opioid prescription practices for chronic pain patients and, if further evidence supports causality, provide insights into strategies to mitigate the burden of dementia.

[DemStepCare: Risk-stratified support for primary care-based dementia care - evaluation from general practitioner's view]

OBJECTIVE

The innovation fund project DemStepCare aimed to optimize multi-professional care through case management, risk stratification, and crisis outpatient clinic. Here, the evaluation results from the perspective of the general practitioners are presented.

METHODS

A quantitative survey was carried out at three time points regarding acceptance, benefit assessment and sensitivity to dementia of the general practitioners. In addition, qualitative interviews were conducted.

RESULTS

Satisfaction with the overall project was high. Added value and relief factors were perceived and more effective and stable dementia care was achieved through collaboration with case management. Physicians reported increased subjective competence in diagnostics and disease management.

CONCLUSIONS

The results confirm the benefit and effectiveness of DemStepCare from general practitioner's perspective.

Longitudinal Management of Dementia in Primary Care

This Viewpoint describes the positive role that primary care teams can play in the lives of patients with dementia and the families that care for them.

Alerting providers to hospitalized persons with dementia using the electronic health record

BACKGROUND

While patients with dementia entering the hospital have worse outcomes than those without dementia, early detection of dementia in the inpatient setting is less than 50%. We developed and assessed the positive predictive value (PPV) and feasibility of a novel electronic health record (EHR) banner to identify patients with dementia who present to the inpatient setting using data from the medical record.

METHODS

We developed and implemented an EHR algorithm to flag hospitalized patients age ≥65 years with potential cognitive impairment in the Epic EHR system using dementia ICD-10 codes, FDA-approved medications, and the use of the term "dementia" in the emergency department physician note. Medical records were reviewed for all patients who were flagged with an EHR banner from October 2022 to May 2023.

RESULTS

A total of 344 individuals were identified who had a banner on their chart of which 280 (81.4%) were either diagnosed with dementia or were on an FDA-approved dementia medication. Forty-three individuals who had confirmed dementia were identified by a medication only (15.4%). Of the patients without confirmed dementia, the majority (N = 33, 9.6%) had a diagnosis of altered mental status, cognitive dysfunction, or mild cognitive impairment. Only 31 individuals (9.0%) had no indication of dementia or cognitive decline in their problem list, past medical history, or medication list.

CONCLUSIONS

We found that it was feasible to implement an EHR algorithm for prospective dementia identification with a high PPV. These types of algorithms provide an opportunity to accurately identify hospitalized older individuals for inclusion in quality improvement projects, clinical trials, pay-for-performance programs, and other initiatives.

Identifying longitudinal healthcare pathways and subsequent mortality for people living with dementia in England: an observational group-based trajectory analysis

BACKGROUND

The number of people living with dementia (PLWD) continues to increase, particularly those with severe symptomatology. Severe symptoms and greater ill-health result in more acute care need. Early healthcare interventions can prove beneficial. Healthcare use has not been analysed as a holistic set of interlinked events. This study explores different healthcare pathways among PLWD, social or spatial inequalities in healthcare pathways and subsequent mortality risk.

METHODS

Group-based trajectory models (GBTM) were applied to electronic healthcare records. We generated clusters of PLWD with similar five-year, post-diagnosis trajectories in rates of primary and secondary healthcare use. Potential social and spatial variations in healthcare use clusters were examined. Cox Proportional Hazards used to explore variation in subsequent mortality risk between healthcare use clusters.

RESULTS

Four healthcare use clusters were identified in both early- (n = 3732) and late-onset (n = 6224) dementia populations. Healthcare use variations were noted; consistent or diminishing healthcare use was associated with lower subsequent mortality risk. Increasing healthcare use was associated with increased mortality risk. Descriptive analyses indicated social and spatial variation in healthcare use cluster membership.

CONCLUSION

Healthcare pathways can help indicate changing need and variation in need, with differential patterns in initial healthcare use post-diagnosis, producing similar subsequent mortality risk. Care in dementia needs to be more accessible and appropriate, with care catered to specific and changing needs. Better continuity of care and greater awareness of dementia in primary can enhance prospects for PLWD. Research needs to further illuminate holistic care need for PLWD, including health and social care use, inequalities in care, health and outcomes.

Alzheimer's disease detection using data fusion with a deep supervised encoder

Alzheimer's disease (AD) is affecting a growing number of individuals. As a result, there is a pressing need for accurate and early diagnosis methods. This study aims to achieve this goal by developing an optimal data analysis strategy to enhance computational diagnosis. Although various modalities of AD diagnostic data are collected, past research on computational methods of AD diagnosis has mainly focused on using single-modal inputs. We hypothesize that integrating, or "fusing," various data modalities as inputs to prediction models could enhance diagnostic accuracy by offering a more comprehensive view of an individual's health profile. However, a potential challenge arises as this fusion of multiple modalities may result in significantly higher dimensional data. We hypothesize that employing suitable dimensionality reduction methods across heterogeneous modalities would not only help diagnosis models extract latent information but also enhance accuracy. Therefore, it is imperative to identify optimal strategies for both data fusion and dimensionality reduction. In this paper, we have conducted a comprehensive comparison of over 80 statistical machine learning methods, considering various classifiers, dimensionality reduction techniques, and data fusion strategies to assess our hypotheses. Specifically, we have explored three primary strategies: (1) Simple data fusion, which involves straightforward concatenation (fusion) of datasets before inputting them into a classifier; (2) Early data fusion, in which datasets are concatenated first, and then a dimensionality reduction technique is applied before feeding the resulting data into a classifier; and (3) Intermediate data fusion, in which dimensionality reduction methods are applied individually to each dataset before concatenating them to construct a classifier. For dimensionality reduction, we have explored several commonly-used techniques such as principal component analysis (PCA), autoencoder (AE), and LASSO. Additionally, we have implemented a new dimensionality-reduction method called the supervised encoder (SE), which involves slight modifications to standard deep neural networks. Our results show that SE substantially improves prediction accuracy compared to PCA, AE, and LASSO, especially in combination with intermediate fusion for multiclass diagnosis prediction.

Validation of a web-based self-administered test for cognitive assessment in a Swedish geriatric setting

Computerized cognitive tests have the potential to cost-effectively detect and monitor cognitive impairments and thereby facilitate treatment for these conditions. However, relatively few of these tests have been validated in a variety of populations. Brain on Track, a self-administered web-based test, has previously been shown to have a good ability to differentiate between healthy individuals and patients with cognitive impairment in Portuguese populations. The objective of this study was to validate the differential ability and evaluate the usability of Brain on Track in a Swedish memory clinic setting. Brain on Track was administered to 30 patients with mild cognitive impairment/mild dementia and 30 healthy controls, all scheduled to perform the test from home after one week and after three months. To evaluate the usability, the patient group was interviewed after completion of the testing phase. Patients scored lower than healthy controls at both the first (median score 42.4 vs 54.1, p<0.001) and the second test (median score 42.3 vs 55.0, p<0.001). The test-retest intra-class correlation was 0.87. A multiple logistic regression model accounting for effects of age, gender and education rendered an ability of Brain on Track to differentiate between the groups with an area under the receiver operation characteristics curve of 0.90 for the first and 0.88 for the second test. In the subjective evaluation, nine patients left positive comments, nine were negative whereas five left mixed comments regarding the test experience. Sixty percent of patients had received help from relatives to log on to the platform. In conclusion, Brain on Track performed well in differentiating healthy controls from patients with cognitive impairment and showed a high test-retest reliability, on par with results from previous studies. However, the substantial proportion of patients needing help to log in could to some extent limit an independent use of the platform.

[Palliative Care Needs in Primary Health Care: Characteristics of Patients with Advanced Cancer and Dementia]

INTRODUCTION

The increase in life expectancy brought a higher prevalence of chronic diseases, with an emphasis on those who reached advanced stages and required palliative care. We aimed to characterize patients diagnosed with advanced neoplasms and/or dementia accompanied in primary health care and to test the sensitivity of two tools for identifying patients with palliative needs.

METHODS

We recruited three voluntary family physicians who provided data relative to 623 patients with active codification for neoplasm and/or dementia on the MIM@UF platform. We defined 'patient with palliative needs' as any patient with this codification in advanced stadium and made their clinical and sociodemographic characterization. Assuming the existence of advanced-stage disease as the gold standard, we calculated and compared the sensitivities of each of the tools under study: the surprise question, the question 'do you think this patient has palliative needs?' and an instrument that corresponded to identification by at least one of the questions.

RESULTS

Among the analyzed data, there were 559 (89.7%) active codifications of neoplasm and 64 (10.3%) of dementia; the prevalence of advanced neoplasm and dementia was 1.0% in the studied sample. The subgroup of patients with advanced dementia showed female sex predominance, an older age, and less access to health care. In both subgroups there was a scarcity of data related to education and income, and we observed polypharmacotherapy and multimorbidity. The sensitivity of the surprise question was 33.3% for neoplasia and 69.3% for dementia; of the new tool 50.0% for neoplasia and 92.3% for dementia; and, when used together, 55.6% for neoplasia and 92.3% for dementia.

CONCLUSION

Our results help characterize two subpopulations of patients in need of palliative care and advance with a possible tool for their identification, to be confirmed in a representative sample.

Mapping Cognitive Trajectories and Detecting Early Dementia Using the Mini-Mental State Examination Cognitive Charts: Application to the French Three-City Cohort

The Cognitive Quotient (QuoCo) classification algorithm monitoring decline on age- and education-adjusted Mini-Mental State Examination (MMSE)-derived cognitive charts has proved superior to the conventionally-used cut-off for identifying incident dementia; however, it remains to be tested in different settings. Data were drawn from the Three-City Cohort to 1) assess the screening accuracy of the QuoCo, and 2) compare its performance to that of serial MMSE tests applying different cut-offs. For the QuoCo, sensitivity was 74.2 (95% CI: 71.4-76.8) and specificity 84.1 (83.6-84.7) and for the MMSE < 24, 64.1 (61.1-67.0) and 94.8 (94.4-95.1), respectively; whereas overall accuracy and sensitivity was highest for MMSE cut-offs <25 and <26. User-friendly charts for mapping cognitive trajectories over visits with an alert for potentially 'abnormal' decline can be of practical use and encourage regular monitoring in primary care where the <24 cut-off is still widely used despite its poor sensitivity.

The electronic health record Risk of Alzheimer's and Dementia Assessment Rule (eRADAR) Brain Health Trial: Protocol for an embedded, pragmatic clinical trial of a low-cost dementia detection algorithm

BACKGROUND

About half of people living with dementia have not received a diagnosis, delaying access to treatment, education, and support. We previously developed a tool, eRADAR, which uses information in the electronic health record (EHR) to identify patients who may have undiagnosed dementia. This paper provides the protocol for an embedded, pragmatic clinical trial (ePCT) implementing eRADAR in two healthcare systems to determine whether an intervention using eRADAR increases dementia diagnosis rates and to examine the benefits and harms experienced by patients and other stakeholders.

METHODS

We will conduct an ePCT within an integrated healthcare system and replicate it in an urban academic medical center. At primary care clinics serving about 27,000 patients age 65 and above, we will randomize primary care providers (PCPs) to have their patients with high eRADAR scores receive targeted outreach (intervention) or usual care. Intervention patients will be offered a "brain health" assessment visit with a clinical research interventionist mirroring existing roles within the healthcare systems. The interventionist will make follow-up recommendations to PCPs and offer support to newly-diagnosed patients. Patients with high eRADAR scores in both study arms will be followed to identify new diagnoses of dementia in the EHR (primary outcome). Secondary outcomes include healthcare utilization from the EHR and patient, family member and clinician satisfaction assessed through surveys and interviews.

CONCLUSION

If this pragmatic trial is successful, the eRADAR tool and intervention could be adopted by other healthcare systems, potentially improving dementia detection, patient care and quality of life.

Blood-based biomarkers in Alzheimer's disease: Future directions for implementation

INTRODUCTION

Disease-modifying therapies (DMTs) for Alzheimer's disease (AD) will increase diagnostic demand. A non-invasive blood-based biomarker (BBBM) test for detection of amyloid-β pathology may reduce diagnostic barriers and facilitate DMT initiation.

OBJECTIVE

To explore heterogeneity in AD care pathways and potential role of BBBM tests.

METHODS

Survey of 213 healthcare professionals/payers in US/China/UK/Germany/Spain/France and two advisory boards (US/Europe).

RESULTS

Current diagnostic pathways are heterogeneous, meaning many AD patients are missed while low-risk patients undergo unnecessary procedures. Confirmatory amyloid testing (cerebrospinal fluid biomarkers/positron emission tomography) is utilized in few patients, resulting in diagnostic/treatment delays. A high negative-predictive-value test could streamline the diagnostic pathway by reducing unnecessary procedures in low-risk patients; supporting confirmatory testing where needed. Imminent approval of DMTs will increase need for fast and reliable AD diagnostic tests.

DISCUSSION

An easy-to-use, accurate, non-invasive BBBM test for amyloid pathology could guide diagnostic procedures or referral, streamlining early diagnosis and DMT initiation.

Highlights

This study explored AD care pathways and how BBBM may meet diagnostic demandsCurrent diagnostic pathways are heterogeneous, with country and setting variationsMany AD patients are missed, while low-risk patients undergo unnecessary proceduresAn easy-to-use, accurate, non-invasive BBBM test for amyloid pathology is neededThis test could streamline early diagnosis of amyloid pathology and DMT initiation.

Prediction of conversion to dementia disorders based on timed up and go dual-task test verbal and motor outcomes: a five-year prospective memory-clinic-based study

BACKGROUND

While assessment tools can increase the detection of cognitive impairment, there is currently insufficient evidence regarding clinical outcomes based on screening for cognitive impairment in older adults.

METHODS

The study purpose was to investigate whether Timed Up and Go dual-task test (TUGdt) results, based on TUG combined with two different verbal tasks (name different animals, TUGdt-NA, and recite months in reverse order, TUGdt-MB), predicted dementia incidence over a period of five years among patients (N = 186, mean = 70.7 years; 45.7% female) diagnosed with Subjective Cognitive Impairment (SCI) and Mild Cognitive Impairment (MCI) following assessment at two memory clinics. Associations between TUG parameters and dementia incidence were examined in Cox regression models.

RESULTS

During follow-up time (median (range) 3.7 (0.1-6.1) years) 98 participants converted to dementia. Novel findings indicated that the TUGdt parameter words/time, after adjustment for age, gender, and education, can be used for the prediction of conversion to dementia in participants with SCI or MCI over a period of five years. Among the TUG-related parameters investigated, words/time showed the best predictive capacity, while time scores of TUG and TUGdt as well as TUGdt cost did not produce significant predictive results. Results further showed that the step parameter step length during TUGdt predicts conversion to dementia before adjustment for age, gender, and education. Optimal TUGdt cutoffs for predicting dementia at 2- and 4-year follow-up based on words/time were calculated. The sensitivity of the TUGdt cutoffs was high at 2-year follow-up: TUGdt-NA words/time, 0.79; TUGdt-MB words/time, 0.71; reducing respectively to 0.64 and 0.65 at 4-year follow-up.

CONCLUSIONS

TUGdt words/time parameters have potential as cost-efficient tools for conversion-to-dementia risk assessment, useful for research and clinical purposes. These parameters may be able to bridge the gap of insufficient evidence for such clinical outcomes.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT05893524: https://www.

CLINICALTRIALS

gov/study/NCT05893524?id=NCT05893524&rank=1 .

Urgent needs of caregiving in ageing populations with Alzheimer's disease and other chronic conditions: Support our loved ones

The ageing process begins at birth. It is a life-long process, and its exact origins are still unknown. Several hypotheses attempt to describe the normal ageing process, including hormonal imbalance, formation of reactive oxygen species, DNA methylation & DNA damage accumulation, loss of proteostasis, epigenetic alterations, mitochondrial dysfunction, senescence, inflammation, and stem cell depletion. With increased lifespan in elderly individuals, the prevalence of age-related diseases including, cancer, diabetes, obesity, hypertension, Alzheimer's, Alzheimer's disease and related dementias, Parkinson's, and other mental illnesses are increased. These increased age-related illnesses, put tremendous pressure & burden on caregivers, family members, and friends who are living with patients with age-related diseases. As medical needs evolve, the caregiver is expected to experience an increase in duties and challenges, which may result in stress on themselves, and impact their own family life. In the current article, we assess the biological mechanisms of ageing and its effect on body systems, exploring lifestyle and ageing, with a specific focus on age-related disorders. We also discussed the history of caregiving and specific challenges faced by caregivers in the presence of multiple comorbidities. We also assessed innovative approaches to funding caregiving, and efforts to improve the medical system to better organize chronic care efforts, while improving the skill and efficiency of both informal and formal caregivers. We also discussed the role of caregiving in end-of-life care. Our critical analysis strongly suggests that there is an urgent need for caregiving in aged populations and support from local, state, and federal agencies.

Multimorbidity Pattern and Risk for Mortality Among Patients With Dementia: A Nationwide Cohort Study Using Latent Class Analysis

OBJECTIVE

Individuals with dementia are at a substantially elevated risk for mortality; however, few studies have examined multimorbidity patterns and determined the inter-relationship between these comorbidities in predicting mortality risk.

METHODS

This is a prospective cohort study. Data from 6,556 patients who were diagnosed with dementia between 1997 and 2012 using the Taiwan National Health Insurance Research Database were analyzed. Latent class analysis was performed using 16 common chronic conditions to identify mortality risk among potentially different latent classes. Logistic regression was performed to determine the adjusted association of the determined latent classes with the 5-year mortality rate.

RESULTS

With adjustment for age, a three-class model was identified, with 42.7% of participants classified as "low comorbidity class (cluster 1)", 44.2% as "cardiometabolic multimorbidity class (cluster 2)", and 13.1% as "FRINGED class (cluster 3, characterized by FRacture, Infection, NasoGastric feeding, and bleEDing over upper gastrointestinal tract)." The incidence of 5-year mortality was 17.6% in cluster 1, 26.7% in cluster 2, and 59.6% in cluster 3. Compared with cluster 1, the odds ratio for mortality was 9.828 (95% confidence interval [CI]=6.708-14.401; p<0.001) in cluster 2 and 1.582 (95% CI=1.281-1.953; p<0.001) in cluster 3.

CONCLUSION

Among patients with dementia, the risk for 5-year mortality was highest in the subpopulation characterized by fracture, urinary and pulmonary infection, upper gastrointestinal bleeding, and nasogastric intubation, rather than cancer or cardiometabolic comorbidities. These findings may improve decision-making and advance care planning for patients with dementia.

What requirements do primary care physicians have with regard to dementia diagnostics and dementia care? - a survey study among general practitioners in Germany 2022/2023

BACKGROUND

General practice offers good conditions to detect and provide care for dementia-related diseases. Nonetheless, the effectiveness of dementia care in general practice is repeatedly criticised. To date, few studies have attempted to form a comprehensive picture of the status quo of dementia care in general practice that focuses on GP perspectives of experience and action. The aim of this study was to identify potential strengths and weaknesses of GP-based dementia care, by means of combined consideration of relevant care and treatment dimensions (construct of 'dementia sensitivity').

METHODS

Through an online poll, a total of 4,511 GPs who are active as treatment providers in Baden-Württemberg, Hesse, Rhineland-Palatinate and Saarland were surveyed between September 2022 and January 2023. In addition to the descriptive analysis, a T-test with independent samples was used to identify significant differences between two groups (interval-scaled or metric variables). Pearson's chi-squared test (χ2) was used to analyze the percentage values. Two levels of significance were tested for (mean difference at p < 0.05 and p < 0.001). In the course of the analysis, there were particular differences with regard to the sociodemographic variables 'urban vs. rural doctors' and 'doctors with geriatric training vs. doctors with no geriatric training'. Therefore, a complete listing of these parameters is given in the tables. In addition, the factor analysis method was employed.

RESULTS

The respondents consider it important for GPs to provide care and support for dementia patients. The doctors express the desire to offer active support to patients and their family caregivers. At the same time, many GPs experience challenges and difficulties when it comes to practical diagnostic steps (in line with guidelines), the (early) identification of dementia and consistent disease management, including the anticipation of care and treatment needs. Moreover, it appears that a significant proportion of the sample has only limited confidence when it comes to review relevant help and support services. One consistent finding is that some doctors in urban practices who also have geriatric training show substantial increases in knowledge and information with regard to dementia care.

CONCLUSIONS

In the light of the findings, it seems particularly advisable to strengthen the geriatric competence of GPs. Moreover, it seems to be essential to ensure that they are better informed about cooperation and support structures in the area of dementia care and better integrated into these.

Twenty-year trajectories of cardio-metabolic factors among people with type 2 diabetes by dementia status in England: a retrospective cohort study

To assess 20-year retrospective trajectories of cardio-metabolic factors preceding dementia diagnosis among people with type 2 diabetes (T2D). We identified 227,145 people with T2D aged > 42 years between 1999 and 2018. Annual mean levels of eight routinely measured cardio-metabolic factors were extracted from the Clinical Practice Research Datalink. Multivariable multilevel piecewise and non-piecewise growth curve models assessed retrospective trajectories of cardio-metabolic factors by dementia status from up to 19 years preceding dementia diagnosis (dementia) or last contact with healthcare (no dementia). 23,546 patients developed dementia; mean (SD) follow-up was 10.0 (5.8) years. In the dementia group, mean systolic blood pressure increased 16-19 years before dementia diagnosis compared with patients without dementia, but declined more steeply from 16 years before diagnosis, while diastolic blood pressure generally declined at similar rates. Mean body mass index followed a steeper non-linear decline from 11 years before diagnosis in the dementia group. Mean blood lipid levels (total cholesterol, LDL, HDL) and glycaemic measures (fasting plasma glucose and HbA1c) were generally higher in the dementia group compared with those without dementia and followed similar patterns of change. However, absolute group differences were small. Differences in levels of cardio-metabolic factors were observed up to two decades prior to dementia diagnosis. Our findings suggest that a long follow-up is crucial to minimise reverse causation arising from changes in cardio-metabolic factors during preclinical dementia. Future investigations which address associations between cardiometabolic factors and dementia should account for potential non-linear relationships and consider the timeframe when measurements are taken.

Social and spatial inequalities in healthcare use among people living with dementia in England (2002-2016)

OBJECTIVES

Healthcare services for people living with dementia (PLWD) are stretched, and government promises of increased funding remain undelivered. With the UK dementia population to surpass 1 million by 2024, and dementia care costs predicted to almost treble by 2040, it is essential we understand differences in healthcare use among PLWD. This study aimed to explore social and spatial variations in healthcare use among people diagnosed with dementia (2002-2016).

METHODS

Data were derived from Electronic Health Records of Clinical Practice Research Datalink GP patients in England (n = 142,302). To standardise healthcare contacts, rates of healthcare contacts per year were calculated for three primary (GP observations and medications) and three secondary healthcare types [Accident & Emergency (A&E) attendances and, emergency and elective hospital admissions]. Fully-adjusted generalised linear regression models were used to identify healthcare use variation by social and spatial groups. Twelve models were generated, one for each healthcare type in early- and late-onset populations separately.

RESULTS

This study highlights numerous social and spatial variations in healthcare use among PLWD. Among PLWD, several groups tended to have healthcare service use more closely associated with negative outcomes, including a greater likelihood of A&E attendances and emergency and elective hospital admissions. These groups include: men, people from White ethnicity groups and people from more deprived and rural areas.

CONCLUSIONS

Systemic and social measures are needed to reduce variations in healthcare use inequalities in PWLD. These include greater healthcare continuity, health checks and medicines reviews, culturally appropriate services, better and more accessible treatment and improved infrastructure.

Sharing Health Care Wishes in Primary Care (SHARE) among older adults with possible cognitive impairment in primary care: Study protocol for a randomized controlled trial

OBJECTIVE

Little is known about effective strategies to improve advance care planning (ACP) for persons with cognitive impairment in primary care, the most common setting of care. We describe a randomized controlled trial to test the efficacy of a multicomponent communication intervention, "Sharing Healthcare Wishes in Primary Care" (SHARE).

PARTICIPANTS

Planned enrollment of 248 dyads of adults 80 years and older with possible cognitive impairment and their care partner, from primary care clinics at 2 Mid-Atlantic health systems.

METHODS

The treatment protocol encompasses an introductory letter from the clinic; access to a designated facilitator trained in ACP; person-family agenda-setting to align perspectives about the family's role; and print education. The control protocol encompasses minimally enhanced usual care, which includes print education and a blank advance directive. Randomization occurs at the individual dyad-level. Patient and care partner surveys are fielded at baseline, 6-, 12-, and 24- months. Fidelity of interventionist delivery of the protocol is measured through audio-recordings of ACP conversations and post-meeting reports, and by ongoing monitoring and support of interventionists.

OUTCOMES

The primary outcome is quality of end-of-life care communication at 6 months; secondary outcomes include ACP process measures. An exploratory aim examines end-of-life care quality and bereaved care partner experiences for patients who die by 24 months.

CONCLUSIONS

Caregiver burden, clinician barriers, and impaired decisional capacity amplify the difficulty and importance of ACP discussions in the context of cognitive impairment: this intervention will comprehensively examine communication processes for this special subpopulation in a key setting of primary care.

REGISTRATION

ClinicalTrials.gov: NCT04593472.

Can Patients with Dementia Be Identified in Primary Care Electronic Medical Records Using Natural Language Processing?

Dementia and mild cognitive impairment can be underrecognized in primary care practice and research. Free-text fields in electronic medical records (EMRs) are a rich source of information which might support increased detection and enable a better understanding of populations at risk of dementia. We used natural language processing (NLP) to identify dementia-related features in EMRs and compared the performance of supervised machine learning models to classify patients with dementia. We assembled a cohort of primary care patients aged 66 + years in Ontario, Canada, from EMR notes collected until December 2016: 526 with dementia and 44,148 without dementia. We identified dementia-related features by applying published lists, clinician input, and NLP with word embeddings to free-text progress and consult notes and organized features into thematic groups. Using machine learning models, we compared the performance of features to detect dementia, overall and during time periods relative to dementia case ascertainment in health administrative databases. Over 900 dementia-related features were identified and grouped into eight themes (including symptoms, social, function, cognition). Using notes from all time periods, LASSO had the best performance (F1 score: 77.2%, sensitivity: 71.5%, specificity: 99.8%). Model performance was poor when notes written before case ascertainment were included (F1 score: 14.4%, sensitivity: 8.3%, specificity 99.9%) but improved as later notes were added. While similar models may eventually improve recognition of cognitive issues and dementia in primary care EMRs, our findings suggest that further research is needed to identify which additional EMR components might be useful to promote early detection of dementia.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41666-023-00125-6.

A dual-task gait test detects mild cognitive impairment with a specificity of 91.2

Background

Mild cognitive impairment (MCI) is a valuable intervention window in the progress of senile dementia, but the question of how to easily and conveniently detect MCI in the community remains unanswered. Gait performance reflects cognitive function, but how to reliably detect MCI through gait testing is still being explored.

Objective

To develop a dual-task gait testing method that could reliably detect MCI in the community.

Methods

A cross-sectional diagnostic study was conducted in 111 older adults (mean age = 72.14 ± 6.90 years) from five communities in Wuhan, China. A novel dual-task gait testing method, walking while identifying animals in pictures (AniP-DT gait test), was developed. The participants were classified into MCI or cognitively intact based on their performance on the Montreal Cognitive Assessment Scale (MoCA). Gait performance was assessed using both single-task and the AniP-DT gait test. Multiple linear regression and binary logistic regression were used to model the association between gait speed and cognitive status, and receiver operating characteristic (ROC) curve analysis was used to assess the discrimination ability.

Results

Compared to the cognitively intact group, the gait speed of the MCI group was lower in both single-task and the AniP-DT gait tests. The gait speed of the AniP-DT gait test was significantly associated with MoCA scores after adjusting the covariates and exhibited good discrimination ability in MCI detection (AUC = 0.814), with a specificity of 91.2%. ROC analysis of the logistic models revealed better discrimination ability of dual-task gait velocity when adjusted with age and years of education (AUC = 0.862).

Conclusion

The evidence in this study suggested that the AniP-DT gait test could be an easy and reliable screening tool for MCI in community older adults.

Patient navigation programs for people with dementia, their caregivers, and members of the care team: a scoping review

OBJECTIVE

The main objective of this review was to map the literature on the characteristics of patient navigation programs for people with dementia, their caregivers, and members of the care team across all settings. The secondary objective was to map the literature on the barriers and facilitators for implementing and delivering such patient navigation programs.

INTRODUCTION

People with dementia have individualized needs that change according to the stage of their condition. They often face fragmented and uncoordinated care when seeking support to address these needs. Patient navigation may be one way to help people with dementia access better care. Patient navigation is a model of care that aims to guide people through the health care system, matching their unmet needs to appropriate resources, services, and programs. Organizing the available information on this topic will present a clearer picture of how patient navigation programs work.

INCLUSION CRITERIA

This review focused on the characteristics of patient navigation programs for people living with dementia, their caregivers, and the members of the care team. It excluded programs not explicitly focused on dementia. It included patient navigation across all settings, delivered in all formats, and administered by all types of navigators if the programs aligned with this review's definition of patient navigation. This review excluded case management programs.

METHODS

This review was conducted in accordance with JBI methodology for scoping reviews. MEDLINE, CINAHL, APA PsycINFO, Embase, and ProQuest Nursing and Allied Health databases were searched for published full-text articles. A gray literature search was also conducted. Two independent reviewers screened articles for relevance against the inclusion criteria. The results are presented in a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram, and the extracted data are presented narratively and in tabular format.

RESULTS

Thirty-nine articles describing 20 programs were included in this review. The majority of these articles were published between 2015 and 2020, and based out of the United States. The types of sources included randomized controlled trials, quasi-experimental studies, and qualitative exploratory studies, among others. All programs provided some form of referral or linkage to other services or resources. Most dementia navigation programs included an interdisciplinary team, and most programs were community-based. There was no consistent patient navigator title or standard delivery method. Commonly reported barriers to implementing and delivering these programs were navigator burnout and a lack of coordination between stakeholders. Commonly reported facilitators were collaboration, communication, and formal partnerships between key stakeholders, as well as accessible and flexible program delivery models.

CONCLUSIONS

This review demonstrates variety and flexibility in the types of services patient navigation programs provided, as well as in the modes of service delivery and in navigator title. This information may be useful for individuals and organizations looking to implement their own programs in the future. It also provides a framework for future systematic reviews that seek to evaluate the effectiveness or efficacy of dementia navigation programs.

Associations of an eye-tracking task and pupillary metrics with age and ASA physical status score in a preoperative cohort

Advanced age, American Society of Anesthesiologists physical status (ASA) classification and the presence of cognitive impairment are associated with an elevated risk of postoperative morbidity and mortality. The visual paired comparison (VPC) task, which relies on recognition of novel images, examines declarative memory. VPC scores have demonstrated the ability to detect mild cognitive impairment and track progression of neurodegenerative disease. Quantitative pupillometry may have similar value. We evaluate for associations between these variables of interest and the feasibility of performing these tests in the preoperative clinic. Prospective data from 199 patients seen in the preoperative clinic at a tertiary academic center were analyzed. A 5 min VPC task (Neurotrack Technologies, Inc, Redwood City, CA) was administered during their scheduled preoperative clinic visit. Pupillary light reflexes were measured at the same visit (PLR-3000™, Neuroptics Corp, Irvine, California).Thirty-four percent of patients were categorized as ASA 2 and 58% as ASA 3. Median age was 57 (IQR: 44-69). Associations were demonstrated between age and ASA physical status (Mann-Whitney U Test, p < 0.0001), maximum pupil size (Spearman Rank Correlation, r = - 0.40, p < 0.0001), and maximum constriction velocity (Spearman Rank Correlation, r = - 0.39, p < 0.0001). Our data also revealed an association between VPC score and age (Spearman Rank Correlation, p = 0.0016, r = - 0.21) but not ASA score (Kruskal-Wallis Test, p = 0.14). When compared to a nonsurgical cohort with no history of memory impairment, our population scored worse on the VPC task (Mann-Whitney U Test, p = 0.0002). A preoperative 5 min VPC task and pupillometry are feasible tests in the preoperative setting and may provide a valuable window into an individual's cognition prior to elective surgery.

Age-Related Perioperative Neurocognitive Disorders: Experimental Models and Druggable Targets

With the worldwide increase in life span, surgical patients are becoming older and have a greater propensity for postoperative cognitive impairment, either new onset or through deterioration of an existing condition; in both conditions, knowledge of the patient's preoperative cognitive function and postoperative cognitive trajectory is imperative. We describe the clinical utility of a tablet-based technique for rapid assessment of the memory and attentiveness domains required for executive function. The pathogenic mechanisms for perioperative neurocognitive disorders have been investigated in animal models in which excessive and/or prolonged postoperative neuroinflammation has emerged as a likely contender. The cellular and molecular species involved in postoperative neuroinflammation are the putative targets for future therapeutic interventions that are efficacious and do not interfere with the surgical patient's healing process.

Comparing risk prediction models aimed at predicting hospitalizations for adverse drug events in community dwelling older adults: a protocol paper

Background

The objective of this paper is to describe the creation, validation, and comparison of two risk prediction modeling approaches for community-dwelling older adults to identify individuals at highest risk for adverse drug event-related hospitalizations. One approach will use traditional statistical methods, the second will use a machine learning approach.

Methods

We will construct medication, clinical, health care utilization, and other variables known to be associated with adverse drug event-related hospitalizations. To create the cohort, we will include older adults (≥ 65 years of age) empaneled to a primary care physician within the Cedars-Sinai Health System primary care clinics with polypharmacy (≥ 5 medications) or at least 1 medication commonly implicated in ADEs (certain oral hypoglycemics, anti-coagulants, anti-platelets, and insulins). We will use a Fine-Gray Cox proportional hazards model for one risk modeling approach and DataRobot, a data science and analytics platform, to run and compare several widely used supervised machine learning algorithms, including Random Forest, Support Vector Machine, Extreme Gradient Boosting (XGBoost), Decision Tree, Naïve Bayes, and K-Nearest Neighbors. We will use a variety of metrics to compare model performance and to assess the risk of algorithmic bias.

Discussion

In conclusion, we hope to develop a pragmatic model that can be implemented in the primary care setting to risk stratify older adults to further optimize medication management.

Differences in structural MRI and diffusion tensor imaging underlie visuomotor performance declines in older adults with an increased risk for Alzheimer's disease

Introduction

Visuomotor impairments have been demonstrated in preclinical AD in individuals with a positive family history of dementia and APOE e4 carriers. Previous behavioral findings have also reported sex-differences in performance of visuomotor tasks involving a visual feedback reversal. The current study investigated the relationship between grey and white matter changes and non-standard visuomotor performance, as well as the effects of APOE status, family history of dementia, and sex on these brain-behavior relationships.

Methods

Older adults (n = 49) with no cognitive impairments completed non-standard visuomotor tasks involving a visual feedback reversal, plane-change, or combination of the two. Participants with a family history of dementia or who were APOE e4 carriers were considered at an increased risk for AD. T1-weighted anatomical scans were used to quantify grey matter volume and thickness, and diffusion tensor imaging measures were used to quantify white matter integrity.

Results

In APOE e4 carriers, grey and white matter structural measures were associated with visuomotor performance. Regression analyses showed that visuomotor deficits were predicted by lower grey matter thickness and volume in areas of the medial temporal lobe previously implicated in visuomotor control (entorhinal and parahippocampal cortices). This finding was replicated in the diffusion data, where regression analyses revealed that lower white matter integrity (lower FA, higher MD, higher RD, higher AxD) was a significant predictor of worse visuomotor performance in the forceps minor, forceps major, cingulum, inferior fronto-occipital fasciculus (IFOF), inferior longitudinal fasciculus (ILF), superior longitudinal fasciculus (SLF), and uncinate fasciculus (UF). Some of these tracts overlap with those important for visuomotor integration, namely the forceps minor, forceps major, SLF, IFOF, and ILF.

Conclusion

These findings suggest that measuring the dysfunction of brain networks underlying visuomotor control in early-stage AD may provide a novel behavioral target for dementia risk detection that is easily accessible, non-invasive, and cost-effective. The results also provide insight into the structural differences in inferior parietal lobule that may underlie previously reported sex-differences in performance of the visual feedback reversal task.

S. Identification of Alzheimer's Disease by Imaging: A Comprehensive Review

In developing countries, there is more concern for Alzheimer's disease (AD) by public health professionals due to its catastrophic effects on the elderly. Early detection of this disease helps in starting the therapy soon and slows down the progression of the disease. Imaging techniques are considered to be the best solutions for its detection. Brain imaging was initially used to diagnose AD. Different techniques for identifying protein accumulation in the nervous system, a sign of Alzheimer's disease, are identified by MRI imaging. Although they were initially attributed to cortical dysfunction, visual system impairments in Alzheimer's patients were also found in the early 1970s. Several non-invasive approaches reported for screening, prevention, and therapy were unsuccessful. It is vitally necessary to develop new diagnostic methods in order to accurately identify patients who are in the early stages of this disease. It would be wonderful to have a quick, non-invasive, affordable, and easily scalable Alzheimer's disease screening. Researchers may be able to identify biomarkers for Alzheimer's disease and understand more about its aetiology with imaging and data processing. This study clarifies the need for medical image processing and analysis strategies which aid in the non-invasive diagnosis of AD.

A novel approach for the detection of cognitive impairment and delirium risk in older patients undergoing spine surgery

BACKGROUND

Postoperative delirium is a common postsurgical complication in older patients and is associated with high morbidity and mortality. The objective of this study was to determine whether a digital cognitive assessment and patient characteristics could identify those at-risk.

METHODS

Patients 65 years and older undergoing spine surgeries ≥3 h were evaluated as part of a single-center prospective observational cohort study at an academic medical center, from January 1, 2019, to December 31, 2020. Of 220 eligible patients, 161 were enrolled and 152 completed the study. The primary outcome of postoperative delirium was measured by the Confusion Assessment Method for the Intensive Care Unit or the Nursing Delirium Screening Scale, administered by trained nursing staff independent from the study protocol. Baseline cognitive impairment was identified using the tablet-based TabCAT Brain Health Assessment.

RESULTS

Of the 152 patients included in this study, 46% were women. The mean [SD] age was 72 [5.4] years. Baseline cognitive impairment was identified in 38% of participants, and 26% had postoperative delirium. In multivariable analysis, impaired Brain Health Assessment Cognitive Score (OR 2.45; 95% CI, 1.05-5.67; p = 0.037), depression (OR 4.54; 95% CI, 1.73-11.89; p = 0.002), and higher surgical complexity Tier 4 (OR 5.88; 95% CI, 1.55-22.26; p = 0.009) were associated with postoperative delirium. The multivariate model was 72% accurate for predicting postoperative delirium, compared to 45% for the electronic medical record-based risk stratification model currently in use.

CONCLUSION

In this prospective cohort study of spine surgery patients, age, cognitive impairment, depression, and surgical complexity identified patients at high risk for postoperative delirium. Integration of scalable digital assessments into preoperative workflows could identify high-risk patients, automate decision support for timely interventions that can improve patient outcomes and lower hospital costs, and provide a baseline cognitive assessment to monitor for postoperative cognitive change.

Comparing Lookback Periods to Ascertain Alzheimer's Disease and Related Dementias

Claims data are a valuable resource for studying Alzheimer's disease and related dementias (ADRD). Alzheimer's disease and related dementias is often identified using a list of claims codes and a fixed lookback period of 3 years of data. However, a 1-year lookback or an approach using all-available lookback data could be beneficial based on different research questions. Thus, the purpose of this study was to compare 1-year and all-available lookback approaches to ascertaining ADRD compared to the standard 3-year approach. Using a cohort of Veterans hospitalized for heart failure (N = 373, 897), our results suggested high agreement (93% or greater) between the lookback periods. The 1-year lookback period had lower sensitivity (60%) and underestimated the prevalence of ADRD. These results suggest that 1-year and all-available lookback periods are viable approaches when using claims data.

Associations Between Use of Paid Help and Care Experiences Among Medicare-Medicaid Enrolled Older Adults With and Without Dementia

OBJECTIVES

Community-living older Medicare and Medicaid enrollees ("dual-enrollees") have high care needs and commonly receive paid and unpaid long-term services and supports (LTSS) to help with routine activities. Little is known about whether receiving paid help or individuals' state and neighborhood environmental context ("LTSS environment") relates to dual-enrollees' care experiences.

METHODS

We examine a sample of n = 979 community-dwelling dual-enrollees with disabilities from 2011 to 2015 National Health and Aging Trends Study, linked to measures of neighborhood disadvantage and state Medicaid home and community-based services (HCBS) generosity. Logistic regression models stratified by dementia status assess associations between paid help and: (a) adverse consequences due to unmet care needs, and (b) participation restrictions in valued activities, among dual-enrollees with and without dementia, adjusting for individual and LTSS environmental characteristics.

RESULTS

Use of paid help was greater for those with (versus without) dementia (46.9% vs. 37.8%). Neighborhood disadvantage was associated with greater use of paid help among dual-enrollees living with dementia. High state Medicaid HCBS generosity was associated with the use of paid help, regardless of dementia status. Dual-enrollees with dementia receiving paid help had higher odds of experiencing adverse consequences due to unmet need (adjusted odds ratio = 2.05; 95% confidence interval 1.16-3.61; p = .02)-no significant associations were observed for participation restrictions. Use of paid help and LTSS environment were not significantly associated with care experiences for dual-enrollees without dementia.

DISCUSSION

Findings highlight the complexities of caring for dual-enrollees, particularly those with dementia, and emphasize the need to strengthen the delivery of paid care with considerations for the LTSS environment.

A remote speech-based AI system to screen for early Alzheimer's disease via smartphones

Introduction

Artificial intelligence (AI) systems leveraging speech and language changes could support timely detection of Alzheimer's disease (AD).

Methods

The AMYPRED study (NCT04828122) recruited 133 subjects with an established amyloid beta (Aβ) biomarker (66 Aβ+, 67 Aβ-) and clinical status (71 cognitively unimpaired [CU], 62 mild cognitive impairment [MCI] or mild AD). Daily story recall tasks were administered via smartphones and analyzed with an AI system to predict MCI/mild AD and Aβ positivity.

Results

Eighty-six percent of participants (115/133) completed remote assessments. The AI system predicted MCI/mild AD (area under the curve [AUC] = 0.85, ±0.07) but not Aβ (AUC = 0.62 ±0.11) in the full sample, and predicted Aβ in clinical subsamples (MCI/mild AD: AUC = 0.78 ±0.14; CU: AUC = 0.74 ±0.13) on short story variants (immediate recall). Long stories and delayed retellings delivered broadly similar results.

Discussion

Speech-based testing offers simple and accessible screening for early-stage AD.

Effects of cognitive impairment and depressive symptoms on health-related quality of life in community-dwelling older adults: The mediating role of disability in the activities of daily living and the instrumental activities of daily living

The objective of this study was to estimate the joint effects of cognitive impairment and depressive symptoms on health-related quality of life (HRQoL) and to explore the mediating role of disability among Chinese community-dwelling older adults. A cross-sectional study was conducted with 2525 community-dwelling older adults aged ≥60 years and living in Shanghai, China in 2019. Participants were divided into four groups: (1) non-depressed without dementia, (2) non-depressed with probable MCI, (3) depressed without dementia and (4) depressed with probable mild cognitive impairment (MCI). HRQoL was assessed using the 36-Item Short-Form Health Survey. Cognitive impairment and depressive symptoms were evaluated with the AD8 and the Geriatric Depression Scale respectively. Activities of daily living (ADL) and instrumental activities of daily living (IADL) disability and other sociodemographic variables were also assessed. The results of this study showed that controlling for sociodemographic characteristics, significant differences in a physical component score (PCS) and a mental component score (MCS) of HRQoL were found across the four groups. Compared to those who were non-depressed without dementia, older adults who were depressed with probable MCI reported the lowest level of PCS and MCS, followed by older adults who were depressed without dementia. Both ADL and IADL disabilities played mediating roles in the relationship between cognitive impairment and depressive symptoms and PCS. Based on this study, we suggest that the early detection and adequate management of depressive symptoms and cognitive status-as well as efforts to improve individuals' ability to manage their ADLs and IADLs-may help to maintain or improve their HRQoL.

Leveraging speech and artificial intelligence to screen for early Alzheimer's disease and amyloid beta positivity

Early detection of Alzheimer's disease is required to identify patients suitable for disease-modifying medications and to improve access to non-pharmacological preventative interventions. Prior research shows detectable changes in speech in Alzheimer's dementia and its clinical precursors. The current study assesses whether a fully automated speech-based artificial intelligence system can detect cognitive impairment and amyloid beta positivity, which characterize early stages of Alzheimer's disease. Two hundred participants (age 54-85, mean 70.6; 114 female, 86 male) from sister studies in the UK (NCT04828122) and the USA (NCT04928976), completed the same assessments and were combined in the current analyses. Participants were recruited from prior clinical trials where amyloid beta status (97 amyloid positive, 103 amyloid negative, as established via PET or CSF test) and clinical diagnostic status was known (94 cognitively unimpaired, 106 with mild cognitive impairment or mild Alzheimer's disease). The automatic story recall task was administered during supervised in-person or telemedicine assessments, where participants were asked to recall stories immediately and after a brief delay. An artificial intelligence text-pair evaluation model produced vector-based outputs from the original story text and recorded and transcribed participant recalls, quantifying differences between them. Vector-based representations were fed into logistic regression models, trained with tournament leave-pair-out cross-validation analysis to predict amyloid beta status (primary endpoint), mild cognitive impairment and amyloid beta status in diagnostic subgroups (secondary endpoints). Predictions were assessed by the area under the receiver operating characteristic curve for the test result in comparison with reference standards (diagnostic and amyloid status). Simulation analysis evaluated two potential benefits of speech-based screening: (i) mild cognitive impairment screening in primary care compared with the Mini-Mental State Exam, and (ii) pre-screening prior to PET scanning when identifying an amyloid positive sample. Speech-based screening predicted amyloid beta positivity (area under the curve = 0.77) and mild cognitive impairment or mild Alzheimer's disease (area under the curve = 0.83) in the full sample, and predicted amyloid beta in subsamples (mild cognitive impairment or mild Alzheimer's disease: area under the curve = 0.82; cognitively unimpaired: area under the curve = 0.71). Simulation analyses indicated that in primary care, speech-based screening could modestly improve detection of mild cognitive impairment (+8.5%), while reducing false positives (-59.1%). Furthermore, speech-based amyloid pre-screening was estimated to reduce the number of PET scans required by 35.3% and 35.5% in individuals with mild cognitive impairment and cognitively unimpaired individuals, respectively. Speech-based assessment offers accessible and scalable screening for mild cognitive impairment and amyloid beta positivity.

The 5-Cog paradigm to improve detection of cognitive impairment and dementia: clinical trial protocol

Cognitive impairment related to dementia is under-diagnosed in primary care despite availability of numerous cognitive assessment tools; under-diagnosis is more prevalent for members of racial and ethnic minority groups. Clinical decision-support systems may improve rates of primary care providers responding to positive cognitive assessments with appropriate follow-up. The 5-Cog study is a randomized controlled trial in 1200 predominantly Black and Hispanic older adults from an urban underserved community who are presenting to primary care with cognitive concerns. The study will validate a novel 5-minute cognitive assessment coupled with an electronic medical record-embedded decision tree to overcome the barriers of current cognitive assessment paradigms in primary care and facilitate improved dementia care.

Evaluation of routinely collected records for dementia outcomes in UK: a prospective cohort study

OBJECTIVES

To evaluate the characteristics of individuals recorded as having a dementia diagnosis in different routinely collected records and to examine the extent of overlap of dementia coding across data sources. Also, to present comparisons of secondary and primary care records providing value for researchers using routinely collected records for dementia outcome capture.

STUDY DESIGN

A prospective cohort study.

SETTING AND PARTICIPANTS

A cohort of 25 639 men and women in Norfolk, aged 40-79 years at recruitment (1993-1997) followed until 2018 linked to routinely collected to identify dementia cases. Data sources include mortality from death certification and National Health Service (NHS) hospital or secondary care records. Primary care records for a subset of the cohort were also reviewed.

PRIMARY OUTCOME MEASURE

Diagnosis of dementia (any-cause).

RESULTS

Over 2000 participants (n=2635 individuals) were found to have a dementia diagnosis recorded in one or more of the data sources examined. Limited concordance was observed across the secondary care data sources. We also observed discrepancies with primary care records for the subset and report on potential linkage-related selection bias.

CONCLUSIONS

Use of different types of record linkage from varying parts of the UK's health system reveals differences in recorded dementia diagnosis, indicating that dementia can be identified to varying extents in different parts of the NHS system. However, there is considerable variation, and limited overlap in those identified. We present potential selection biases that might occur depending on whether cause of death, or primary and secondary care data sources are used. With the expansion of using routinely collected health data, researchers must be aware of these potential biases and inaccuracies, reporting carefully on the likely extent of limitations and challenges of the data sources they use.

Statin use is associated with lower risk of dementia in stroke patients: a community-based cohort study with inverse probability weighted marginal structural model analysis

Current evidence is inconclusive on cognitive benefits or harms of statins among stroke patients, who have high risk of dementia. This observational cohort study investigated the association between statin use and post-stroke dementia using data from the Clinical Practice Research Datalink. Patients without prior dementia who had an incident stroke but received no statins in the preceding year were followed for up to 10 years. We used inverse probability weighted marginal structural models to estimate observational analogues of intention-to-treat (ITT, statin initiation vs. no initiation) and per-protocol (PP, sustained statin use vs. no use) effects on the risk of dementia. To explore potential impact of unmeasured confounding, we examined the risks of coronary heart disease (CHD, positive control outcome), fracture and peptic ulcer (negative control outcomes). In 18,577 statin initiators and 14,613 non-initiators (mean follow-up of 4.2 years), the adjusted hazard ratio (aHR) for dementia was 0.70 (95% confidence interval [CI] 0.64–0.75) in ITT analysis and 0.55 (95% CI 0.50–0.62) in PP analysis. The corresponding aHR_ITT and aHR_PP were 0.87 (95% CI 0.79–0.95) and 0.70 (95% CI 0.62–0.80) for CHD, 1.03 (95% CI 0.82–1.29) and 1.09 (95% CI 0.77–1.54) for peptic ulcer, and 0.88 (95% CI 0.80–0.96) and 0.86 (95% CI 0.75–0.98) for fracture. Statin initiation after stroke was associated with lower risk of dementia, with a potentially greater benefit in patients who persisted with statins over time. The observed association of statin use with post-stroke dementia may in part be overestimated due to unmeasured confounding shared with the association between statin use and fracture.

Using Self-Administered Game-Based Cognitive Assessment to Screen for Degenerative Dementia: A Pilot Study

BACKGROUND

The earlier detection of dementia is needed as cases increase yearly in the aging populations of Taiwan and the world. In recent years, the global internet usage rate has gradually increased among older people. To expand dementia screening and provide timely medical intervention, a simple self-administrated assessment tool to assist in easily screening for dementia is needed.

OBJECTIVE

The two-part goal of this pilot study was, first, to develop a Game-Based Cognitive Assessment (GBCA) tool, and then, to evaluate its validity at early screening for patients with cognitive impairment.

METHOD

The researchers recruited 67 patients with neurocognitive disorders (NCDs) and 57 healthy controls (HCs). Each participant underwent the GBCA and other clinical cognitive assessments (CDR, CASI, and MMSE), and filled out a questionnaire evaluating their experience of using the GBCA. Statistical analyses were used to measure the validity of the GBCA at screening for degenerative dementia.

RESULTS

The average GBCA scores of the HC and NCD groups were 87 (SD = 7.9) and 52 (SD = 21.7), respectively. The GBCA correlated well with the CASI (r2 = 0.90, p <  0.001) and with the MMSE (r2 = 0.92, p <  0.001), indicating concurrent validity. The GBCA cut-off of 75/76 corresponded to measurements of sensitivity, specificity, and area under curve of 85.1%, 91.5%, and 0.978, respectively. The positive predictive value was 91.9%, and the negative predictive value was 84.4%. The results of the user-experience questionnaire for the HC and NCD groups were good and acceptable, respectively.

CONCLUSION

The GBCA is an effective and acceptable tool for screening for degenerative dementia.

Estimation of the global prevalence of dementia in 2019 and forecasted prevalence in 2050: an analysis for the Global Burden of Disease Study 2019

BACKGROUND

Given the projected trends in population ageing and population growth, the number of people with dementia is expected to increase. In addition, strong evidence has emerged supporting the importance of potentially modifiable risk factors for dementia. Characterising the distribution and magnitude of anticipated growth is crucial for public health planning and resource prioritisation. This study aimed to improve on previous forecasts of dementia prevalence by producing country-level estimates and incorporating information on selected risk factors.

METHODS

We forecasted the prevalence of dementia attributable to the three dementia risk factors included in the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 (high body-mass index, high fasting plasma glucose, and smoking) from 2019 to 2050, using relative risks and forecasted risk factor prevalence to predict GBD risk-attributable prevalence in 2050 globally and by world region and country. Using linear regression models with education included as an additional predictor, we then forecasted the prevalence of dementia not attributable to GBD risks. To assess the relative contribution of future trends in GBD risk factors, education, population growth, and population ageing, we did a decomposition analysis.

FINDINGS

We estimated that the number of people with dementia would increase from 57·4 (95% uncertainty interval 50·4-65·1) million cases globally in 2019 to 152·8 (130·8-175·9) million cases in 2050. Despite large increases in the projected number of people living with dementia, age-standardised both-sex prevalence remained stable between 2019 and 2050 (global percentage change of 0·1% [-7·5 to 10·8]). We estimated that there were more women with dementia than men with dementia globally in 2019 (female-to-male ratio of 1·69 [1·64-1·73]), and we expect this pattern to continue to 2050 (female-to-male ratio of 1·67 [1·52-1·85]). There was geographical heterogeneity in the projected increases across countries and regions, with the smallest percentage changes in the number of projected dementia cases in high-income Asia Pacific (53% [41-67]) and western Europe (74% [58-90]), and the largest in north Africa and the Middle East (367% [329-403]) and eastern sub-Saharan Africa (357% [323-395]). Projected increases in cases could largely be attributed to population growth and population ageing, although their relative importance varied by world region, with population growth contributing most to the increases in sub-Saharan Africa and population ageing contributing most to the increases in east Asia.

INTERPRETATION

Growth in the number of individuals living with dementia underscores the need for public health planning efforts and policy to address the needs of this group. Country-level estimates can be used to inform national planning efforts and decisions. Multifaceted approaches, including scaling up interventions to address modifiable risk factors and investing in research on biological mechanisms, will be key in addressing the expected increases in the number of individuals affected by dementia.

FUNDING

Bill & Melinda Gates Foundation and Gates Ventures.

Interplay between polygenic propensity for ageing-related traits and the consumption of fruits and vegetables on future dementia diagnosis

BACKGROUND

Understanding how polygenic scores for ageing-related traits interact with diet in determining a future dementia including Alzheimer's diagnosis (AD) would increase our understanding of mechanisms underlying dementia onset.

METHODS

Using 6784 population representative adults aged ≥50 years from the English Longitudinal Study of Ageing, we employed accelerated failure time survival model to investigate interactions between polygenic scores for AD (AD-PGS), schizophrenia (SZ-PGS) and general cognition (GC-PGS) and the baseline daily fruit and vegetable intake in association with dementia diagnosis during a 10-year follow-up. The baseline sample was obtained from waves 3-4 (2006-2009); follow-up data came from wave 5 (2010-2011) to wave 8 (2016-2017).

RESULTS

Consuming < 5 portions of fruit and vegetables a day was associated with 33-37% greater risk for dementia in the following 10 years depending on an individual polygenic propensity. One standard deviation (1-SD) increase in AD-PGS was associated with 24% higher risk of dementia and 47% higher risk for AD diagnosis. 1-SD increase in SZ-PGS was associated with an increased risk of AD diagnosis by 66%(95%CI = 1.05-2.64) in participants who consumed < 5 portions of fruit or vegetables. There was a significant additive interaction between GC-PGS and < 5 portions of the baseline daily intake of fruit and vegetables in association with AD diagnosis during the 10-year follow-up (RERI = 0.70, 95%CI = 0.09-4.82; AP = 0.36, 95%CI = 0.17-0.66).

CONCLUSION

A diet rich in fruit and vegetables is an important factor influencing the subsequent risk of dementia in the 10 years follow-up, especially in the context of polygenetic predisposition to AD, schizophrenia, and general cognition.

Longitudinal validation of an electronic health record delirium prediction model applied at admission in COVID-19 patients

OBJECTIVE

To validate a previously published machine learning model of delirium risk in hospitalized patients with coronavirus disease 2019 (COVID-19).

METHOD

Using data from six hospitals across two academic medical networks covering care occurring after initial model development, we calculated the predicted risk of delirium using a previously developed risk model applied to diagnostic, medication, laboratory, and other clinical features available in the electronic health record (EHR) at time of hospital admission. We evaluated the accuracy of these predictions against subsequent delirium diagnoses during that admission.

RESULTS

Of the 5102 patients in this cohort, 716 (14%) developed delirium. The model's risk predictions produced a c-index of 0.75 (95% CI, 0.73-0.77) with 27.7% of cases occurring in the top decile of predicted risk scores. Model calibration was diminished compared to the initial COVID-19 wave.

CONCLUSION

This EHR delirium risk prediction model, developed during the initial surge of COVID-19 patients, produced consistent discrimination over subsequent larger waves; however, with changing cohort composition and delirium occurrence rates, model calibration decreased. These results underscore the importance of calibration, and the challenge of developing risk models for clinical contexts where standard of care and clinical populations may shift.

Hearing Assessment and Rehabilitation for People Living With Dementia

Hearing impairment commonly co-occurs with dementia. Audiologists, therefore, need to be prepared to address the specific needs of people living with dementia (PwD). PwD have needs in terms of dementia-friendly clinical settings, assessments, and rehabilitation strategies tailored to support individual requirements that depend on social context, personality, background, and health-related factors, as well as audiometric HL and experience with hearing assistance. Audiologists typically receive limited specialist training in assisting PwD and professional guidance for audiologists is scarce. The aim of this review was to outline best practice recommendations for the assessment and rehabilitation of hearing impairment for PwD with reference to the current evidence base. These recommendations, written by audiology, psychology, speech-language, and dementia nursing professionals, also highlight areas of research need. The review is aimed at hearing care professionals and includes practical recommendations for adapting audiological procedures and processes for the needs of PwD.

The Impact of Demographic, Socio-Economic and Geographic Factors on Mortality Risk among People Living with Dementia in England (2002-2016)

Increasing numbers of people living with dementia (PLWD), and a pressured health and social care system, will exacerbate inequalities in mortality for PLWD. There is a dearth of research examining multiple factors in mortality risk among PLWD, including application of large administrative datasets to investigate these issues. This study explored variation mortality risk variation among people diagnosed with dementia between 2002-2016, based on: age, sex, ethnicity, deprivation, geography and general practice (GP) contacts. Data were derived from electronic health records from a cohort of Clinical Practice Research Datalink GP patients in England (n = 142,340). Cox proportional hazards regression modelled mortality risk separately for people with early- and later- onset dementia. Few social inequalities were observed in early-onset dementia; men had greater risk of mortality. For early- and later-onset, higher rates of GP observations-and for later-onset only dementia medications-are associated with increased mortality risk. Social inequalities were evident in later-onset dementia. Accounting for other explanatory factors, Black and Mixed/Other ethnicity groups had lower mortality risk, more deprived areas had greater mortality risk, and higher mortality was observed in North East, South Central and South West GP regions. This study provides novel evidence of the extent of mortality risk inequalities among PLWD. Variance in mortality risk was observed by social, demographic and geographic factors, and frequency of GP contact. Findings illustrate need for greater person-centred care discussions, prioritising tackling inequalities among PLWD. Future research should explore more outcomes for PLWD, and more explanatory factors of health outcomes.

Association of major blood lipids with post-stroke dementia: a community-based cohort study

Background and purpose

The roles of blood low‐density lipoprotein cholesterol (LDL‐C), high‐density lipoprotein cholesterol (HDL‐C) and triglycerides in the development of post‐stroke dementia remain uncertain. This study was to investigate their potential associations.

Methods

A retrospective cohort study was conducted using the Clinical Practice Research Datalink. Patients with first‐ever stroke but no prior dementia were followed up for 10 years. Cox regression was used to examine the association of baseline LDL‐C, HDL‐C and triglycerides with post‐stroke dementia.

Results

Amongst 63,959 stroke patients, 15,879 had complete baseline data and were included in our main analysis. 10.8% developed dementia during a median of 4.6 years of follow‐up. The adjusted hazard ratio of dementia for LDL‐C (per log mmol/l increase) was 1.29 (95% confidence interval [CI] 1.14–1.47), with a linear increasing trend (p trend <0.001). The counterpart for triglycerides was 0.79 (95% CI 0.69–0.89), with a linear decreasing trend (p trend <0.001). For HDL‐C, there was no association with dementia (adjusted hazard ratio 0.89, 95% CI 0.74–1.08) or a linear trend (p trend = 0.22).

Conclusions

Blood lipids may affect the risk of post‐stroke dementia in different ways, with higher risk associated with LDL‐C, lower risk associated with triglycerides, and no association with HDL‐C.

A classification algorithm to predict chronic pain using both regression and machine learning - A stepwise approach

This secondary data analysis study aimed to (1) investigate the use of two sense-based parameters (movement and sleep hours) as predictors of chronic pain when controlling for patient demographics and depression, and (2) identify a classification model with accuracy in predicting chronic pain. Data collected by Oregon Health & Science University between March 2018 and December 2019 under the Collaborative Aging Research Using Technology Initiative were analyzed in two stages. Data were collected by sensor technologies and questionnaires from older adults living independently or with a partner in the community. In Stage 1, regression models were employed to determine unique sensor-based behavioral predictors of pain. These sensor-based parameters were used to create a classification model to predict the weekly recalled pain intensity and interference level using a deep neural network model, a machine learning approach, in Stage 2. Daily step count was a unique predictor for both pain intensity (75% Accuracy, F1 = 0.58) and pain interference (82% Accuracy, F1 = 0.59). The developed classification model performed well in this dataset with acceptable accuracy scores. This study demonstrated that machine learning technique can be used to identify the relationship between patients' pain and the risk factors.

The Performance of Dual-Task Tests Can Be a Combined Neuro-Psychological and Motor Marker of Mild Cognitive Impairment, Depression and Dementia in Geriatric Patients-A Cross-Sectional Study

The study aims to assess the performance of dual-task tests in the geriatric population and their association with the cognitive status of the patients.

METHODS

Patients admitted to the Department of Geriatrics, Hospital of the Ministry of Interior and Administration on Bialystok, Poland, in 2019 and 2020 were enrolled in the study. Data on the patients' clinical, functional, and cognitive status were collected based on the comprehensive geriatric assessment. Dual-task tests included Timed Up and Go (TUG) test while counting backward (CB7), enumerating animals (EA), and holding a cup (TUG M).

RESULTS

250 patients were included in the study, with a median age of 81.5 years (IQR 76-86) and most above 75 years of age (80.8%). Only 29 (11.6%) of study participants had no cognitive or mood disorders. Depression was diagnosed in 30.4%, MCI in 12%, and dementia in 38.4% of cases with median Mini-Mental Score Evaluation (MMSE) 17 (12-20) points. Dual-task TUG CB7 results did not differ between cognitive conditions of patients. TUG EA differed between healthy controls and other cognitive groups and TUG between healthy controls and depression and dementia, but not mild cognitive impairment (MCI). The performance of all dual-task tests differed in patients with and without dementia. Ability to finish TUG CB7 was low even in the group without dementia. There were statistically significant differences in median scores of MMSE and Clock Drawing Test (CDT) between patients who were able or not to finish single and dual-task gait tests.

CONCLUSION

Dual-task test results and the performance of these tasks can differentiate patients with depression, MCI and dementia compared to healthy controls in the geriatric population.

‘We're happy as we are’: the experience of living with possible undiagnosed dementia

It is estimated that a third of people in the United Kingdom with signs of dementia are living without a formal diagnosis. In Wales, the proportion is nearly half. Some explanations for the gap between prevalence of dementia and number of diagnoses include living with a long-term partner/spouse and systemic barriers to diagnosis. This study recruited participants from the Cognitive Function and Ageing Studies-Wales (CFAS-Wales) cohort, randomly selected from people aged over 65 living in two areas of Wales, who met study criteria for a diagnosis of dementia and did not have a record of a formal diagnosis in general practice records. We aimed to understand more about the contexts and circumstances of people who live with and cope with cognitive difficulties without having a formal diagnosis of dementia. We conducted qualitative interviews with six participants and their spouses, and additionally with four family members of three invited people who were unable to take part. Themes were generated using thematic analysis. We present the argument that there is an adaptive response to low service levels and a complex interaction between the expectations of levels of service, perceptions of the legitimacy of cognitive problems and the right to make demands on services. This paper concludes that more could be done to address barriers to diagnosis and treatment services for those living with symptoms of dementia, but that the value placed on diagnosis by some individuals might be lower than anticipated by government policy.

Validation of the Taiwanese Version of ACE-III (T-ACE-III) to Detect Dementia in a Memory Clinic

OBJECTIVE

The Addenbrooke's Cognitive Examination III (ACE-III) is a 100-points cognitive test used in detecting dementia in many countries. There has been no validation study of the ACE-III in patients with suspected dementia in a Taiwanese population, where the language is traditional Chinese. We aimed to culturally adapt and validate the ACE-III as a cognitive assessment tool for differentiating between people with and without dementia presenting to healthcare professionals in Taiwan with possible dementia.

METHODS

We culturally adapted the ACE-III for Taiwan (T-ACE-III) and tested it with consenting patients with suspected dementia in northern Taiwan who had been through the diagnostic process. We calculated receiver operating characteristic (ROC) curves to test the ability of the T-ACE-III to differentiate between dementia and non-dementia cases using clinician diagnosis as the gold standard. We generated the Youden Index to determine the best cut-off score.

RESULTS

We recruited 90 Taiwanese individuals aged 49-93 years: 24 males and 33 females had dementia and 12 males and 21 females did not. The area under the ROC curve was 0.99 for distinguishing dementia from non-dementia. The T-ACE-III had a sensitivity of 100% and specificity of 78.8% when the cut-off score was 86/87. With a cut-off value of 73/74, the specificity was 100.0%, and sensitivity 89.5%. The highest Youden Index was 0.895, indicating the best overall cut-off point to be 73/74.

CONCLUSIONS

The T-ACE-III is an acceptable cognitive test with excellent psychometric properties for discriminating dementia from non-dementia in Taiwanese populations in memory clinic settings.

Socio-Economic Disparities in Access to Diagnostic Neuroimaging Services in the United Kingdom: A Systematic Review

Socio-economic factors affecting health care can lead to delays in diagnosis of neurological conditions, consequentially affecting treatment and morbidity rates. This inequality in health care can leave patients from lower socio-economic backgrounds more vulnerable to a poorer quality of care from health care providers in the United Kingdom (U.K.). Aims: In this systematic review, we assess the impact of socio-economic status on the use of diagnostic neuroimaging in the U.K., measured by the timeliness, accessibility and appropriate use of computed tomography (CT), magnetic resonance imaging (MRI), ultrasonography, electroencephalography (EEG) and single-photon emission computed tomography (SPECT). We specifically evaluate the non-surgical use of neuroimaging techniques as this relies on the judgment of primary care-givers (e.g., doctors and radiologists), where health disparities are most common. This study includes the analysis of diagnostic imaging used for dementia, minor head injury, stroke, cancer, epilepsy, chronic inflammatory demyelinating polyneuropathy and Parkinson’s disease. With this study, we aim to assess the health inequalities at disease diagnosis. Methods: Using Medline (via Ovid), PubMed and Web of Science databases as sources of information, we critically appraise existing studies on neuroimaging use in the U.K. health care system, published between January 2010 and February 2021. Findings: A total of 18 studies were included in this research, revealing that there was an increase in patients of Black and Asian communities diagnosed with dementia and at an earlier age. There was little evidence to suggest that a lack of access to diagnostic imaging is associated with socio-economic status. However, there are data to suggest that people of a lower socio-economic background require more specialist services with diagnostic neuroimaging tools. In addition, there is evidence to suggest that diagnostic neuroimaging techniques could be utilised more effectively by health care workers to prevent unnecessary delays in diagnosis for patients in lower socio-economic areas.

Improved quality of care and reduced healthcare costs at the end-of-life among older people with dementia who received palliative home care: A nationwide propensity score-matched decedent cohort study

BACKGROUND

While palliative home care is advocated for people with dementia, evidence of its effectiveness is lacking.

AIM

To evaluate the effects of palliative home care on quality and costs of end-of-life care for older people with dementia.

DESIGN

Decedent cohort study using linked nationwide administrative databases and propensity score matching.

SETTING/PARTICIPANTS

All home-dwelling older people who died with dementia between 2010 and 2015 in Belgium (N = 23,670).

EXPOSURE

Receiving palliative home care support for the first time between 360 and 15 days before death.

RESULTS

Five thousand six hundred and thirty-seven (23.8%) received palliative home care support in the last 2 years of life, of whom 2918 received it for the first time between 360 and 15 days before death. Two thousand eight hundred and thirty-nine people who received support were matched to 2839 people who received usual care. After matching, those using palliative home care support, in the last 14 days of life, had lower risk of hospital admission (17.5% vs 50.5%; relative risk (RR) = 0.21), undergoing diagnostic testing (17.0% vs 53.6%; RR = 0.20) and receiving inappropriate medications, but were more likely to die at home (75.7% vs 32.6%; RR = 6.45) and to have primary care professional contacts (mean 11.7 vs mean 5.2), compared with those who did not. Further, they had lower mean total costs of care in the last 30 days of life (incremental cost:-€2129).

CONCLUSIONS

Palliative home care use by home-dwelling older people with dementia is associated with improved quality and reduced costs of end-of-life care. Access remains low and should be increased.