Unsupervised multimodal modeling of cognitive and brain health trajectories for early dementia prediction.

Predicting the course of neurodegenerative disorders early has potential to greatly improve clinical management and patient outcomes. A key challenge for early prediction in real-world clinical settings is the lack of labeled data (i.e., clinical diagnosis). In contrast to supervised classification approaches that require labeled data, we propose an unsupervised multimodal trajectory modeling (MTM) approach based on a mixture of state space models that captures changes in longitudinal data (i.e., trajectories) and stratifies individuals without using clinical diagnosis for model training. MTM learns the relationship between states comprising expensive, invasive biomarkers (ß-amyloid, grey matter density) and readily obtainable cognitive observations. MTM training on trajectories stratifies individuals into clinically meaningful clusters more reliably than MTM training on baseline data alone and is robust to missing data (i.e., cognitive data alone or single assessments). Extracting an individualized cognitive health index (i.e., MTM-derived cluster membership index) allows us to predict progression to AD more precisely than standard clinical assessments (i.e., cognitive tests or MRI scans alone). Importantly, MTM generalizes successfully from research cohort to real-world clinical data from memory clinic patients with missing data, enhancing the clinical utility of our approach. Thus, our multimodal trajectory modeling approach provides a cost-effective and non-invasive tool for early dementia prediction without labeled data (i.e., clinical diagnosis) with strong potential for translation to clinical practice.

Diagnostic accuracy of cognitive screening tools validated for older adults in Iran: a systematic review and meta-analysis.

BACKGROUND: This systematic review aims to comprehensively assess the diagnostic accuracy of cognitive screening tools validated for older adults in Iran, providing evidence-based recommendations for clinicians and researchers. METHODS: A comprehensive search in March 2023 across Web of Science, PubMed, Scopus, ScienceDirect, SID, IranMedex, and IranDoc, enhanced by hand-searching references and Google Scholar, identified cross-sectional studies on cognitive screening in Iranian seniors. We assessed diagnostic accuracy, cognitive domains, and test strengths and weaknesses. A bivariate random-effects meta-analysis provided summary estimates and 95% confidence intervals, illustrated in forest plots. RESULTS: Our review, derived from an initial screening of 38 articles, focused on 17 studies involving 14 cognitive screening tools and participant counts from 60 to 350, mostly from specialized clinics. The MMSE was the only tool examined in at least three studies, prompting a meta-analysis revealing its sensitivity at 0.89 and specificity at 0.77 for dementia detection, albeit amidst significant heterogeneity (I^2 > 80%). ACE-III demonstrated the highest diagnostic accuracy for MCI and dementia, while MoCA's performance was deemed adequate for MCI and excellent for dementia. High bias risk in studies limits interpretation. CONCLUSION: This review identifies key cognitive tools for dementia and MCI in Iranian older adults, tailored to educational levels for use in primary and specialized care. It emphasizes the need for further validation to enhance diagnostic precision across diverse settings, within a concise framework prioritizing brevity and accuracy for clinical applicability.

Prevalence and Determinants of Diagnosed Dementia: A Registry Linkage Study Linking Diagnosis of Dementia in the Population-Based HUNT Study to Registry Diagnosis of Dementia in Primary Care and Hospitals in Norway.

Background: A timely diagnosis of dementia can be beneficial for providing good support, treatment, and care, but the diagnostic rate remains unknown and is probably low. Objective: To determine the dementia diagnostic rate and to describe factors associated with diagnosed dementia. Methods: This registry linkage study linked information on research-based study diagnoses of all-cause dementia and subtypes of dementias, Alzheimer's disease, and related dementias, in 1,525 participants from a cross-sectional population-based study (HUNT4 70+) to dementia registry diagnoses in both primary-care and hospital registries. Factors associated with dementia were analyzed with multiple logistic regression. Results: Among those with research-based dementia study diagnoses in HUNT4 70+, 35.6% had a dementia registry diagnosis in the health registries. The diagnostic rate in registry diagnoses was 19.8% among home-dwellers and 66.0% among nursing home residents. Of those with a study diagnosis of Alzheimer's disease, 35.8% (95% confidence interval (CI) 32.6-39.0) had a registry diagnosis; for those with a study diagnosis of vascular dementia, the rate was 25.8% (95% CI 19.2-33.3) and for Lewy body dementias and frontotemporal dementia, the diagnosis rate was 63.0% (95% CI 48.7-75.7) and 60.0% (95% CI 43.3-75.1), respectively. Factors associated with having a registry diagnosis included dementia in the family, not being in the youngest or oldest age group, higher education, more severe cognitive decline, and greater need for help with activities of daily living. Conclusions: Undiagnosed dementia is common, as only one-third of those with dementia are diagnosed. Diagnoses appear to be made at a late stage of dementia.

Peripheral GFAP and NfL as early biomarkers for dementia: longitudinal insights from the UK Biobank.

BACKGROUND: Peripheral glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) are sensitive markers of neuroinflammation and neuronal damage. Previous studies with highly selected participants have shown that peripheral GFAP and NfL levels are elevated in the pre-clinical phase of Alzheimer's disease (AD) and dementia. However, the predictive value of GFAP and NfL for dementia requires more evidence from population-based cohorts. METHODS: This was a prospective cohort study to evaluate UK Biobank participants enrolled from 2006 to 2010 using plasma GFAP and NfL measurements measured by Olink Target Platform and prospectively followed up for dementia diagnosis. Primary outcome was the risk of clinical diagnosed dementia. Secondary outcomes were cognition. Linear regression was used to assess the associations between peripheral GFAP and NfL with cognition. Cox proportional hazard models with cross-validations were used to estimate associations between elevated GFAP and NfL with risk of dementia. All models were adjusted for covariates. RESULTS: A subsample of 48,542 participants in the UK Biobank with peripheral GFAP and NfL measurements were evaluated. With an average follow-up of 13.18 ± 2.42 years, 1312 new all-cause dementia cases were identified. Peripheral GFAP and NfL increased up to 15 years before dementia diagnosis was made. After strictly adjusting for confounders, increment in NfL was found to be associated with decreased numeric memory and prolonged reaction time. A greater annualized rate of change in GFAP was significantly associated with faster global cognitive decline. Elevation of GFAP (hazard ratio (HR) ranges from 2.25 to 3.15) and NfL (HR ranges from 1.98 to 4.23) increased the risk for several types of dementia. GFAP and NfL significantly improved the predictive values for dementia using previous models (area under the curve (AUC) ranges from 0.80 to 0.89, C-index ranges from 0.86 to 0.91). The AD genetic risk score and number of APOE*E4 alleles strongly correlated with GFAP and NfL levels. CONCLUSIONS: These results suggest that peripheral GFAP and NfL are potential biomarkers for the early diagnosis of dementia. In addition, anti-inflammatory therapies in the initial stages of dementia may have potential benefits.

Association between colchicine use and the risk of dementia among patients with gout: A nationwide retrospective cohort study.

BACKGROUND: Recent findings suggest a link between gout and the development of dementia. Early treatment with colchicine is recommended as a first-line therapy for gout flares. Animal studies demonstrate that colchicine could induce cognitive impairment. This cohort study aimed to investigate the association between colchicine use and the risk of developing dementia. METHODS: In this nationwide cohort study, we performed comparative analysis on 6147 patients ≥40 years, with gout and colchicine new users against 6147 controls to assess subsequent dementia risk. The colchicine group and the control group (urate lowering therapy group) were matched on the bases of age, sex, index year, and comorbidities. All participants were followed for up to 14 years for a diagnosis of dementia considering medical records were retrospectively checked over this period. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Sensitivity analyses were performed to validate our findings. RESULTS: The adjusted hazard ratio (aHR) of dementia for colchicine users was 1.45 (95% CI = 1.05, 1.99) relative to comparison group after adjusting for sex, age, and comorbidities. Sensitivity analysis aiming to minimize underdiagnosed occult dementia at the time of index year yielded consistent positive association. In higher accumulative dose colchicine group (cumulative defined daily dose [cDDD] >30), the aHR of dementia risk for colchicine users was 1.42 (95% CI = 1.03, 1.97) compared with nonusers. For those duration of colchicine use >30 days, the aHR was 1.53 (95% CI = 1.01-2.32) compared to the nonuser group. CONCLUSIONS: A significant risk of dementia was observed in this study in patients with gout using colchicine at higher cDDD and for a longer period. Further research is needed to elucidate the relationship between colchicine, gout, and dementia.

Community screening for dementia among older adults in China: a machine learning-based strategy.

BACKGROUND: Dementia is a leading cause of disability in people older than 65 years worldwide. However, diagnosing dementia in its earliest symptomatic stages remains challenging. This study combined specific questions from the AD8 scale with comprehensive health-related characteristics, and used machine learning (ML) to construct diagnostic models of cognitive impairment (CI). METHODS: The study was based on the Shenzhen Healthy Ageing Research (SHARE) project, and we recruited 823 participants aged 65 years and older, who completed a comprehensive health assessment and cognitive function assessments. Permutation importance was used to select features. Five ML models using BalanceCascade were applied to predict CI: a support vector machine (SVM), multilayer perceptron (MLP), AdaBoost, gradient boosting decision tree (GBDT), and logistic regression (LR). An AD8 score ≥ 2 was used to define CI as a baseline. SHapley Additive exPlanations (SHAP) values were used to interpret the results of ML models. RESULTS: The first and sixth items of AD8, platelets, waist circumference, body mass index, carcinoembryonic antigens, age, serum uric acid, white blood cells, abnormal electrocardiogram, heart rate, and sex were selected as predictive features. Compared to the baseline (AUC = 0.65), the MLP showed the highest performance (AUC: 0.83 ± 0.04), followed by AdaBoost (AUC: 0.80 ± 0.04), SVM (AUC: 0.78 ± 0.04), GBDT (0.76 ± 0.04). Furthermore, the accuracy, sensitivity and specificity of four ML models were higher than the baseline. SHAP summary plots based on MLP showed the most influential feature on model decision for positive CI prediction was female sex, followed by older age and lower waist circumference. CONCLUSIONS: The diagnostic models of CI applying ML, especially the MLP, were substantially more effective than the traditional AD8 scale with a score of ≥ 2 points. Our findings may provide new ideas for community dementia screening and to promote such screening while minimizing medical and health resources.

[Aspiration pneumonia and dementia in nursing homes: to anticipate emergency.] / Pneumonie d'aspiration en EMS et démence : anticiper l'urgence.

The care of a nursing home resident suffering from dementia and aspiration pneumonia (AP) is generally initiated by the family doctor (FD) in collaboration with the nursing home professionals. This is a holistic emergency medicine whose occurrence should be the subject of advance care planning, an AP being rarely isolated, and its risk factors are known. AP - the probable cause of half of deaths of demented individuals in nursing homes - requires essentially non-hospital care. It calls on the scientific, relational, collaborative, and ethical skills of the family doctor. This review aims to contextualize the emergency management skills of the FD in the living environment of the nursing home. The management of uncertainty linked to a probabilistic diagnosis is highlighted and care commensurate with life expectancy is provided.

La prise en soins d'un résident d'un établissement médicosocial (EMS) souffrant de démence et de pneumonie d'aspiration (PA) est en général initiée par le médecin de famille (MF) en collaboration avec les professionnels du lieu de vie de la personne. Il s'agit d'une médecine d'urgence holistique qui devrait faire l'objet d'un plan de soins anticipés, la PA étant rarement isolée et ses facteurs de risque étant connus. La PA est la cause probable de la moitié des décès de personnes démentes en EMS. Elle ne devrait en principe pas nécessiter d'hospitalisation. La PA fait appel à des compétences scientifiques, relationnelles, collaboratives et éthiques du MF. Dans cet article de revue, nous contextualisons les compétences de gestion de l'urgence du MF dans un EMS. Nous discutons également de la gestion de l'incertitude en lien avec un diagnostic probabiliste et proposons des soins en adéquation avec l'espérance de vie.

An algorithm for the early diagnosis and correct approach to dementia management: results of a multiprofessional team.

BACKGROUNG: The early identification of cognitive disorder is a primary scope, because it could reduce the rate of severe cognitive impairment and thus contribute to reduce healthcare costs in the next future. AIMS: The present paper aimed to build a virtuous diagnostic path of cognitive impairment, highlighting all the professionalism that can serve this purpose. METHODS: The Delphi method was used by the experts, who reviewed the information available during each meeting related to the following topics: early diagnosis of cognitive impairment, definition of Mild Cognitive Impairment, unmet needs in post-stroke patients, critical decision-making nodes in complex patients, risk factors, neuropsychological, imaging diagnosis, blood tests, the criteria for differential diagnosis and the possible treatments. RESULTS: The discussion panels analyzed and discussed the available evidences on these topics and the related items. At each meeting, the activities aimed at the creation of a diagnostic-welfare flow chart derived from the proposal of the board and the suggestions of the respondents. Subsequently, the conclusions of each panel were written, and the study group reviewed them until a global consensus was reached. Once this process was completed, the preparation of the final document was carried out. CONCLUSIONS: Eventually, we built an algorithm for the early diagnosis and treatment, the risk factors, with the possible differences among the different kinds of dementia.

Cognitive Impairment in the Primary Care Clinic.

Cognitive impairment is a common problem in the geriatric population and is characterized by variable symptoms of memory difficulties, executive dysfunction, language or visuospatial problems, and behavioral changes. It is imperative that primary care clinicians recognize and differentiate the variable symptoms associated with cognitive impairment from changes attributable to normal aging or secondary to other medical conditions. A thorough evaluation for potentially reversible causes of dementia is required before diagnosis with a neurodegenerative dementia. Other abnormal neurologic findings, rapid progression, or early age of onset are red flags that merit referral to neurology for more specialized evaluation and treatment.

Deep phenotyping of dementia in a multi-ethnic cardiovascular cohort: The Multi-Ethnic Study of Atherosclerosis (MESA).

BACKGROUND: Our understanding of the specific aspects of vascular contributions to dementia remains unclear. OBJECTIVES: We aim to identify the correlates of incident dementia in a multi-ethnic cardiovascular cohort. METHODS: A total of 6806 participants with follow-up data for incident dementia were included. Probable dementia diagnoses were identified using hospitalization discharge diagnoses according to the International Classification of Diseases Codes (ICD). We used Random Forest analyses to identify the correlates of incident dementia and cognitive function from among 198 variables collected at the baseline MESA exam entailing demographic risk factors, medical history, anthropometry, lab biomarkers, electrocardiograms, cardiovascular magnetic resonance imaging, carotid ultrasonography, coronary artery calcium and liver fat content. Death and stroke were considered competing events. RESULTS: Over 14 years of follow-up, 326 dementia events were identified. Beyond age, the top correlates of dementia included coronary artery calcification, high sensitivity troponin, common carotid artery intima to media thickness, NT-proBNP, physical activity, pulse pressure, tumor necrosis factor-α, history of cancer, and liver to spleen attenuation ratio from computed tomography. Correlates of cognitive function included income and physical activity, body size, serum glucose, glomerular filtration rate, measures of carotid artery stiffness, alcohol use, and inflammation indexed as IL-2 and TNF soluble receptors and plasmin-antiplasmin complex. CONCLUSION: In a deeply phenotyped cardiovascular cohort we identified the key correlates of dementia beyond age as subclinical atherosclerosis and myocyte damage, vascular function, inflammation, physical activity, hepatic steatosis, and history of cancer.

Plasma GFAP, NfL and pTau 181 detect preclinical stages of dementia.

Background: Plasma biomarkers are preferable to invasive and expensive diagnostic tools, such as neuroimaging and lumbar puncture that are gold standard in the clinical management of Alzheimer's Disease (AD). Here, we investigated plasma Glial Fibrillary Acidic Protein (GFAP), Neurofilament Light Chain (NfL) and Phosphorylated-tau-181 (pTau 181) in AD and in its early stages: Subjective cognitive decline (SCD) and Mild cognitive impairment (MCI). Material and methods: This study included 152 patients (42 SCD, 74 MCI and 36 AD). All patients underwent comprehensive clinical and neurological assessment. Blood samples were collected for Apolipoprotein E (APOE) genotyping and plasma biomarker (GFAP, NfL, and pTau 181) measurements. Forty-three patients (7 SCD, 27 MCI, and 9 AD) underwent a follow-up (FU) visit after 2 years, and a second plasma sample was collected. Plasma biomarker levels were detected using the Simoa SR-X technology (Quanterix Corp.). Statistical analysis was performed using SPSS software version 28 (IBM SPSS Statistics). Statistical significance was set at p < 0.05. Results: GFAP, NfL and pTau 181 levels in plasma were lower in SCD and MCI than in AD patients. In particular, plasma GFAP levels were statistically significant different between SCD and AD (p=0.003), and between MCI and AD (p=0.032). Plasma NfL was different in SCD vs MCI (p=0.026), SCD vs AD (p<0.001), SCD vs AD FU (p<0.001), SCD FU vs AD (p=0.033), SCD FU vs AD FU (p=0.011), MCI vs AD (p=0.002), MCI FU vs AD (p=0.003), MCI FU vs AD FU (p=0.003) and MCI vs AD FU (p=0.003). Plasma pTau 181 concentration was significantly different between SCD and AD (p=0.001), MCI and AD (p=0.026), MCI FU and AD (p=0.020). In APOE ϵ4 carriers, a statistically significant increase in plasma NfL (p<0.001) and pTau 181 levels was found (p=0.014). Moreover, an association emerged between age at disease onset and plasma GFAP (p = 0.021) and pTau181 (p < 0.001) levels. Discussion and conclusions: Plasma GFAP, NfL and pTau 181 are promising biomarkers in the diagnosis of the prodromic stages and prognosis of dementia.

Feasibility and acceptability of NIDUS-professional, a training and support intervention for homecare workers caring for clients living with dementia: a cluster-randomised feasibility trial.

INTRODUCTION: In the first randomised controlled trial of a dementia training and support intervention in UK homecare agencies, we aimed to assess: acceptability of our co-designed, manualised training, delivered by non-clinical facilitators; outcome completion feasibility; and costs for a future trial. METHODS: This cluster-randomised (2:1) single-blind, feasibility trial involved English homecare agencies. Intervention arm agency staff were offered group videocall sessions: 6 over 3 months, then monthly for 3 months (NIDUS-professional). Family carers (henceforth carers) and clients with dementia (dyads) were offered six to eight complementary, individual intervention sessions (NIDUS-Family). We collected potential trial measures as secondary outcomes remotely at baseline and 6 months: HCW (homecare worker) Work-related Strain Inventory (WRSI), Sense of Competence (SoC); proxy-rated Quality of Life (QOL), Disability Assessment for Dementia scale (DAD), Neuropsychiatric Inventory (NPI) and Homecare Satisfaction (HCS). RESULTS: From December 2021 to September 2022, we met agency (4 intervention, 2 control) and HCWs (n = 62) recruitment targets and recruited 16 carers and 16/60 planned clients. We met a priori progression criteria for adherence (≥4/6 sessions: 29/44 [65.9%,95% confidence interval (CI): 50.1,79.5]), HCW or carer proxy-outcome completion (15/16 (93.8% [69.8,99.8]) and proceeding with adaptation for HCWs outcome completion (46/63 (73.0% [CI: 60.3,83.4]). Delivery of NIDUS-Professional costs was £6,423 (£137 per eligible client). WRSI scores decreased and SoC increased at follow-up, with no significant between-group differences. For intervention arm proxy-rated outcomes, carer-rated QOL increased, HCW-rated was unchanged; carer and HCW-rated NPI decreased; DAD decreased (greater disability) and HCS was unchanged. CONCLUSION: A pragmatic trial is warranted; we will consider using aggregated, agency-level client outcomes, including neuropsychiatric symptoms.

State Department of Motor Vehicles Reporting Mandates of Dementia Diagnoses and Dementia Underdiagnosis.

Importance: With older drivers representing the fastest growing segment of the driver population and dementia prevalence increasing with age, policymakers face the challenge of balancing road safety and mobility of older adults. In states that require reporting a dementia diagnosis to the Department of Motor Vehicles (DMV), individuals with dementia may be reluctant to disclose symptoms of cognitive decline, and clinicians may be reluctant to probe for those symptoms, which may be associated with missed or delayed diagnoses. Objective: To assess whether DMV reporting policies for drivers with dementia are associated with primary care clinicians' underdiagnosing dementia. Design, Setting, and Participants: This cross-sectional study used data from the 100% Medicare fee-for-service program and the Medicare Advantage plans from 2017 to 2019 on 223 036 primary care clinicians with at least 25 Medicare patients. Statistical analysis was performed from July to October 2023. Exposures: State DMV reporting policies for drivers with dementia. Main Outcomes and Measures: The main outcome was a binary variable indicating whether the clinician underdiagnosed dementia or not. Each clinician's expected number of dementia cases was estimated using a predictive model based on patient characteristics. Comparing the estimation with observed dementia diagnoses identified clinicians who underdiagnosed dementia vs those who did not, after accounting for sampling errors. Results: Four states have clinician reporting mandates, 14 have mandates requiring drivers to self-report dementia diagnoses, and 32 states and the District of Columbia do not have explicit requirements. Among primary care clinicians in states with clinician reporting mandates (n = 35 620), 51.4% were female, 91.9% worked in a metropolitan area, and 19.9% of the patient panel were beneficiaries dually eligible for Medicare and Medicaid. Among primary care clinicians in states with patient self-reporting mandates (n = 57 548), 55.7% were female, 83.1% worked in a metropolitan area, and 15.4% of the patient panel were dually eligible for Medicare and Medicaid. Among clinicians in states without mandates, 55.7% were female, 83.0% worked in a metropolitan area, and 14.6% of the patient panel were dually eligible for Medicare and Medicaid. Clinicians in states with clinician reporting mandates had an adjusted 12.4% (95% CI, 10.5%-14.2%) probability of underdiagnosing dementia compared with 7.8% (95% CI, 6.9%-8.7%) in states with self-reporting and 7.7% (95% CI, 6.9%-8.4%) in states with no mandates, an approximately 4-percentage point difference (P < .001). Conclusions and Relevance: Results of this cross-sectional study of primary care clinicians suggest that mandatory DMV policies for clinicians to report patients with dementia may be associated with a higher risk of missed or delayed dementia diagnoses. Future research is needed to better understand the unintended consequences and the risk-benefit tradeoffs of these policies.

Cluster analysis dissecting cognitive deficits in older adults with major depressive disorder and the association with neurofilament light chain.

BACKGROUND: Cognitive impairment is a growing problem with increasing burden in global aging. Older adults with major depressive disorder (MDD) have higher risk of dementia. Neurofilament light chain (NfL) has been proven as a potential biomarker in neurodegenerative disease, including dementia. We aimed to investigate the association between cognitive deficits and NfL levels in older adults with MDD. METHODS: In this cross-sectional study, we enrolled 39 MDD patients and 15 individuals with mild neurocognitive disorder or major neurocognitive disorder, Alzheimer's type, as controls, from a tertiary psychiatric hospital. Both groups were over age 65 and with matched Mini-Mental State Examination (MMSE) score. Demographic data, clinical variables, and plasma NfL levels were obtained. We used cluster analysis according to their cognitive profile and estimated the correlation between plasma NfL levels and each cognitive domain. RESULTS: In the MDD group, participants had higher rate of family psychiatry history and current alcohol use habit compared with controls. Control group of neurocognitive disorders showed significantly lower score in total MMSE and higher plasma NfL levels. Part of the MDD patients presented cognitive deficits clustered with that of neurocognitive disorders (cluster A). In cluster A, the total MMSE score (r=-0.58277, p=0.0287) and the comprehension domain (r=-0.71717, p=0.0039) were negatively correlated to NfL levels after adjusting for age, while the associations had not been observed in the other cluster. CONCLUSIONS: We noted the negative correlation between NfL levels and cognition in MDD patients clustered with neurodegenerative disorder, Alzheimer's type. NfL could be a promising candidate as a biomarker to predict subtype of patients in MDD to develop cognitive decline. Further longitudinal studies and within MDD cluster analysis are required to validate our findings for clinical implications.

The impact of a hospital-based special care unit on behavioural and psychological symptoms in older people living with dementia.

BACKGROUND: Hospital patients with behavioural and psychological symptoms of dementia (BPSD) are vulnerable to a range of adverse outcomes. Hospital-based Special Care Units (SCUs) are secure dementia-enabling environments providing specialised gerontological care. Due to a scarcity of research, their value remains unconfirmed. OBJECTIVE: To compare hospital based SCU management of BPSD with standard care. DESIGN: Single-case multiple baseline design. SETTING AND PARTICIPANTS: One-hundred admissions to an 8-bed SCU over 2 years in a large Australian public hospital. METHODS: Repeated measures of BPSD severity were undertaken prospectively by specialist dementia nurses for patients admitted to a general ward (standard care) and transferred to the SCU. Demographic and other clinical data, including diagnoses, medication use, and care-related outcomes were obtained from medical records retrospectively. Analysis used multilevel models to regress BPSD scores onto care-setting outcomes, adjusting for time and other factors. RESULTS: When receiving standard care, patients' BPSD severity was 6.8 (95% CI 6.04-7.64) points higher for aggression, 15.6 (95% CI 13.90-17.42) points higher for the neuropsychiatric inventory, and 5.8 (95% CI 5.14-6.50) points higher for non-aggressive agitation compared to SCU. Patients receiving standard care also experienced increased odds for patient-to-nurse violence (OR 2.61, 95% CI 1.67-4.09), security callouts (OR 5.39 95% CI 3.40-8.52), physical restraint (OR 17.20, 95% CI 7.94-37.25) and antipsychotic administration (OR 3.41, 95% CI 1.60-7.24). CONCLUSION: Clinically significant reductions in BPSD and psychotropic administration were associated with SCU care relative to standard ward care. These results suggest more robust investigation of hospital SCUs, and dementia-enabling design are warranted.

Barriers and facilitators to care for agitation and/or aggression among persons living with dementia in long-term care.

BACKGROUND: Agitation and/or aggression affect up to 60% of persons living with dementia in long-term care (LTC). It can be treated via non-pharmacological and pharmacological interventions, but the former are underused in clinical practice. In the literature, there is currently a lack of understanding of the challenges to caring for agitation and/or aggression among persons living with dementia in LTC. This study assesses what barriers and facilitators across the spectrum of care exist for agitation and/or aggression among people with dementia in LTC across stakeholder groups. METHODS: This was a qualitative study that used semi-structured interviews among persons involved in the care and/or planning of care for people with dementia in LTC. Participants were recruited via purposive and snowball sampling, with the assistance of four owner-operator models. Interviews were guided by the Theoretical Domains Framework and transcribed and analyzed using Framework Analysis. RESULTS: Eighteen interviews were conducted across 5 stakeholder groups. Key identified barriers were a lack of agitation and/or aggression diagnostic measures, limited training for managing agitation and/or aggression in LTC, an overuse of physical and chemical restraints, and an underuse of non-pharmacological interventions. Facilitators included using an interdisciplinary team to deliver care and having competent and trained healthcare providers to administer non-pharmacological interventions. CONCLUSIONS: This study advances care for persons living with dementia in LTC by drawing attention to unique and systemic barriers present across local and national Canadian LTC facilities. Findings will support future implementation research endeavours to eliminate these identified barriers across the spectrum of care, thus improving care outcomes among people with dementia in LTC.

Potentially inappropriate prescribing for people with dementia in ambulatory care: a cross-sectional observational study.

BACKGROUND: Studies have shown that potentially inappropriate prescribing (PIP) is highly prevalent among people with dementia (PwD) and linked to negative outcomes, such as hospitalisation and mortality. However, there are limited data on prescribing appropriateness for PwD in Saudi Arabia. Therefore, we aimed to estimate the prevalence of PIP and investigate associations between PIP and other patient characteristics among PwD in an ambulatory care setting. METHODS: A cross-sectional, retrospective analysis was conducted at a tertiary hospital in Saudi Arabia. Patients who were ≥ 65 years old, had dementia, and visited ambulatory care clinics between 01/01/2019 and 31/12/2021 were included. Prescribing appropriateness was evaluated by applying the Screening Tool of Older Persons Potentially Inappropriate Prescriptions (STOPP) criteria. Descriptive analyses were used to describe the study population. Prevalence of PIP and the prevalence per each STOPP criterion were calculated as a percentage of all eligible patients. Logistic regression analysis was used to investigate associations between PIP, polypharmacy, age and sex; odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Analyses were conducted using SPSS v27. RESULTS: A total of 287 PwD were identified; 56.0% (n = 161) were female. The mean number of medications prescribed was 9.0 [standard deviation (SD) ± 4.2]. The prevalence of PIP was 61.0% (n = 175). Common instances of PIP were drugs prescribed beyond the recommended duration (n = 90, 31.4%), drugs prescribed without an evidence-based clinical indication (n = 78, 27.2%), proton pump inhibitors (PPIs) for > 8 weeks (n = 75, 26.0%), and acetylcholinesterase inhibitors with concurrent drugs that reduce heart rate (n = 60, 21.0%). Polypharmacy was observed in 82.6% (n = 237) of patients and was strongly associated with PIP (adjusted OR 24.1, 95% CI 9.0-64.5). CONCLUSIONS: Findings have revealed a high prevalence of PIP among PwD in Saudi Arabia that is strongly associated with polypharmacy. Future research should aim to explore key stakeholders' experiences and perspectives of medicines management to optimise medication use for this vulnerable patient population.

Determinants of hospital readmissions in older people with dementia: a narrative review.

INTRODUCTION: Over 50% of hospitalised older people with dementia have multimorbidity, and are at an increased risk of hospital readmissions within 30 days of their discharge. Between 20-40% of these readmissions may be preventable. Current research focuses on the physical causes of hospital readmissions. However, older people with dementia have additional psychosocial factors that are likely to increase their risk of readmissions. This narrative review aimed to identify psychosocial determinants of hospital readmissions, within the context of known physical factors. METHODS: Electronic databases MEDLINE, EMBASE, CINAHL and PsychInfo were searched from inception until July 2022 and followed up in February 2024. Quantitative and qualitative studies in English including adults aged 65 years and over with dementia, their care workers and informal carers were considered if they investigated hospital readmissions. An inductive approach was adopted to map the determinants of readmissions. Identified themes were described as narrative categories. RESULTS: Seventeen studies including 7,194,878 participants met our inclusion criteria from a total of 6369 articles. Sixteen quantitative studies included observational cohort and randomised controlled trial designs, and one study was qualitative. Ten studies were based in the USA, and one study each from Taiwan, Australia, Canada, Sweden, Japan, Denmark, and The Netherlands. Large hospital and insurance records provided data on over 2 million patients in one American study. Physical determinants included reduced mobility and accumulation of long-term conditions. Psychosocial determinants included inadequate hospital discharge planning, limited interdisciplinary collaboration, socioeconomic inequalities among ethnic minorities, and behavioural and psychological symptoms. Other important psychosocial factors such as loneliness, poverty and mental well-being, were not included in the studies. CONCLUSION: Poorly defined roles and responsibilities of health and social care professionals and poor communication during care transitions, increase the risk of readmission in older people with dementia. These identified psychosocial determinants are likely to significantly contribute to readmissions. However, future research should focus on the understanding of the interaction between a host of psychosocial and physical determinants, and multidisciplinary interventions across care settings to reduce hospital readmissions.