Predicting dementia diagnosis from cognitive footprints in electronic health records: a case-control study protocol

INTRODUCTION: Dementia is a group of disabling disorders that can be devastating for persons living with it and for their families. Data-informed decision-making strategies to identify individuals at high risk of dementia are essential to facilitate large-scale prevention and early intervention. This population-based case-control study aims to develop and validate a clinical algorithm for predicting dementia diagnosis, based on the cognitive footprint in personal and medical history. METHODS AND ANALYSIS: We will use territory-wide electronic health records from the Clinical Data Analysis and Reporting System (CDARS) in Hong Kong between 1 January 2001 and 31 December 2018. All individuals who were at least 65 years old by the end of 2018 will be identified from CDARS. A random sample of control individuals who did not receive any diagnosis of dementia will be matched with those who did receive such a diagnosis by age, gender and index date with 1:1 ratio. Exposure to potential protective/risk factors will be included in both conventional logistic regression and machine-learning models. Established risk factors of interest will include diabetes mellitus, midlife hypertension, midlife obesity, depression, head injuries and low education. Exploratory risk factors will include vascular disease, infectious disease and medication. The prediction accuracy of several state-of-the-art machine-learning algorithms will be compared. ETHICS AND DISSEMINATION: This study was approved by Institutional Review Board of The University of Hong Kong/Hospital Authority Hong Kong West Cluster (UW 18-225). Patients' records are anonymised to protect privacy. Study results will be disseminated through peer-reviewed publications. Codes of the resulted dementia risk prediction algorithm will be made publicly available at the website of the Tools to Inform Policy: Chinese Communities' Action in Response to Dementia project (https://www.tip-card.hku.hk/)

Identifying dementia from cognitive footprints in hospital records among Chinese older adults: a machine-learning study

Background: By combining theory-driven and data-driven methods, this study aimed to develop dementia predictive algorithms among Chinese older adults guided by the cognitive footprint theory. Methods: Electronic medical records from the Clinical Data Analysis and Reporting System in Hong Kong were employed. We included patients with dementia diagnosed at 65+ between 2010 and 2018, and 1:1 matched dementia-free controls. We identified 51 features, comprising exposures to established modifiable factors and other factors before and after 65 years old. The performances of four machine learning models, including LASSO, Multilayer perceptron (MLP), XGBoost, and LightGBM, were compared with logistic regression models, for all patients and subgroups by age. Findings: A total of 159,920 individuals (40.5% male; mean age [SD]: 83.97 [7.38]) were included. Compared with the model included established modifiable factors only (area under the curve [AUC] 0.689, 95% CI [0.684, 0.694]), the predictive accuracy substantially improved for models with all factors (0.774, [0.770, 0.778]). Machine learning and logistic regression models performed similarly, with AUC ranged between 0.773 (0.768, 0.777) for LASSO and 0.780 (0.776, 0.784) for MLP. Antipsychotics, education, antidepressants, head injury, and stroke were identified as the most important predictors in the total sample. Age-specific models identified different important features, with cardiovascular and infectious diseases becoming prominent in older ages. Interpretation: The models showed satisfactory performances in identifying dementia. These algorithms can be used in clinical practice to assist decision making and allow timely interventions cost-effectively. Funding: The Research Grants Council of Hong Kong under the Early Career Scheme 27110519

Association of comorbidity with healthcare utilization in people living With dementia, 2010–2019: a population-based cohort study

Evidence on the healthcare utilization associated with comorbidity in people with dementia is lacking in Chinese societies. This study aimed to quantify healthcare utilization associated with comorbidity that is common in people living with dementia. We conducted a cohort study using population-based data from Hong Kong public hospitals. Individuals aged 35+ with a dementia diagnosis between 2010 and 2019 were included. Among 88,151 participants, people with at least two comorbidities accounted for 81.2%. Estimates from negative binomial regressions showed that compared to those with one or no comorbid condition other than dementia, adjusted rate ratios of hospitalizations among individuals with six or seven and eight or more conditions were 1.97 [98.75% CI, 1.89–2.05] and 2.74 [2.63–2.86], respectively; adjusted rate ratios of Accident and Emergency department visits among individuals with six or seven and eight or more conditions were 1.53 [1.44–1.63] and 1.92 [1.80–2.05], respectively. Comorbid chronic kidney diseases were associated with the highest adjusted rate ratios of hospitalizations (1.81 [1.74–1.89]), whereas comorbid chronic ulcer of the skin was associated with the highest adjusted rate ratios of Accident and Emergency department visits (1.73 [1.61–1.85]). Healthcare utilization for individuals with dementia differed substantially by both the number of comorbid chronic conditions and the presence of some specific comorbid conditions. These findings further highlight the importance of taking account of multiple long-term conditions in tailoring the care approach and developing healthcare plans for people with dementia

Health and social care service utilisation and associated expenditure among community-dwelling older adults with depressive symptoms

AIMS: Late-life depression has substantial impacts on individuals, families and society. Knowledge gaps remain in estimating the economic impacts associated with late-life depression by symptom severity, which has implications for resource prioritisation and research design (such as in modelling). This study examined the incremental health and social care expenditure of depressive symptoms by severity. METHODS: We analysed data collected from 2707 older adults aged 60 years and over in Hong Kong. The Patient Health Questionnaire-9 (PHQ-9) and the Client Service Receipt Inventory were used, respectively, to measure depressive symptoms and service utilisation as a basis for calculating care expenditure. Two-part models were used to estimate the incremental expenditure associated with symptom severity over 1 year. RESULTS: The average PHQ-9 score was 6.3 (standard deviation, s.d. = 4.0). The percentages of respondents with mild, moderate and moderately severe symptoms and non-depressed were 51.8%, 13.5%, 3.7% and 31.0%, respectively. Overall, the moderately severe group generated the largest average incremental expenditure (US$5886; 95$3849; 95% CI 2520-5177 or a 176% increase) and the moderate group (US$1843; 95$691; 95% CI 444-939), then gradually fell to negative between scores of 12 (US$- 35; 95$ -171; 95% CI - 417 to 76) and soared to positive and rebounded at the score of 23 (US$601; 95% CI -1652 to 2854). CONCLUSIONS: The association between depressive symptoms and care expenditure is stronger among older adults with mild and moderately severe symptoms. Older adults with the same symptom severity have different care utilisation and expenditure patterns. Non-psychiatric healthcare is the major cost element. These findings inform ways to optimise policy efforts to improve the financial sustainability of health and long-term care systems, including the involvement of primary care physicians and other geriatric healthcare providers in preventing and treating depression among older adults and related budgeting and accounting issues across services

Risk profiles and one-year outcomes of patients with newly diagnosed atrial fibrillation in India: Insights from the GARFIELD-AF Registry.

BACKGROUND: The Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) is an ongoing prospective noninterventional registry, which is providing important information on the baseline characteristics, treatment patterns, and 1-year outcomes in patients with newly diagnosed non-valvular atrial fibrillation (NVAF). This report describes data from Indian patients recruited in this registry. METHODS AND RESULTS: A total of 52,014 patients with newly diagnosed AF were enrolled globally; of these, 1388 patients were recruited from 26 sites within India (2012-2016). In India, the mean age was 65.8 years at diagnosis of NVAF. Hypertension was the most prevalent risk factor for AF, present in 68.5% of patients from India and in 76.3% of patients globally (P < 0.001). Diabetes and coronary artery disease (CAD) were prevalent in 36.2% and 28.1% of patients as compared with global prevalence of 22.2% and 21.6%, respectively (P < 0.001 for both). Antiplatelet therapy was the most common antithrombotic treatment in India. With increasing stroke risk, however, patients were more likely to receive oral anticoagulant therapy [mainly vitamin K antagonist (VKA)], but average international normalized ratio (INR) was lower among Indian patients [median INR value 1.6 (interquartile range {IQR}: 1.3-2.3) versus 2.3 (IQR 1.8-2.8) (P < 0.001)]. Compared with other countries, patients from India had markedly higher rates of all-cause mortality [7.68 per 100 person-years (95% confidence interval 6.32-9.35) vs 4.34 (4.16-4.53), P < 0.0001], while rates of stroke/systemic embolism and major bleeding were lower after 1 year of follow-up. CONCLUSION: Compared to previously published registries from India, the GARFIELD-AF registry describes clinical profiles and outcomes in Indian patients with AF of a different etiology. The registry data show that compared to the rest of the world, Indian AF patients are younger in age and have more diabetes and CAD. Patients with a higher stroke risk are more likely to receive anticoagulation therapy with VKA but are underdosed compared with the global average in the GARFIELD-AF. CLINICAL TRIAL REGISTRATION-URL: http://www.clinicaltrials.gov. Unique identifier: NCT01090362

Perceived Help-Seeking Difficulty, Barriers, Delay, and Burden in Carers of People with Suspected Dementia

Because of an often complicated and difficult-to-access care system, help-seeking for people with suspected dementia can be stressful. Difficulty in help-seeking may contribute to carer burden, in addition to other known stressors in dementia care. This study examined the relationship between perceived help-seeking difficulty and carer burden, and the barriers contributing to perceived difficulty. We interviewed 110 carers accessing a community-based dementia assessment service for suspected dementia of a family member for their perceived difficulty, delays, and barriers in help-seeking, and carers burden in terms of role strain, self-criticism, and negative emotions. Linear regression models showed that perceived help-seeking difficulty is associated with carer self-criticism, while carer role strain and negative emotions are associated with symptom severity of the person with dementia but not help-seeking difficulty. Inadequate knowledge about symptoms, service accessibility, and affordability together explained more than half of the variance in perceived help-seeking difficulty (Nagelkerke R2 = 0.56). Public awareness about symptoms, support in navigating service, and financial support may reduce perceived difficulty in help-seeking, which in turn may reduce carer self-criticism during the early course of illness

Real-world implementation of early intervention in psychosis: resources, funding models and evidence-based practice

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Health Expectancies in Adults Aged 50 Years or Older in China

© The Author(s) 2015. Objective: The purpose of this study is to understand the functional health of older adults in China and to assess the potential for advancing healthy and active aging. Method: Data of 13,739 older adults aged 50 years and older from the China Health and Retirement Longitudinal Study in 2011 were analyzed. Life expectancy in good per ceived health, chronic-disease-free life expectancy, active life expectancy, and severe impairment-free life expectancy were calculated using Sullivan's method. Results: At age 50 years, older adults had a life expectancy in good perceived health of 7.0 and 6.7 years in men and women, respectively. They would remain chronic-disease-free for 8.4 and 8.6 years, without activity limitation for 23.6 and 26.0 years, and severe impairment-free for 21.4 and 24.2 years. Discussion: The world's largest aging population was spending a substantial proportion of remaining life years in suboptimal health and well-being, while remaining largely independent in basic self-care without severe impairments.Link_to_subscribed_fulltex