Abstract WMP19: A Brain Care Score for Risk of Late-Life Depression: Data From the UK Biobank Cohort
Bibliographic record
Abstract
Introduction: The 21-point Brain Care Score (BCS), developed via a modified Delphi process with practitioners and patients, is a novel instrument designed to motivate behavioral and lifestyle changes, ultimately aiming to decrease incidence of dementia and stroke (Fig 1). Whether or not BCS components are associated with longitudinal changes in mood disorders is not clear. For this study, we tested the hypothesis that the BCS also significantly correlates to late-life depression incidence in the UK Biobank (UKB). Design / Methods: The BCS was derived from UKB participants (using both the hospital and general practitioners cohort) aged 40-69 years, at baseline (2006-2010). After excluding patients with prevalent psychiatric disorders, we performed multivariable Cox proportional hazard regression models between the BCS and risk of incident late-life depression, adjusting for sex and stratified by age groups (<50, 50-59, >59 years). Results: The total BCS (median: 12; IQR:11-14) was derived for 416,370/502,408 (83%) UKB participants with complete data (mean age: 57; females: 54%). After exclusion of 50,395 participants who had mood or psychiatric disorders other than depression, a total of 365,975 participants were included in our analysis. In total, 6,628 incident cases of late-life depression were documented during the median follow-up period of 13 years. Each five-point increase in BCS was associated with a 59% (HR: 0.41, 95% CI: -0.03-0.85) decreased incidence of late-life depression among UKB participants aged <50, 35% (HR: 0.65, 95% CI: 0.57-0.74) among those aged 50-59; and 28% (HR: 0.72, 95% CI: 0.65-0.79) lower risk among those aged >59). Conclusions: In addition to its associations with dementia and stroke incidence, the BCS strongly correlates with late-life depression incidence in the UK Biobank. Additional research is needed to understand the association between BCS elements and late life depression in additional, diverse cohorts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".