Visit-To-Visit Blood Pressure Variability and Subthreshold Depressive Symptoms in Older Adults
Bibliographic record
Abstract
OBJECTIVES: Depression is related to increased risk for dementia, possibly through links with cerebrovascular disease. Blood pressure variability is an emerging risk factor for cerebrovascular disease and dementia, but relationships with affective symptoms remain understudied. DESIGN: Retrospective analysis of prospective cohort study. SETTING: Alzheimer's Disease Neuroimaging Initiative. PARTICIPANTS: 505 older adults without history of dementia or recent depression underwent three to four blood pressure measurements over 12 months and completed a self-report measure of depressive symptoms (Geriatric Depression Scale - 15 Item) at study baseline and 24-months follow-up. MEASUREMENTS: Blood pressure variability was calculated as variability independent of mean and maximum minus minimum. Regression models investigated relationships between blood pressure variability and severity of self-reported depressive symptoms at 24-months follow-up after controlling for several variables, including average blood pressure, antihypertensive use, antidepressant use, and baseline depressive symptom severity. RESULTS: Elevated diastolic blood pressure variability was related to greater total depressive symptom score at follow-up (ß = .16 [95% CI 0.02, .30]; p = 0.03), with specific contribution from increased severity of symptoms of dysphoria (odds ratio = 1.35 [95% CI 1.07, 1.75]; p = 0.02). Blood pressure variability was not significantly related to other symptom subscales, including those reflecting life satisfaction or withdrawal. CONCLUSIONS: Findings suggest that elevated diastolic blood pressure variability is related to subthreshold depressive symptomatology in older adults without history of dementia or recent depression, independent of average blood pressure. Blood pressure variability may be an understudied vascular risk factor linked with depression and cognitive impairment, with potential therapeutic implications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".