Depression, depressive symptoms, and rate of hippocampal atrophy in a longitudinal cohort of older men and women
Bibliographic record
Abstract
BACKGROUND: Several studies have reported smaller hippocampal volume (HcV) in depression patients; however, the temporality of the association remains unknown. One proposed hypothesis is that depression may cause HcV loss. This study evaluates whether previous depression and recent depressive symptoms are associated with HcV and HcV loss. METHOD: We used a prospective cohort of older adults (n = 1328; age = 65-80 years) with two cerebral magnetic resonance imaging examinations at baseline and 4-year follow-up. Using multivariable linear regression models, we estimated, in stratified analyses by gender, the association between indicators of history of depression and its severity (age at onset, recurrence, hospitalization for depression), proximal depressive symptoms [Center for Epidemiologic Studies-Depression (CES-D) scale], baseline antidepressant use, and the outcomes: baseline HcV and annual percentage change in HcV. RESULTS: At baseline, women with more depressive symptoms had smaller HcV [-0.05 cm3, 95% confidence interval (CI) -0.1 to -0.01 cm3 per 10-unit increase in CES-D scores]. History of depression was associated with a 0.2% faster annual HcV loss in women (95% CI 0.01-0.36%). More baseline depressive symptoms and worsening of these symptoms were also associated with accelerated HcV loss in women. No associations were observed in men. Treatment for depression was associated with slower HcV loss in women and men. CONCLUSIONS: While only concomitant depressive symptoms were associated with HcV, both previous depression and more proximal depressive symptoms were associated with faster HcV loss in women.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".