Hippocampal Atrophy and Subsequent Depressive Symptoms in Older Men and Women: Results From a 10-Year Prospective Cohort
Bibliographic record
Abstract
Several studies have reported smaller hippocampal volume in patients with depression. However, the temporality of the association is undetermined. One hypothesis is that hippocampal atrophy might be a susceptibility factor for depression. In the present study, we assessed whether hippocampal atrophy was associated with subsequent depressive symptoms in a cohort of older French adults (n = 1,309) who were 65-80 years of age and enrolled into the study in 1999-2001 in Dijon, France. Subjects were followed for more than 10 years. Participants underwent 2 cerebral magnetic resonance imaging scans, one at baseline and one at the 4-year follow-up. We used linear mixed models to estimate the associations of hippocampal atrophy with 1) the average depressive symptom scores over follow-up (using the Center for Epidemiologic Studies-Depression scale) measured biennially over the subsequent 6 years and 2) changes in symptom scores over follow-up. In women, a 2-standard-deviation increase in annual hippocampal atrophy was associated with a 1.67-point (95% confidence interval: 0.59, 2.77) increase in the average depressive symptom score over follow-up and with a 1.97-point (95% confidence interval: 0.68, 3.24) increase in scores over the 2 subsequent years but not with later changes in symptoms. No association was detected in men. Accounting for potential selective attrition (using inverse probability weights) did not alter results. Hippocampal atrophy was associated with more subsequent depressive symptoms and with shorter-term worsening of symptoms in women.
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".