The Temporal Relationship Between Depression Symptoms and Cognitive Functioning in Older Medical Patients--Prospective or Concurrent?
Bibliographic record
Abstract
BACKGROUND: Epidemiological studies remain inconclusive as to whether old age depression is an independent risk factor, a prodrome, or a clinical concomitant of cognitive impairment. The objective of this study, using repeated measures over a 12-month period, was to examine the short-term temporal relationship between depressive symptoms and cognitive impairment. METHODS: Two hundred eighty-one medical inpatients 65 years old or older were followed up with the Hamilton Depression Rating Scale (HDRS) and Mini-Mental State Examination (MMSE) at enrollment and 3, 6, and 12 months later. A repeated-measures mixed linear regression model was used to evaluate the association between HDRS scores and MMSE changes over time and to test competing hypotheses about their temporal sequence. RESULTS: After adjusting for age, cardiovascular risk, illness severity, baseline physical and cognitive function, and other covariates, a one-point increase in HDRS score (baseline mean +/- standard deviation: 14.4 +/- 7.4) was associated with a lower MMSE score (-0.03, 95% confidence interval, -0.07 to 0.00) at the same time points, but not with the MMSE at subsequent time points (all p values >.40). There were no statistically significant interactions detected between follow-up time and HDRS scores measured at baseline or during follow-up. These results were confirmed in alternative models using dynamic measures of both HDRS and MMSE changes over each successive follow-up interval. CONCLUSIONS: These findings suggest that the short-term relationship between depression symptoms and cognitive functioning may be concurrent or temporary, rather than prospective or protracted, consistent with the clinical concomitant hypothesis.
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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 | 0.003 | 0.011 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".