Differential cognitive impairment in subjects with geriatric depression who will develop Alzheimer's disease and other dementias: a retrospective study
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to retrospectively differentiate the cognitive profile of subjects with geriatric depression who will later be diagnosed with Alzheimer's disease (AD) from those who will be diagnosed with other dementias, and subjects who will remain with no dementia. METHODS: Forty-four depressed patients admitted to a day hospital program for depression who participated in a historical cohort study were assessed after 7.5 years of follow-up. Fourteen of these subjects subsequently developed dementia: seven met the criteria for probable AD and seven met the criteria for dementias other than AD (Dementia-No-AD; D-NAD, such as dementia with Lewy bodies (DLB), vascular and mixed dementia). Thirty subjects remained without dementia (No Dementia, ND) at follow-up. The three groups were thus compared on their baseline cognitive performances on the six sections of the Mini-mental State Examination (MMSE) and on the five subscales of the Dementia Rating Scale (DRS). RESULTS: An analysis of variance (ANOVA) and post-hoc Student-Newman-Keuls analyses with an alpha of p < 0.05 revealed that the subjects who received a diagnosis of dementia at follow-up had previously had more impairment on tasks measuring attention and memory (DRS-MMSE) than those who did not develop dementia (AD = D-NAD < ND). Moreover, the future AD subjects could be differentiated on the basis of their difficulties on the MMSE-orientation subtest (AD < ND = D-NAD), whereas the future D-NAD subjects initially had more problems with executive functions (DRS) and MMSE-visuospatial abilities (D-NAD < AD = ND). CONCLUSION: The identification of early neuropsychological markers in elderly depressed patients highlights the need to evaluate this population broadly as soon as possible in the depression/dementia process in order to improve the prognosis.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".