Depression and increased risk of Alzheimer’s dementia: Longitudinal analyses of modifiable risk and sex‐related factors
Bibliographic record
Abstract
Abstract Background Older adults with depression are at increased risk of Alzheimer’s dementia (AD). Most adults with AD are women. Women have two‐fold lifetime risk of depression. It is not known how sex influences the risk of depression upon AD. Method We used the longitudinal case series dataset from National Alzheimer’s Coordinating Center for analysis. Older adults (age 50+) with normal cognition, who visited memory clinics across the United States from September/2005 to December/2019, were followed from initial visit until first diagnosis of AD or loss to follow up. Multivariable survival analyses were conducted to determine if 1) recent and remote depression were independently predictive of AD, 2) this risk differed between the sexes, and 3) sex modifies this risk. Result 652 of 10,739 enrolled subjects developed AD over a median follow‐up of 55.3 months. Only recently active depression (within the last 2 years) was associated with increased risk of AD (HR=2.0; 95%CI, 1.5‐2.6) independently of other significant risk factors. After stratification by sex, recent depression was an independent predictor of AD in females (HR=2.3; 95%CI, 1.7‐3.1) but not in males (HR= 1.2; 95%CI, 0.7‐2.1). No interaction between recent depression and sex in predicting the risk of AD was observed (HR=1.5; 95%CI, 0.8‐2.8). Conclusion Only recent history of depression was associated with higher risk of AD. This risk was significant only in women. Future analyses should determine if current findings extend to other populations and may be explained by variable distribution of neurobiological or other modifiable risk factors between the sexes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".