Predictors and risk factors for suicide in late-life depression: a systematic review and meta-analysis
Bibliographic record
Abstract
Background The prevalence of late-life depression (LLD) is high, and its most dangerous, serious, and fatal comorbidity is suicide. Therefore, the present study systematically investigates the risk factors for suicide in individuals with LLD, offering empirical support for the development of preventive interventions against suicidal behavior. Methods PubMed, Web of Science, the Cochrane Library, PsycInfo, CNKI, Wan Fang Data, VIP, and CBM databases were searched from the inception of each database to February 2025 to identify observational studies of risk factors for suicide in LLD patients. The Newcastle–Ottawa Scale (NOS) and the Agency for Healthcare Research and Quality (AHRQ) were used to ensure study quality. Stata 18.0 software was used to perform a meta-analysis and sensitivity analysis to compute the pooled odds ratio. Results A total of 12 studies (eight case–control, two cross-sectional, and two longitudinal studies), with a quality level of medium or above, were included in the analysis. Depression severity (OR = 3.485, 95% CI: 1.385 to 8.769, P = 0.008) was identified as a significant risk factor for suicide in LLD. The age of onset (OR = 0.969, 95% CI: 0.905 to 1.039, P = 0.378) was not statistically significant for the risk of suicide in LLD. The descriptive analysis revealed that suicidal ideation, educational level, N3 sleep duration, odor identification dysfunction, alcohol drinking history, cognitive function, history of major trauma, history of suicide attempts, and high-density lipoprotein were associated with an increased suicide risk in LLD. Conclusion Our meta-analysis has revealed a variety of factors influencing suicide risk in LLD patients. Clinical staff should strengthen the assessment and screening of risk factors and take timely intervention and targeted treatment to reduce the risk of suicide in LLD. Systematic review registration https://www.crd.york.ac.uk/prospero/ , identifier CRD420251040029.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.035 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".