Years of potential life lost and life expectancy in schizophrenia: a systematic review and meta-analysis
Bibliographic record
Abstract
Background Several studies and meta-analyses have shown that mortality in people with schizophrenia is higher than that in the general population but have used relative measures, such as standardised mortality ratios. We did a systematic review and meta-analysis to estimate years of potential life lost and life expectancy in schizophrenia, which are more direct, absolute measures of increased mortality. Methods We searched MEDLINE, PsycINFO, Embase, Cinahl, and Web of Science for published studies on years of potential life lost and life expectancy in schizophrenia. Data from individual studies were combined in meta-analyses as weighted averages. We did subgroup analyses for sex, geographical region, timing of publication, and risk of bias (estimated with the Newcastle-Ottawa Scale). Findings We identified 11 studies in 13 publications covering all inhabited continents except South America (Africa n=1, Asia n=1, Australia n=1, Europe n=7, and North America n=3) that involved up to 247 603 patients. Schizophrenia was associated with a weighted average of 14·5 years of potential life lost (95% CI 11·2–17·8), and was higher for men than women (15·9, 13·8–18·0 vs 13·6, 11·4–15·8). Loss was least in the Asian study and greatest in Africa. The overall weighted average life expectancy was 64·7 years (95% CI 61·1–71·3), and was lower for men than women (59·9 years, 95% CI 55·5–64·3 vs 67·6 years, 63·1–72·1). Life expectancy was lowest in Asia and Africa. Timing of publication and risk of bias had little effect on results. Interpretation The effects of schizophrenia on years potential life lost and life expectancy seem to be substantial and not to have lessened over time. Development and implementation of interventions and initiatives to reduce this mortality gap are urgently needed. Funding None.
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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 | 0.016 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.045 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".