Long-term mortality and associated factors in first episode psychosis: a 25-year follow-up study
Bibliographic record
Abstract
BACKGROUND: Individuals with first-episode psychosis (FEP) face markedly increased excess mortality, yet the long-term trends and key contributing factors remain insufficiently characterized. This study aimed to examine long-term mortality patterns, standardized mortality ratios (SMRs), and associated factors in a FEP cohort. METHODS: This population-based cohort study included 1,389 individuals diagnosed with FEP, followed for up to 25 years. Mortality outcomes were obtained from Hong Kong's centralized hospital database (CMS) and coroner's court reports, with SMRs calculated. Baseline sociodemographic and clinical, as well as long-term treatment-related factors of all-cause, natural, and unnatural mortality were analyzed. RESULTS: Among 1,389 participants, 137 deaths (9.86%) occurred during the follow-up period with the overall SMR of 6.56 (95% CI, 5.50-7.71). The cumulative incidence rate of unnatural mortality increased sharply over the first 10 years and that of the natural cause of death started to increase after the first decade of the illness. Male gender and poorer social functioning were associated with increased all-cause mortality risk, while male gender, lower education, and baseline hospitalization raised unnatural mortality risk. Greater monthly antipsychotic variability during the first 10 years increased all-cause mortality risk in the period after the initial 10 years. CONCLUSIONS: This 25-year follow-up study of FEP highlighted the changes in the long-term mortality pattern of FEP and thus the phase-specific needs of individuals with FEP. Therefore, it is important to integrate physical care into mental health services, as well as stage-specific and individualized care for patients with psychotic disorders to reduce long-term excess mortality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".