Mortality After the First Diagnosis of Schizophrenia-Spectrum Disorders: A Population-based Retrospective Cohort Study
Bibliographic record
Abstract
There is emerging evidence of high mortality rates after the first diagnosis of psychotic disorder. The objective of this study was to estimate the standardized mortality ratio (SMR) in a population-based cohort of individuals with a first diagnosis of schizophrenia-spectrum psychotic disorder (SSD). The cohort included a population-based sample of individuals with a first diagnosis of SSD based on the first diagnosis occurring during hospitalization or in an outpatient setting between 2007 and 2010 in Ontario, Canada. All patients were followed for 5 years after the first diagnosis. The primary outcome was SMR, including all-cause, suicide-related, accidental, and other causes. Between 2007 and 2010, there were 2382 patients in the hospitalization cohort and 11 003 patients in the outpatient cohort. Over the 5-year observation period, 97 (4.1%) of the hospitalization cohort and 292 (2.7%) of the outpatient cohort died, resulting in an SMR of 13.6 and 9.1, respectively. In both cohorts, suicide was the most common cause of death. Approximately 1 in 25 patients with a first diagnosis of SSD during hospitalization, and 1 in 40 patients with a first diagnosis of SSD in an outpatient setting, died within 5 years of first diagnosis in Ontario, Canada. This mortality rate is between 9 and 13 times higher than would be expected in the age-matched general population. Based on these data, timely access to services should be a public health priority to reduce mortality following a first diagnosis of an SSD.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".