Cardiovascular Disease in Patients With Schizophrenia in Saskatchewan, Canada
Bibliographic record
Abstract
BACKGROUND: Studies have shown that patients with schizophrenia have higher rates of cardiovascular disease and mortality compared with the general population. However, population-based data on the prevalence, incidence, and mortality of cardiovascular disease are needed. METHOD: In this retrospective cohort study, the Saskatchewan Health databases were searched for all patients diagnosed with schizophrenia (ICD-9 code 295) in 1994 or 1995. 3022 subjects were identified. For each subject, 4 age- and sex-matched comparison individuals were selected randomly among residents of the province who had no diagnosis of schizophrenia or any other mental disorders and who received no prescriptions for antipsychotic medications. Prevalence of cardiovascular morbidity during 1994 and 1995 and incidence of cardiovascular morbidity and mortality during the follow-up period of January 1996 through March 1999 were analyzed. RESULTS: Concerning prevalence of morbidity in schizophrenia patients, significantly increased risk-adjusted odds ratios were as follows: arrhythmia, 1.5 (95% CI = 1.2 to 1.8); syncope, 4.0 (95% CI = 2.0 to 7.9); heart failure, 1.7 (95% CI = 1.4 to 2.2); stroke, 2.1 (95% CI = 1.6 to 2.7); transient cerebral ischemia, 2.6 (95% CI = 1.7 to 3.7); and diabetes, 2.1 (95% CI = 1.8 to 2.4). Odds of acute myocardial infarction, ischemic heart disease, and ventricular arrhythmias were not significantly different from those for the comparison group. Concerning incidence of morbidity and mortality in the patients, adjusted relative risk was significantly increased for ventricular arrhythmia, 2.3 (95% CI = 1.2 to 4.3); heart failure, 1.6 (95% CI = 1.2 to 2.0); stroke, 1.5 (95% CI = 1.2 to 2.0); diabetes, 1.8 (95% CI = 1.2 to 2.6); all-cause mortality, 2.8 (95% CI = 2.3 to 3.4); and cardiovascular mortality, 2.2 (95% CI = 1.7 to 2.8). CONCLUSIONS: Persons with schizophrenia appear to be at greater risk for cardiovascular morbidity and mortality than those in the general population.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".