Risk of Mortality Associated with Preexisting Chronic Diseases and Prior Year Diagnosis of a Mental Disorder in Survivors of a First Myocardial Infarction or Stroke
Bibliographic record
Abstract
Background: Chronic medical diseases and recurrent mental disorders are common and may lead to a negative prognosis in adults with cardiovascular diseases (CVDs). The impact of these overlapping morbidities is likely to be further increased in the critical years following a first acute CVD event such as a stroke or myocardial infarction (MI). Objectives: The objective of this study was to examine associations of preexisting chronic diseases and recent mental disorders with mortality in survivors of a first MI or stroke. Methods: Data from the 48,526 patients (59% men) aged ≥40 years with a first MI or stroke were extracted from the Quebec Integrated Chronic Disease Surveillance System. Cox regression models were used to assess the effect of preexisting cancer, renal disease, diabetes, chronic obstructive pulmonary disease (COPD), and recent mental disorders on the risk of recurrent fatal CVD events and all-cause mortality following the index MI or stroke. Results: An increased risk of CVD mortality was observed at 1, 3, and 4.5 years in women and men with coexisting mental disorders and at 4.5 years in those with chronic, preexisting renal disease. Inversely, cancer and COPD were associated with a lowered risk of CVD mortality during the study period. An increased risk of all-cause mortality at all time points was observed in adults with any of the assessed conditions. Conclusions: Adults with coexisting mental disorders are at increased risk of CVD mortality and all-cause mortality in the years following a first MI or stroke. This increased vulnerability is separate from the extra mortality attributable to preexisting chronic diseases.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".