Cardiovascular hazards of insufficient treatment of depression among patients with known cardiovascular disease: a propensity score adjusted analysis
Bibliographic record
Abstract
Aims: The association between depression care adequacy and the risk of subsequent adverse cardiovascular disease (CVD) outcomes among patients with a previous diagnosis of myocardial infarction (MI) or stroke is not well defined. Methods and results: This retrospective cohort study used commercial claims data (2010-2015) and included adults with newly diagnosed and treated major depressive disorder (MDD) following an initial MI or stroke diagnosis. Depression care adequacy was assessed during the 3-month period following the MDD diagnosis index date using two measures: antidepressant dosage adequacy and duration adequacy. Cox models adjusted for the propensity of receiving adequate depression care were used to compare the risk of a composite CVD outcome (MI, stroke, congestive heart failure, and angina) as well as each individual CVD event between patients receiving adequate vs. inadequate depression care. A total of 1568 patients were included in the final cohort. Of these, 937 (59.8%) were categorized as receiving inadequate depression care based on at least one of the two treatment adequacy criteria. Propensity score adjusted Cox models showed that depression care inadequacy was associated with a significantly higher risk of the composite CVD endpoint [hazard ratio (HR) 1.20, 95% confidence interval (CI) 1.04-1.39], stroke (HR 1.20, 95% CI 1.02-1.42), and angina (HR 1.95, 95% CI 1.21-3.16) with no significant interaction based on cohort included (MI vs. stroke) or the definition of inadequate depression (dose vs. duration inadequacy) (Pinteraction > 0.05). Conclusion: Inadequate MDD care was associated with a higher risk of adverse CVD events. These findings reveal a significant unmet clinical need in patients with post-MI or post-stroke MDD that may impact CVD outcomes.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".