Work stress and the risk of recurrent coronary heart disease events: A systematic review and meta-analysis
Bibliographic record
Abstract
Though much evidence indicates that work stress increases the risk of incident of coronary heart disease (CHD), little is known about the role of work stress in the development of recurrent CHD events. The objective of this study was to review and synthesize the existing epidemiological evidence on whether work stress increases the risk of recurrent CHD events in patients with the first CHD. A systematic literature search in the PubMed database (January 1990 - December 2013) for prospective studies was performed. Inclusion criteria included: peer-reviewed English papers with original data, studies with substantial follow-up (> 3 years), end points defined as cardiac death or nonfatal myocardial infarction, as well as work stress assessed with reliable and valid instruments. Meta-analysis using random-effects modeling was conducted in order to synthesize the observed effects across the studies. Five papers derived from 4 prospective studies conducted in Sweden and Canada were included in this systematic review. The measurement of work stress was based on the Demand- Control model (4 papers) or the Effort-Reward Imbalance model (1 paper). According to the estimation by meta-analysis based on 4 papers, a significant effect of work stress on the risk of recurrent CHD events (hazard ratio: 1.65, 95% confidence interval: 1.23-2.22) was observed. Our findings suggest that, in patients with the first CHD, work stress is associated with an increased relative risk of recurrent CHD events by 65%. Due to the limited literature, more well-designed prospective research is needed to examine this association, in particular, from other than western regions of the world.
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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 | 0.011 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.037 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".