Trends in postcoronary artery bypass graft sternal wound dehiscence in a provincial population
Bibliographic record
Abstract
Background It appears that the medical profile of patients undergoing coronary artery bypass graft (CABG) surgery has changed. The impact of this demographic shift on CABG outcomes, such as sternal wound dehiscence, is unclear. Objectives To quantify the incidence and trends of sternal wound dehiscence, quantify the demographic shift of those undergoing CABG and identify patient factors predictive of disease. Methods A prospective analysis was performed on a historical cohort of consecutive patients who underwent CABG (without valve replacement) in Alberta between April 1, 2002 and November 30, 2009. The incidence and trends of sternal wound dehiscence were determined. In addition, the trend of the mean Charlson index score and European System for Cardiac Operative Risk Evaluation (EuroSCORE) (capturing patient comorbidities) was analyzed. Univariable analysis and multivariable models were performed to determine factors predictive of wound dehiscence. Results A total of 5815 patients underwent CABG during the study period. The incidence proportion of sternal wound dehiscence in Alberta was 1.86% and the incidence rate was 1.98 cases per 100 person-years. Although both the EuroSCORE and Charlson scores significantly increased over the study period, the incidence of sternal wound dehiscence did not change significantly. Factors predictive of sternal wound dehiscence were diabetes (OR 2.97 [95% CI 1.73 to 5.10]), obesity (OR 1.55 [95% CI 1.05 to 2.27]) and female sex (OR 1.90 [95% CI 1.26 to 2.87]). Conclusions The incidence proportion of sternal wound dehiscence in Alberta was comparable with the incidence previously published in the literature. While patients undergoing CABG had worsening medical profiles, the incidence of sternal wound dehiscence did not appear to be increasing significantly.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".