Trends in postcoronary artery bypass graft sternal wound dehiscence in a provincial population
Bibliographic record
Abstract
C oronary artery bypass grafting (CABG) is a common procedure for the treatment of coronary artery disease.Over a five-year period, 774,881 isolated CABG procedures were recorded in the Society of Thoracic Surgeons National Audit Cardiac Surgery Database in the United States (1).Sternal wound dehiscence following mid-line sternotomy approach for CABG can result in significant morbidity and mortality (5% to 20%) (2).Despite significant sequelae from developing wound dehiscence, this complication is relatively uncommon, with incidence commonly reported to be between 0.4% and 4% (1,(3)(4)(5)(6)(7)(8)(9)(10)(11)(12).As described by Pairolero and Arnold (13), sternal wound dehiscence can be classified as type I (postoperative days 1 to 3), type II (within the first two to three weeks postoperatively) and type III (one year to several years postoperatively).Type I infections are generally superficial in nature, with the possibility of progressing to type II infections.Type II infections generally require irrigation and debridement, serial dressing changes, and local or regional flap closure.It is inferred that additional procedures such as these result in prolonged length of stay, increase risk to the patient and increased use of hospital resources.Understanding the incidence of sternal wound dehiscence in a given patient population is important for quality control and resource planning.The patient population undergoing CABG appears to be changing, as evidenced by long-term studies demonstrating that CABG benefits individuals with certain comorbid conditions (such as diabetes and renal failure) compared with angioplasty (14-17).It is believed this has an impact on management protocols -and, therefore, the incidence of sternal wound dehiscence -because individuals undergoing CABG today have proportionately more comorbid conditions than previously studied cohorts.original arTicle
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".