Outcomes in the Management of Sternal Dehiscence by Plastic Surgery
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In Brief Purpose: Infection rates following median sternotomy vary between 0.2% and 10%. These cases are associated with morbidity and mortality rates between 10% and 25% and 5% and 20%, respectively. The purpose of this study was to evaluate patient outcomes following plastic surgery correction of sternotomy dehiscence (SD). Methods: All patients operated on for an SD following coronary artery bypass graft surgery (CABG), between 1995 and 2005, with 1 or more flaps, were included. Results: Eighty cases were identified over a 10-year period. The mean age was 64 (±9.1) years. Two or more procedures were required in 17.5% of patients, and the mortality rate within 30 days was 12.5%. Significant variability was revealed between the cumulative mortality rates of plastic surgeons, from 0.0% to 50.0%. Multiple associations were identified for poor outcome, including chronic renal insufficiency and early mortality, and obesity with risk of reintervention. Conclusion: Although patients who undergo surgical correction of a deep sternal infection usually tolerate their intervention well, the mortality within 30 days remains high. This study has identified several factors explaining morbidity and mortality in this patient population. A review of flap reconstructions of 80 post-sternotomy infections demonstrated the need for multiple procedures in 17.5% and a 30-day mortality rate of 12.5%. Obesity was a risk factor for reoperation, and chronic renal failure for mortality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it