Predictors of prolonged hospitalization in modified sternoplasty following postoperative mediastinitis
Bibliographic record
Abstract
BACKGROUND AND AIM: Deep sternal wound infection (DSWI) is a serious complication following cardiac surgery, and demands early intervention as any delay in diagnosis and management may lead to increased morbidity and mortality. DSWI is associated with increased length of hospitalization (LOH) and economic burden in this patient population. The aim of this study was to determine predictors for increased length of hospitalization in patients who underwent the Modified Sternoplasty technique for deep sternal wound infection following cardiac surgery. METHODS: A retrospective study was undertaken on data from patients who underwent the Modified Sternoplasty surgery for DSWI between September 2010 and January 2020. Patients' characteristics that were recorded included medical history, type of the original heart surgery, length of hospitalizations, and risk factors including hyperlipidemia, diabetes mellitus and hypertension, and morbidity and mortality rates following the Modified Sternoplasty. RESULTS: Sixty-eight patients underwent the Modified Sternoplasty surgery with an average length of hospitalization of 24.63 + 22.09 days. Multivariable analysis showed that only gender was considered a predictor of length of hospitalization when controlling for comorbidities, with average length of hospitalization longer for women than men (35.4 vs. 20.9, p = .04). CONCLUSION: The Modified Sternoplasty surgery is a novel surgical technique for managing DSWI complicated by sternal dehiscence with exposed heart and great vessels. Female gender was associated with increased length of hospitalization in our patient cohort, with average length of hospitalization for women almost twice that of males.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 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".