Factors associated with emergency free flap reoperation in postmastectomy breast reconstruction: A population-based cohort study
Bibliographic record
Abstract
BACKGROUND: Reoperation shortly after free flap breast reconstruction is a substantial event with impacts on patients and healthcare utilization. The objective of the study was to evaluate the factors associated with the return to the operating room in free flap breast reconstruction patients. METHODS: This retrospective cohort study included patients who underwent postmastectomy free flap breast reconstruction from 2005 to 2020 in Ontario, Canada. Patient records were identified from a prospectively maintained administrative database stored at the Institute for Clinical Evaluation Sciences. The outcome of interest was emergency return to the operating room within a week of primary autologous breast reconstruction. Univariate and multivariable logistic regression models were used to assess independent factors associated with emergency reoperation. RESULTS: We evaluated 2290 patients who underwent autologous breast reconstruction with free tissue transfer. Overall, 167 patients (7.29%) underwent emergency surgery within 7 days. Most reoperations (86%) occurred within the first 3 days. The odds of reoperation were higher for patients from the lower-income quintiles (quintile 5 vs. quintile 1: adjusted odds ratio [aOR] 2.14, 95% confidence interval [CI] 1.27-3.60, p = 0.004) and in nonteaching hospitals (aOR 1.73, 95% CI 1.09-2.72, p = 0.019). Age, Charlson Comorbidity Index, diabetes, reconstruction timing, geographical location, and rurality were not associated with free flap takeback. CONCLUSION: In a universal health care system, patients from the lowest income quintile and patients who underwent reconstruction at nonteaching hospitals were at increased odds of reoperation. Increased efforts are needed to mitigate the disparities and improve outcomes across all demographics.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".