Early Postoperative Complications From National Surgical Quality Improvement Program
Bibliographic record
Abstract
BACKGROUND: Despite the recent surge in rates of immediate breast reconstruction, there is a paucity of large multicenter studies to compare differences in morbidity after immediate versus delayed breast reconstruction. This study used the National Surgical Quality Improvement Program (NSQIP) to study the association between timing of breast reconstruction and complication rates, stratified by reconstructive modality. STUDY DESIGN: The NSQIP database was used to identify breast reconstructions from 2005 to 2012. Rates of major complications were compared by timing within each reconstructive modality (implant vs autologous). Cohort differences in baseline characteristics and variables associated with increased complication rates were identified in bivariate analyses. A multivariable model was created to compare the association between the timing of reconstruction and major complications. RESULTS: Of 24,506 postmastectomy reconstructions, 85.8% were immediate, 14.2% were delayed, 84% were implant, and 16% were autologous reconstructions. Overall, 10.0% of patients suffered a major complication. After stratification, only implant reconstructions showed a statistically higher complication rate with immediate (8.8%) reconstruction compared with delayed (5.3%) (odds ratio, 1.7, P < 0.01). There was no significant difference in complication rates between autologous immediate (18.4%) or delayed (19.0%) reconstructions. After controlling for baseline cohort differences and other risk factors, immediate reconstruction remained as an independent significant predictor of major complications in implant reconstructions (odds ratio, 1.8, P < 0.01). CONCLUSIONS: Immediate rather than delayed breast reconstruction is associated with a significantly higher rate of major complications in implant reconstruction but not in autologous reconstruction. It is important to include these findings in the routine preoperative surgeon-patient discussion of reconstructive options.
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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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".