Synergistic Interaction Increases Complication Rates following Microvascular Breast Reconstruction
Bibliographic record
Abstract
BACKGROUND: Microvascular breast reconstruction is a complex procedure that can be associated with high complication rates. Although a number of individual predictors of perioperative complications have been identified, few studies have explored interaction between risk factors. Understanding the synergistic effects of multiple risk factors is central to accurate and personalized preoperative risk prediction. METHODS: The authors conducted a retrospective cohort study of patients who underwent microvascular breast reconstruction at their institution between 2009 and 2017. All intraoperative and postoperative complications were recorded. A multivariable logistic regression exploratory model identified independent predictors of complications. Interactions between individual variables were then assessed using the relative excess risk index (RERI) and the synergy index (SI). RESULTS: Nine hundred twelve patients were included in the study and 26.1 percent experienced at least one perioperative complication. Obesity (OR, 1.54; p = 0.009), immediate reconstruction (OR, 1.49; p = 0.028), and comorbidities (OR, 1.43; p = 0.033) were identified as independent predictors of complications. Obesity and comorbidities had significant synergistic interactions with immediate reconstruction (RERI, 0.86; SI, 2.35; p = 0.0002; and RERI, 0.54; SI, 1.78; p = 0.001), bilateral reconstruction (RERI, 0.12; SI, 1.15; p = 0.002; and RERI, 0.59; SI, 3.16; p = 0.005), and previous radiotherapy (RERI, 0.62; SI, 4.43; p = 0.01; and RERI, 0.11; SI, 1.23; p = 0.040). Patients undergoing immediate breast reconstruction who were both obese and smokers had a 12-fold increase in complication rates (OR, 12.68; 95 percent CI, 1.36 to 118.46; p = 0.026) with a very strong synergistic interaction between variables (RERI, 10.55; SI, 10.33). CONCLUSION: Patient- and treatment-related variables interact in a synergistic manner to increase the risk of complications following microvascular breast reconstruction. CLINICAL QUESTION/LEVEL OF EVIDENCE: Risk, III.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".