Using Propensity Score Analysis to Compare Major Complications between DIEP and Free Muscle-Sparing TRAM Flap Breast Reconstructions
Bibliographic record
Abstract
BACKGROUND: Previous studies comparing muscle-sparing transverse rectus abdominis myocutaneous (TRAM) versus deep inferior epigastric artery perforator (DIEP) free flaps have not considered procedure selection bias. Propensity score analysis provides a statistical approach to consider preoperative factors in flap selection, and was used to compare major complications (breast and abdominal) between these microsurgical breast reconstruction (free muscle-sparing TRAM versus DIEP). METHODS: This study evaluated major breast and abdominal complications in 292 consecutive patients (428 free abdominal flaps). Propensity scores were calculated for patient differences affecting flap selection (DIEP versus free muscle-sparing TRAM). Multivariate logistic models using selected covariates separately analyzed breast and abdominal complications between flap methods. RESULTS: There were 83 major complications (28 percent): breast, 20 percent; abdomen, 8 percent. Using propensity scores, the adjusted odds of abdominal complications were significantly higher in free muscle-sparing TRAM than in DIEP flaps (OR, 2.73; 95 percent CI, 1.01 to 7.07). With prior chemotherapy, body mass index significantly increased abdominal complications (OR, 1.16; 95 percent CI, 1.01 to 1.34). Using propensity scores, there was no significant association between reconstruction method and breast complications; diabetics had significantly increased breast complications (OR, 4.19; 95 percent CI, 1.14 to 15.98). Previous abdominal operations (OR, 1.77; 95 percent CI, 0.96 to 3.30) and immediate reconstruction (OR, 1.86; 95 percent CI, 0.94 to 3.71) approached significance. CONCLUSIONS: Propensity score analysis indicated significantly higher abdominal complications in free muscle-sparing TRAM compared with DIEP flaps. This study highlights the importance of separately evaluating recipient breast and donor abdominal complications and use of propensity scores to minimize procedure selection bias. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, 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 | 0.015 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".