Effects of Nitroglycerin Ointment on Mastectomy Flap Necrosis in Immediate Breast Reconstruction
Bibliographic record
Abstract
BACKGROUND: Mastectomy flap necrosis is a common complication of immediate breast reconstruction that impacts recovery time and reconstructive success. Nitroglycerin ointment is a topical vasodilator that has been shown to improve skin flap survival in an animal model. The objective of this study was to evaluate whether the application of nitroglycerin ointment to the breast skin after mastectomy and immediate reconstruction causes a decrease in the rate of mastectomy flap necrosis compared with placebo. METHODS: This study was conducted as a randomized controlled trial and included patients aged 21 to 69 years undergoing mastectomy and immediate breast reconstruction at the University of British Columbia-affiliated hospitals (Vancouver, British Columbia, Canada). Patients with a medical history that precluded the administration of nitroglycerin were excluded from the study. The target sample size was 400 patients. Nitroglycerin ointment (45 mg) or a placebo was applied to the mastectomy skin at the time of surgical dressing. RESULTS: The trial was stopped at the first interim analysis after 165 patients had been randomized (85 to the treatment group and 80 to the placebo group). Mastectomy flap necrosis developed in 27 patients (33.8 percent) receiving placebo and in 13 patients (15.3 percent) receiving nitroglycerin ointment; the between-group difference was 18.5 percent (p = 0.006; 95 percent CI, 5.3 to 31.0 percent). Postoperative complications were similar in both groups [nitroglycerin, 22.4 percent (19 of 85); placebo, 28.8 percent (23 of 80)]. CONCLUSIONS: In patients undergoing mastectomy and immediate reconstruction, there was a marked reduction in mastectomy flap necrosis in patients who received nitroglycerin ointment. Nitroglycerin ointment application is a simple, safe, and effective way to help prevent mastectomy flap necrosis. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, I.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".