Increasing the Time to Expander-Implant Exchange after Postmastectomy Radiation Therapy Reduces Expander-Implant Failure
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Bibliographic record
Abstract
BACKGROUND: Increased rates of complications can occur when postmastectomy radiation therapy is required after immediate expander-implant breast reconstruction. The sequence and timing of tissue expansion and implant exchange with regard to postmastectomy radiation therapy may impact complication rates. METHODS: A prospectively maintained database of patients undergoing mastectomy and immediate reconstruction was queried for patients who underwent postmastectomy radiation therapy. The authors' protocol is to complete tissue expansion before radiation, irradiate the fully inflated expander, and then perform expander-implant exchange. Starting in 2009, the authors refined their protocol by increasing the time interval between completion of radiation therapy and expander-implant exchange from 3 months to 6 months as a strategy to reduce surgical complications. For analysis, patients were divided into two cohorts based on whether expander-implant exchange was performed less than 6 months or more than 6 months after radiation. The primary outcome was expander-implant failure, defined as device removal without concurrent replacement. RESULTS: Eighty-eight patients met selection criteria; 49 (55.7 percent) had expander-implant exchange within 6 months of completing radiation therapy (mean, 3.4 months; range, 1.2 to 5.8 months), and the rest had at least a 6-month interval (mean, 8.6 months; range, 6.1 to 17.1 months). Risk factors for postoperative complications were equivalent between cohorts. Overall expander-implant failure was 15.9 percent; failure was significantly higher in the cohort with less than 6 months' time before exchange (22.4 percent versus 7.7 percent, p = 0.036). CONCLUSION: Delaying expander-implant exchange for at least 6 months after the completion of postmastectomy radiation therapy can significantly reduce expander-implant failure.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 it