Epidural Nerve Blocks Increase Intraoperative Vasopressor Consumption and Delay Surgical Start Time in Deep Inferior Epigastric Perforator Free Flap Breast Reconstruction
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Bibliographic record
Abstract
Background: Epidural nerve blocks (EA) have been widely used in abdominal and thoracic surgery as an adjunct to general anesthesia (GA). The role for EA in microsurgical free flap breast reconstruction remains unclear with concerns regarding its impact on flap survival and operating room efficiency. The purpose of this study was to examine the effectiveness of epidural blocks in patients undergoing deep inferior epigastric perforator (DIEP) flap breast reconstruction. Methods: A retrospective analysis of patients undergoing DIEP breast reconstruction under GA alone was compared with those receiving EA/GA. Electronic records were analyzed for patient demographics, intraoperative data, and postoperative outcomes. The primary outcome was 48-hour narcotic usage and secondary outcomes were intraoperative vasopressor consumption, surgical delay, and safety profile. Results: Sixty-one patients underwent DIEP reconstruction, 46 (75%) underwent EA/GA and 15 (25%) underwent GA alone. Epidural blocks were associated with a significant delay in operating room start time (67.8 min versus 45.6 min; P = 0.0004.) Patients in the EA/GA group also had a significant increase in vasopressor use (n = 38 versus n = 8; P = 0.037); however, there was no difference in flap complication rate [1 (2%) versus 2 (13%); P = 0.15]. Postoperatively, patients who received an epidural block had a reduced average pain score (1.1 versus 2.2; P = 0.0235), but there was no difference in 48-hour narcotic usage. Conclusions: Although epidural blocks reduce postoperative pain following DIEP flap breast reconstruction, they increase intraoperative vasopressor use and delay the start time of the case. Further studies are required to elucidate whether the benefits of improved pain control outweigh the potential risk for increased surgical complications and increased health care costs.
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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 | 0.000 | 0.001 |
| 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) | 0.003 | 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 it