An Enhanced Recovery after Surgery Pathway for Microvascular Breast Reconstruction Is Safe and Effective
Bibliographic record
Abstract
Background: The aim of this study was to develop, implement, and evaluate a standardized perioperative enhanced recovery after surgery (ERAS) clinical care pathway in microsurgical abdominal-based breast reconstruction. Methods: Development of a clinical care pathway was informed by the latest ERAS guideline for breast reconstruction. Key features included shortened preoperative fasting, judicious fluids, multimodal analgesics, early oral nutrition, early Foley catheter removal, and early ambulation. There were 3 groups of women in this cohort study: (1) traditional historical control; (2) transition group with partial implementation; and (3) ERAS. Narcotic use, patient-reported pain scores, antiemetic use, time to regular diet, time to first walk, hospital length of stay, and 30-day postoperative complications were compared between the groups. Results: After implementation of the pathway, the use of parenteral narcotics was reduced by 88% (traditional, 112 mg; transition, 58 mg; ERAS, 13 mg; P < 0.0001), with no consequent increase in patient-reported pain. Patients in the ERAS cohort used less antiemetics (7.0, 5.3, 2.2 doses, P < 0.0001), returned to normal diet 19 hours earlier (46, 39, 27 hours, P < 0.0001), and walked 25 hours sooner (75, 70, 50 hours, P < 0.0001). Overall, hospital length of stay was reduced by 2 days in the ERAS cohort (6.6, 5.6, 4.8 days, P < 0.0001), without an increase in rates of major complications (9.5%, 10.1%, 8.3%, P = 0.9). Conclusions: A clinical care pathway in microsurgical breast reconstruction using the ERAS Society guideline promotes successful early recovery.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".