Clinical and Economic Impact of an Enhanced Recovery Pathway for Open and Laparoscopic Rectal Surgery
Bibliographic record
Abstract
BACKGROUND: The short-term benefits of laparoscopy for rectal surgery are equivocal. The objective of this study was to determine the clinical and economic impact of an enhanced recovery pathway (ERP) for laparoscopic and open rectal surgery. MATERIALS AND METHODS: All patients who underwent elective rectal resection with primary anastomosis between January 2009 and March 2012 at two tertiary-care, university-affiliated institutions were identified. Patients who met inclusion criteria were divided into four groups, according to surgical approach (laparoscopic [lap] or open) and perioperative management (ERP or conventional care [CC]). Length of stay (LOS), postoperative complications, and hospital costs were compared. RESULTS: A total of 381 patients were included in the analysis (201 open-CC, 34 lap-CC, 38 open-ERP, and 108 lap-ERP). Patients were mostly similar at baseline. ERPs significantly reduced median LOS after both open cases (open-CC 10 days versus open-ERP 7.5 days, P = .003) and laparoscopic cases (lap-CC 5 days versus lap-ERP 4.5 days, P = .046). ERPs also reduced variability in LOS compared with CC. There was no difference in postoperative complications with the use of ERPs (open-CC 51% versus open-ERP 50%, P = .419; lap-CC 32% versus lap-ERP 36%, P = .689). On multivariate analysis, both ERP (-3.6 days [95% confidence interval, CI -6.0 to -1.3]) and laparoscopy (-3.6 days [95% CI -5.9 to -1.0]) were independently associated with decreased LOS. Overall costs were only lower when lap-ERP was compared with open-CC (mean difference -2420 CAN$ [95% CI -5628 to -786]). CONCLUSIONS: ERPs reduced LOS after rectal resections, and the combination of laparoscopy and ERPs significantly reduced overall costs compared to when neither strategy was used.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".