PD51-11 REPORTING RADICAL CYSTECTOMY OUTCOMES FOLLOWING IMPLEMENTATION OF ENHANCED RECOVERY AFTER SURGERY (ERAS) PROTOCOLS
Bibliographic record
Abstract
INTRODUCTION AND OBJECTIVE: Enhanced Recovery After Surgery (ERAS) is a perioperative approach to managing surgical patients. The impact of ERAS on radical cystectomy (RC) outcomes remains under-studied. Our goal was to systematically review the literature regarding ERAS protocols and RC outcomes. The primary outcome was hospital length of stay (LOS). METHODS: A systematic review was performed using Ovid and Medline for articles published from 1970 through 2018. Individual patient data (IPD) was requested from selected papers and meta-analysis undertaken. RESULTS: Overall, 4,197 articles were retrieved and 22 (0.5%) studies, reporting 3,847 patients, were selected for review. Of the 18 observational studies which met inclusion criteria, length of stay followed by 30 and 90-d complications were the most studied primary endpoints following implementation of ERAS protocols. Only one RC study to date has assessed the impact of all 26 ERAS items on RC outcomes. ERAS use was associated with reduced morbidity, quicker bowel recovery, and shorter LOS. ERAS resulted in no increased risk of mortality. IPD were obtained for 11 studies from 6 centers reporting 2,077 patients. In multivariate analysis, ERAS factors associated with an increased LOS included use of bowel preparation (Odds Ratio (OR): 5.11; 95% Confidence Interval (CI), 2.18-11.97, p<0.001), and use of nasogastric tube (NGT) postoperatively (OR: 3.19; 1.45-7.03, p=0.004), while the use of rectus sheath/local anesthesia blocks vs. spinal/epidural was associated with a shorter hospital stay (OR: 0.56; 0.35-0.91, p=0.020). CONCLUSIONS: Implementation of ERAS protocols was associated with reduced LOS and post-operative complication rate with no increased risk of mortality. Elimination of bowel preparation and NGT, and use of regional anesthesia were significantly associated with decreased LOS. These findings reflect different components of recovery which ERAS can optimize and further support documentation of use of ERAS components when reporting RC outcomes. Source of Funding: This study was conducted with the support of a Department of Defense Peer Reviewed Cancer Research Program (PRCRP) Career Development Award (W81XWH1710576) and the Herzog Foundation (SBW).
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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 | 0.025 | 0.109 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.013 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".