Effect of intraperitoneal local anesthesia on enhanced recovery outcomes after bariatric surgery: a randomized controlled pilot study
Bibliographic record
Abstract
BACKGROUND: Patients with extreme obesity are at high risk for adverse perioperative events, especially when opioid-centric analgesic protocols are used, and perioperative pain management interventions in bariatric surgery could improve safety, outcomes and satisfaction. We aimed to evaluate the impact of intraperitoneal local anesthesia (IPLA) on enhanced recovery after bariatric surgery (ERABS) outcomes. METHODS: We conducted a prospective double-blind randomized controlled pilot study in adherence to an a priori peer-reviewed protocol. Patients undergoing laparoscopic Roux-en-Y gastric bypass surgery (LRYGB) with an established ERABS protocol between July 2014 and February 2015 were randomly allocated to receive either IPLA with 0.2% ropivacaine (intervention group) or normal saline (control group). We measured pain scores, analgesic consumption and adverse effects. Functional prehabilitation outcomes, including peak expiratory flow (PEF) and the Six Minute Walk Test (6MWT) and Quality of Recovery Survey-40 (QoR-40) scores, were assessed before surgery, and 1 day and 7 days postoperatively. RESULTS: One hundred patients were randomly allocated to the study groups, of whom 92 completed the study, 46 in each group. There were no statistically significant differences between the 2 groups in baseline characteristics or any primary or secondary outcomes. Pain scores and analgesic consumption were low in both groups. There were no adverse events. Significant declines in PEF and 6MWT and QoR-40 scores were noted on postoperative day 1 in both groups; the values returned to baseline on postoperative day 7 in both groups. CONCLUSION: ClinicalTrials.gov no. NCT02154763.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".