Intravenous Lidocaine Versus Thoracic Epidural Analgesia
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Laparoscopy, thoracic epidural analgesia, and enhanced recovery program (ERP) have been shown to be the major elements to facilitate the postoperative recovery strategy in open colorectal surgery. This study compared the effect of intraoperative and postoperative intravenous (IV) lidocaine infusion with thoracic epidural analgesia on postoperative restoration of bowel function in patients undergoing laparoscopic colorectal resection using an ERP. METHODS: Sixty patients scheduled for elective laparoscopic colorectal surgery were prospectively randomized to receive either thoracic epidural analgesia (TEA group) or IV lidocaine infusion (IL group) (1 mg/kg per hour) with patient-controlled analgesia morphine for the first 48 hours after surgery. All patients received a similar ERP. The primary outcome was time to return of bowel function. Postoperative pain intensity, time out of bed, dietary intake, duration of hospital stay, and postoperative complications were also recorded. RESULTS: Mean times and SD (95% confidence interval) to first flatus (TEA, 24 [SD, 11] [19-29] hrs vs IL, 27 [SD, 12] [22-32] hrs) and to bowel movements (TEA, 44 ±19 [35-52] hrs vs IL, 43 [SD, 20] [34-51] hrs) were similar in both groups (P = 0.887). Thoracic epidural analgesia provided better analgesia in patients undergoing rectal surgery. Time out of bed and dietary intake were similar. Patients in the TEA and IL groups were discharged on median day 3 (interquartile range, 3-4 days), P = 0.744. Sixty percent of patients in both groups left the hospital on day 3. CONCLUSIONS: Intraoperative and postoperative IV infusion of lidocaine in patients undergoing laparoscopic colorectal resection using an ERP had a similar impact on bowel function compared with thoracic epidural analgesia.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".