Transmuscular quadratus lumborum block reduces opioid consumption and prolongs time to first opioid demand after laparoscopic nephrectomy
Bibliographic record
Abstract
BACKGROUND: Robotic and hand-assisted laparoscopic nephrectomies are often associated with moderate to severe postoperative pain. The aim of the current study was to investigate the analgesic efficacy of the transmuscular quadratus lumborum (TQL) block for patients undergoing robotic or hand-assisted laparoscopic nephrectomy. METHODS: Fifty patients were included in this single-center study. All patients were scheduled for elective hand-assisted or robotic laparoscopic nephrectomy under general anesthesia. Preoperatively, patients were randomly allocated to TQL block bilaterally with ropivacaine 60 mL 0.375% or 60 mL saline and all patients received standard multimodal analgesia and intravenous patient-controlled analgesia. Primary outcome was postoperative oral morphine equivalent (OME) consumption 0-12 hours. Secondary outcomes were postoperative OME consumption up to 24 hours, pain scores, time to first opioid, nausea/vomiting, time to first ambulation and hospital length of stay (LOS). RESULTS: Mean (95% CI) OME consumption was significantly lower in the intervention group at 12 hours after surgery 50 (28.5 to 71.5) mg versus control 87.5 (62.7 to 112.3) mg, p=0.02. At 24 hours, 69.4 (43.2 to 95.5) mg versus 127 (96.7 to 158.6) mg, p<0.01. Time to first opioid was significantly prolonged in the intervention group median (IQR) 4.4 (2.8-17.6) hours compared with 0.3 (0.1-1.0) hours in the control group, p<0.001. No significant intergroup differences were recorded for time to first ambulation, pain scores, nausea/vomiting nor for LOS. CONCLUSION: Preoperative bilateral TQL block significantly reduced postoperative opioid consumption by 43% and significantly prolonged time to first opioid. TRIAL REGISTRATION NUMBER: NCT03571490.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".