Efficacy of Different Approaches of Quadratus Lumborum Block for Postoperative Analgesia After Cesarean Delivery
Bibliographic record
Abstract
OBJECTIVES: Various approaches to quadratus lumborum block (QLB) have been found to be an effective analgesic modality after cesarean delivery (CD). However, the evidence for the superiority of any individual approach still needs to be demonstrated. Therefore, we conducted this network meta-analysis to compare and rank the different injection sites for QLB for pain-related outcomes after CD. MATERIALS AND METHODS: PubMed, EMBASE, SCOPUS, and the Cochrane Central Registers of Controlled Trials (CENTRAL) were searched for randomized controlled trials (RCTs) evaluating the role of any approach of QLB with placebo/no block for post-CD pain. The primary outcome was parenteral consumption of morphine milligram equivalents in 24 postoperative hours. The secondary end points were early pain scores (4 to 6 h), late pain scores (24 h), adverse effects, and block-related complications. We used the surface under cumulative ranking probabilities to order approaches. The analysis was performed using Bayesian statistics (random-effects model). RESULTS: Thirteen trials enrolling 890 patients were included. The surface under cumulative ranking probability for parenteral morphine equivalent consumption in 24 hours was the highest (87%) for the lateral approach, followed by the posterior and anterior approaches. The probability of reducing pain scores at all intervals was highest with the anterior approach. The anterior approach also ranked high for postoperative nausea and vomiting reduction, the only consistent reported side effect. DISCUSSION: The anterior approach QLB had a superior probability for most patient-centric outcomes for patients undergoing CD. The findings should be confirmed through large RCTs.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.018 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".