Relative perioperative analgesic efficacy of single-shot serratus anterior plane block versus thoracic paravertebral block in breast and thoracic surgeries – A systematic review and meta-analysis of randomised controlled trials
Bibliographic record
Abstract
Background and Aims: Various regional analgesia techniques, such as thoracic paravertebral (TPV) and serratus anterior plane (SAP) blocks, have been employed to manage postoperative pain following chest wall surgery. However, the comparative analgesic efficacy of these two approaches remains uncertain. This systematic review and meta-analysis aimed to assess the relative analgesic efficacy of these blocks in chest wall surgeries, including breast and thoracic procedures. The primary objective was the time to first rescue analgesia, and the secondary objective encompassed opioid consumption within 24 h, pain scores at different time intervals, opioid-related adverse effects and block-related complications. Methods: A systematic search for randomised controlled trials (RCTs) was conducted in PubMed, EMBASE and Scopus databases, covering studies from their inception to September 2023. We included active treatment arms from RCTs comparing these analgesic modalities. Statistical analysis was conducted in Review Manager Version 5.3, and results were analysed and reported separately for breast and thoracic surgery subgroups. Results: = 98%) between the SAP and TPV block groups. However, the TPV block demonstrated superior results for secondary outcomes in thoracic surgery patients. Complications related to the TPV block included pleural puncture and haematoma at the injection site. Conclusions: The evidence suggests that both blocks generally offer comparable analgesic efficacy for chest wall surgery patients, with the TPV block providing a slight advantage for those undergoing thoracic surgery.
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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 | 0.015 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.038 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".