Analgesic Efficacy of Single-Shot Erector Spinae Block in Video-Assisted Thoracoscopic Surgery: A Propensity Score-Matched Retrospective Cohort Study
Bibliographic record
Abstract
Introduction Video-assisted thoracic surgery (VATS) is a minimally invasive surgical technique though effective analgesia remains a challenge. Erector spinae plane block (ESPB) has gained popularity due to its ease and safety of placement. In this study, we evaluated the analgesic efficacy of ESPB in patients undergoing VATS through a propensity score-matched retrospective cohort study. The primary outcome is the total opioid use in the first 12 postoperative hours. Methods We used binomial logistic regression to model whether patients received ESPB as a function of age, sex, body mass index (BMI), American Society of Anesthesiologists (ASA) physical status, and surgery type to generate a propensity score for each patient for matching. Results After screening 286 patients, 55 patients each in the ESPB and no-block groups were matched. ESPB was associated with a 1.2 mg (95% CI: -2.2 to -0.2) reduction in opioid use in IV hydromorphone equivalents when compared to no block. However, there was no reduction in the 12-hour pain score area under the curve or incidence of complications between the two groups. Conclusions ESPB was associated with a modest reduction in total opioid consumption although not a difference in pain score. While its analgesic efficacy may be limited, ESPB could be considered a component of multi-modal analgesia in VATS.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".