EP181 Quality of post-operative analgesia of paravertebral blocks vs thoracic epidurals in patients undergoing vats lobectomies
Bibliographic record
Abstract
Please confirm that an ethics committee approval has been applied for or granted: Not relevant Background and Aims Inadequate pain management after VATS lobectomies has been associated with significant morbidity. Thoracic epidurals (TEAs) have classically been the primary modality for post-operative analgesia. However, they are not without significant complications. We investigated if paravertebral blocks (PVBs) provide non-inferior postoperative analgesia while diminishing patients‘ risk of analgesia-related complications. Methods We performed an anonymized prospective chart review of 165 patients undergoing VATS lobectomies with a PVB or a TEA at Vancouver General Hospital with local health authority approval. Postoperative pain scores at rest and with activity, and total opioid consumption, were recorded in the PACU, and on postoperative days 0, 1, and 2. The frequency of hemodynamic and respiratory complications, Foley catheterization, nausea, pruritus, and drowsiness were recorded at the same time intervals. Data were analyzed using a linear mixed model. P-values less than 0.05 were considered to be significant. Results 65 patients received a PVB and 100 patients received a TEA, and the groups did not differ significantly for any studied demographic variable. We did not identify any points in patients’ post-operative courses where pain, at rest and with activity, and total opioid consumption differed significantly between the two patient cohorts. Patients who received TEAs had more complications than those with PVBs, with the greatest differences found in the incidence of hemodynamic complications, pruritis, and Foley catheterization. Conclusions PVBs offer non-inferior analgesia while providing a reduced incidence of analgesia-related complications relative to TEAs in patients undergoing VATS lobectomies. PVBs should thus be considered as an effective analgesic alternative to TEAs in these patients.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.004 | 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".