Paravertebral vs. Epidural Analgesia for Liver Surgery (PEALS): Protocol for a randomized controlled pilot study
Bibliographic record
Abstract
Background: Perioperative thoracic epidural analgesia (TEA) is commonly used in hepatectomy patients since it is opioid-sparing and reduces cardiorespiratory complications. However, TEA has a high failure rate and is associated with potentially devastating complications (particularly spinal haematoma) and the risk is likely increased with hepatectomy. Thus, some centres favour systemic opioid-based modalities which, in turn, are associated with inferior analgesia and well-known risks/side-effects. Hence, alternative analgesic methods are desirable. Paravertebral block (PVB) has been used in liver resection with advantages including hemodynamic stability, low failure rates, and low risk of spinal haematoma. Our purpose is to conduct a blinded, pilot RCT with hepatectomy patients randomised to receive TEA or PVB for perioperative analgesia. Our hypothesis is that opioid consumption, time to first analgesic request, and pain scores will be comparable between groups, but PVB patients will require fewer perioperative vasopressors/blood products, and have fewer adverse events and a shorter hospital stay. Methods: With ethics approval, this non-inferiority, pilot RCT with a convenience sample of 50 hepatectomy patients will examine whether PVB imparts analgesia comparable to TEA but with fewer adverse effects. Primary outcomes are surrogates of analgesia for 72 h postoperatively (i.e., opioid consumption, time to first analgesic request and pain scores at rest and with coughing); Secondary outcomes are blood products/fluids administered; side effects/complications until 72 h postoperatively; length of hospital stay. The results will be used to plan a large multicentre trial comparing TEA vs. PVB in hepatectomy patients. This study has a high potential to positively impact the quality/safety of patient care. ClinicalTrials.gov registration: NCT02909322 (09-21-2016); Available at URL: https://clinicaltrials.gov/ct2/show/NCT0290932
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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 | 0.034 | 0.037 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.076 | 0.011 |
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".