Comparison of the popliteal artery and the capsule of the posterior knee (IPACK) block and the genicular nerve block in primary total knee arthroplasty
Bibliographic record
Abstract
Objectives: To compare the efficacy of genicular block and interspace between the popliteal artery and the posterior capsule (IPACK) block in the reduction of postoperative pain, the need for rescue analgesics, and the effects on a range of motion (ROM) in patients with TKA. Methods: This prospective randomized controlled study was carried out between February and May 2023. Based on the block method, 60 participants were divided into three equal groups. These groups included the IPACK block group (n=20), the genicular block group (n=20), and control group (n=20). Western Ontario and McMaster Universities Arthritis Index (WOMAC), Knee Society score (KSS) and Oxford Knee score (OKS) were used for clinical evaluation in the postoperative period. Results: The KSS and OKS scores of the IPACK and GNB were significantly lower than the control group (p<0.001, p<0.001). The timed up and go (TUG) values of the IPACK and GNB groups at 12th and 24th hour were significantly lower than the control group (p<0.001, p<0.001). The Tramadol rescue values of the IPACK block and control groups were significantly higher than the GNB group (p=0.028, p=0.001, respectively). The ROM values of the IPACK and GNB groups were significantly higher than the control group (p<0.001, p<0.001). Conclusion: Both GNB and IPACK blocks had a significant positive impact on postoperative pain scores within the initial 24 hours following total knee arthroplasty (TKA). In comparison with IPACK, GNB had lower opioid consumption in the early postoperative period while also promoting better mobilization.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".