Peripheral Nerve Block for Pain Management after Total Hip Arthroplasty: A Retrospective Study with Propensity Score Matching
Bibliographic record
Abstract
This study aimed to evaluate the effect of a peripheral nerve block (PNB) on immediate postoperative analgesia and the early functional outcomes for patients who underwent total hip arthroplasty (THA). From January 2016 to August 2021, 353 patients who underwent THA were divided into two groups: the patient-controlled analgesia (PCA) group (n = 217) who received only intravenous (IV) analgesia, and others who received IV PCA and PNB (PCA + PNB group) (n = 136). After propensity score matching for age and sex, 136 patients from each group were included in the study. Primary outcomes were the visual analogue scale (VAS) at rest, activity status at postoperative 6, 24, 48 h. Secondary outcomes were functional scores by the Western Ontario and McMaster Universities Osteoarthritis (WOMAC) index, Harris Hip Score (HHS) and rescue medications used. The postoperative VAS at 6, 24, 48 h at rest and 6 h at activity were significantly lower in the PCA + PNB group (p = 0.000, 0.001, 0.000, 0.004 in order). There was no significant difference for postoperative 3-month HHS (p = 0.218), except for 3-month WOMAC index (p = 0.001). There were no significant differences for VAS between the PNB methods except femoral nerve block (FNB) and fascia iliaca compartment block (FICB) at postoperative activity 48 h (p = 0.028). There was no significant difference in the total count and amount of rescue medication (p = 0.091, 0.069) and difference in the quadriceps weakness was not noted. Therefore, PNB is beneficial for patients who undergo THA as it provides sufficient postoperative analgesia, especially during immediate postoperative resting pain without quadriceps weakness.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".