Do pain referral patterns determine patient outcome after total hip arthroplasty?
Bibliographic record
Abstract
Quality of life outcome and patient satisfaction after total hip arthroplasty are complex phenomena and many confounding determinants have been identified. Degenerative disease of the hip joint may present with variable patterns of pain referral in the lower limb. However the effect of varied preoperative pain referral patterns on patient outcome and satisfaction after total hip arthroplasty has not previously been examined. From 2000 to 2003, 236 eligible patients scheduled to undergo primary total hip arthroplasty were prospectively enrolled. The principal pain referral pattern (as hip, thigh or knee) was identified in all patients. Health related quality of life (HRQOL) was examined using the Harris Hip score (HHS), the Western Ontario McMaster Universities Osteoarthritis Index (WOMAC) and the 36-Item Short-Form Health Survey (SF-36) pre-operatively, 1 year and 2 years postoperatively and with the HHS at 3 months postoperatively. All patients were followed up for a minimum of 2 years. The frequency of the pain referral distributions were; hip pain 41%, knee pain 32% and thigh pain 27%. Patients in all groups were comparable preoperatively with respect to age, HHS, and both mean and domain specific WOMAC and SF-36 scores. The mean duration of symptoms was significantly greater in patients with knee pain when compared to the remaining two pain patterns. All patients demonstrated improvements in HHS, SF-36 and WOMAC scores after surgery. At all times postoperatively there were significant differences in mean HHS and mean and domain specific WOMAC and SF-36 scores between patients with hip or thigh pain and those with knee pain (p < 0.001). While notable, differences between hip and thigh pain were not as consistent however. Based on these findings, it appears that pre-operative pain referral patterns of hip arthritis are among the determinant factors for patient outcome and satisfaction after total hip arthroplasty, as measured using validated HRQOL scoring systems.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".