Der Einfluss von präoperativem Funktionsstatus und Schmerz auf das patientenzentrierte Frühergebnis nach Hüftendoprothesen-Implantation
Bibliographic record
Abstract
AIM: It was the purpose of this prospective study to investigate the impact of preoperative functional status and pain on the early patient-centred outcome after total hip arthroplasty (THA). METHODS: 67 consecutive patients scheduled for THA were included in this study. Outcome was analysed with the Western Ontario and McMaster Universities' (WOMAC) Osteoarthritis Index preoperatively and after ten days and 12 weeks, respectively. Patients were grouped with regard to their preoperative function and pain according to the WOMAC Osteoarthritis Index. Statistical analysis was performed using a multivariate regression model considering further confounding variables (age, gender, affected side, duration of surgery, and anchorage of THA). RESULTS: All patients showed a significant functional improvement both at ten days postoperatively and after three months, respectively. Patients with a higher degree of disability preoperatively had a larger relative functional improvement according to their WOMAC score compared to patients who initially were less deteriorated. However, the latter had the better absolute scores postoperatively. Multiple regression analysis revealed gender (OR: -11.85, 95% CI: -22.65 to -1.06, p=0.03) and preoperative WOMAC score (OR: 0.34, 95% CI: 0.09 to 0.59, p<0.01) to be significant prognostic variables at ten days postoperatively. After three months, age (OR: 0.43, 95% CI: 0.04 to 0.82, p=0.03) was the only variable predicting the patient-centred outcome. CONCLUSION: In our study sample, patient-related variables did significantly influence the patient-centred outcome after ten days (gender and WOMAC) and at three months postoperatively (age) whereas procedure-related variables did not have any impact.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".