Gait analysis and WOMAC are complementary in assessing functional outcome in total hip replacement
Bibliographic record
Abstract
OBJECTIVE: To investigate the correlation between objective and subjective evaluation of patients with total hip replacement. DESIGN: Prospective preliminary trial comparing the Western Ontario and McMaster University questionnaire (WOMAC) and gait analysis preoperatively and three months postoperatively. SETTING: A German academic orthopaedic centre specializing in total hip replacement surgery. SUBJECTS: Seventeen patients (median age 70 years) with hip osteoarthritis. INTERVENTION: All patients had had a primary unilateral total hip replacement. MAIN MEASURES: WOMAC questionnaire to assess self-perceived health status and gait analysis to determine objective gait parameters. RESULTS: Performance of walking as well as subjective judgement of health status improved following surgery (gait speed P = 0.0222; stride length P = 0.038; stance phase ratio P = 0.0466; WOMAC P < 0.0001). However, the correlation between gait parameters and WOMAC was poor (r = -0.27 or less). Correlation between changes of walking parameters and WOMAC was bad to good (r = 0.01 to r = -0.72). CONCLUSION: The WOMAC questionnaire might not reflect walking performance. The addition of gait analysis is recommended to gain objective information about the quality of gait.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".