Hip and knee replacement continuum of care: combining clinical and functional outcome measurement
Bibliographic record
Abstract
The total number of hip and knee arthroplasties has been increasing steadily in the USA every year. The University of California Irvine recognized a high volume activity that could be improved with the implementation of clinical pathways. Data collection was obtained by monitoring the clinical path on 138 patients. Baseline preoperative data and telephonic postoperative data were collected at 90 days postdischarge utilizing quality-of-life/functionality validated tools. Clinical path utilization was 100%. Ambulation day 1 was at 80% for hips and 85% for knees. Blood transfusions were at 56% for hips and 36% for knees. These percentages are well above the US national reported value for autologous blood transfusions of 30%. The short form 36 health survey questionnaire (SF-36) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) preoperative and postoperative data were available on 47 patients (35%) at 90 days. The WOMAC osteoarthritis index showed a percent mean difference improvement of 82% (pre = 35.8, post = 65.3). The SF-36 revealed statistical significance in physical functioning, role physical, social functioning, bodily pain, energy/vitality and mental health. In conclusion, clinical pathways are a reliable measure of health care. Analysis of clinical path variance and functional outcomes provide the necessary data for making sound business/health-care decisions.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".