One-staged hip and knee arthroplasty: a retrospective clinical and radiographical study
Bibliographic record
Abstract
BACKGROUND: Prosthetic replacements of the hip and knee are two great successes of orthopedic surgery, which have shown effectiveness and reliability. One-staged hip or knee replacement may be indicated for patients affected from symptomatic end-stage bilateral hip or knee osteoarthritis. The aim of this study was to evaluate clinical and radiographical outcomes and complications of a group of 12 patients.METHODS: All the patients were evaluated clinically by Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and Visual Analogue Scale and radiographically (offset, cervical-diaphyseal angle, hip-knee-ankle angle, limb length discrepancy, osseointegration, heterotopic ossification). A statistical analysis was performed.RESULTS: At a mean follow-up of 28.8 months all the implants were well-positioned and osseointegrated. There was a marked improvement in pain (P<0.001) and WOMAC (P<0.001). The radiographic evaluations showed good restoration of the articular geometry. No complications were recorded.CONCLUSIONS: One-staged hip and knee arthroplasty has demonstrated to have good functional outcomes with low complication rate.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".