No difference in the functional improvements between unilateral and bilateral total knee replacements
Bibliographic record
Abstract
BACKGROUND: Differences between staged bilateral total knee replacement (TKR) and simultaneous bilateral TKR have been investigated, but few studies have investigated differences in the functional improvements resulting from these methods. Therefore, this study investigates the different functional improvements between staged bilateral total knee TKR and simultaneous bilateral TKR. METHODS: Among 144 potential bilateral TKR patients who were included in this study, 93 (64.6%) patients selected unilateral TKR and 51 (35.4%) selected bilateral TKR. Functional improvements were assessed using the Western Ontario and McMaster University osteoarthritis index (WOMAC) and the Medical Outcomes Trust Short Form-36 (SF-36), and patients were interviewed pre-operatively and after 6 months. A generalized equation was used to test for differences in functional improvements. RESULTS: After TKR, pain, stiffness, function and total WOMAC scores were significantly reduced in both groups, with mean changes from - 26.6 to - 41.4 and from - 27.5 to - 42.2.The mean health change of SF-36 scores, physical component and mental component scores changed to 45.2 ± 18.2, 74.0 ± 15.4 and 77.0 ± 9.6, respectively, in Group 1 and 47.1 ± 17.1, 74.0 ± 15.2 and 75.5 ± 12.1, respectively, in Group 2. Unilateral and simultaneous bilateral TKR produce similar functional improvements, although current work status may be a novel impact factor. CONCLUSION: No differences in functional improvements were identified between patients who selected unilateral versus bilateral TKR, indicating no recommendation for one procedure over the other.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".