Similar outcomes between ultracongruent and posterior-stabilized insert in total knee arthroplasty: A propensity score-matched analysis
Bibliographic record
Abstract
Purpose: (1) To compare postoperative range of motion (ROM), stability, and clinical outcomes between fixed-bearing posterior-stabilized (PS) and ultracongruent (UC). (2) The effect of postoperative stability on ROM and clinical outcomes was also evaluated in both designs. Materials and methods: Propensity score matching was conducted for age, gender, body mass index, preoperative ROM, Western Ontario and McMaster Universities Osteoarthritis (WOMAC) index, Knee Society (KS) scores, hip–knee–ankle (HKA) alignment, and follow-up period. Two hundred patients (100 PS and 100 UC) were enrolled. Preoperative and final follow-up outcomes including postoperative ROM, anteroposterior (AP) stability (good, fair, and poor), WOMAC index, and KS scores were compared. Then, postoperative outcomes compared between the PS and UC. We also analyzed if AP stability was associated with the postoperative outcomes in both implant designs. Results: In both groups, ROM and clinical outcomes of final follow-up showed improvement than preoperation. Statistical significance was not determined between the PS and UC groups in terms of postoperative ROM (PS vs. UC, 134.6° vs. 133.4°, p = 0.13), stability (good/fair/poor, 91/9/0 vs. 84/14/0, p = 0.376), WOMAC index, KS scores, and outliers of HKA alignment (15% vs. 10%, p = 0.393). “Fair” stability showed inferior KS scores but greater ROM than “good” stability in both designs. Conclusion: TKA with UC insert provided similar ROM, AP stability, and clinical outcomes when compared to PS insert. In both designs, greater postoperative ROM was found but inferior clinical outcomes were found when TKA resulted in fair stability instead of good stability. Level of evidence III: Retrospective comparative study.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".