Patient-Reported Outcomes following Cemented versus Cementless Primary Total Knee Arthroplasty: A comparative analysis based on propensity score matching
Bibliographic record
Abstract
Abstract Background: Existing studies of patient-reported outcomes (PRO) following total knee arthroplasty (TKA) based on fixation methods (cemented vs cementless) are limited to single centers with small sample sizes. Using data from the large, multicenter Comparative Effectiveness of Pulmonary Embolism Prevention After Hip and Knee Replacement (PEPPER) trial (ClinicalTrials.gov: NCT02810704), we compared baseline and early post-operative global and condition-specific PROs between patients undergoing cemented versus cementless TKA.Methods: We examined prospectively collected pre- and post-operative (1, 3, and 6-months) outcomes in 5,961 patients undergoing primary TKA enrolled by 28 medical centers between 12/19/2016 and 8/31/2021. Outcomes included the short-form of the Knee Injury and Osteoarthritis Outcome Score (KOOS-Jr.), the Patient-Reported Outcomes Measurement Information System Physical Health (PROMIS-PH), and the Numeric Pain Rating Scale (NPRS). To minimize selection bias, we performed a 1-to-1 propensity score matched analysis to assess relative pre- to post-operative change in outcomes within and between cemented and cementless TKA groups.Results: Propensity score matching provided balanced covariates between TKA groups. With greater than 90% follow-up, significant pre to- post-operative improvements were observed in both groups. At 6 months, the cemented TKA group achieved a 3.3 point (55% of the Minimum Clinically Important Difference) greater improvement in the mean KOOS-Jr. (95%CI: 0.36, 6.30; P=0.028) than did the cementless group with no significant between-group differences in PROMIS-PH and NPRS. Conclusions: In a large cohort of primary TKAs, patients with cemented fixation reported early incremental benefit in KOOS-Jr. over those with cementless TKA. Future studies are warranted to capture longer follow-up of PROs.
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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 | 0.015 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".