Comparative Outcomes Between Cruciate-Retaining and Posterior-Stabilized Prostheses in Total Knee Arthroplasty
Bibliographic record
Abstract
Introduction Total knee arthroplasty (TKA) is the definitive surgical treatment for advanced gonarthrosis when conservative measures fail. Among the available implant designs, posterior cruciate-retaining (PCR) and posterior-stabilized (PS) prostheses are widely used, yet their comparative performance in long-term functional recovery and health-related quality of life remains under debate. Methods We conducted a prospective observational study involving 48 elderly patients undergoing primary TKA at a tertiary-care center in Mexico. Participants received either PCR (n=27) or PS (n=21) implants based on intraoperative assessment. Patient-reported outcomes were evaluated using the Western Ontario and McMaster Universities Osteoarthritis (WOMAC) Index, the 36-Item Short Form Health Survey (SF-36), and Patient-Reported Outcomes Measurement Information System (PROMIS-10) Global Health questionnaire at preoperative, six, 12, and 24 months postoperatively. Results Both groups demonstrated improvements in all outcome measures; however, PCR patients consistently achieved better results across the follow-up period. At 24 months, WOMAC scores, which reflect better symptom control with higher values, were superior in the PCR group for pain (77.5 vs. 71.0), stiffness (72.5 vs. 62.5), and physical function (86.5 vs. 82.6). SF-36 also favored PCR in physical functioning (66.5 vs. 64.1), bodily pain (72.1 vs. 70.0), and role-physical (54.0 vs. 51.0). PROMIS-10 confirmed these trends, with higher physical (73.9 vs. 71.3) and mental health scores (75.2 vs. 72.0) among PCR patients at 24 months. Conclusions Patients receiving cruciate-retaining prostheses experienced greater and more sustained improvements in pain relief, joint function, and quality of life compared to those with posterior-stabilized implants. These findings support the functional advantage of PCR designs in elderly patients undergoing TKA and highlight the value of long-term, multidimensional outcome assessment using patient-reported outcome measures (PROMs).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".