Computer-Assisted Compared with Conventional Total Knee Replacement
Bibliographic record
Abstract
BACKGROUND: We previously reported the short-term radiographic and functional results of a randomized controlled trial (RCT) comparing computer-assisted and conventionally performed total knee replacement. We currently report the 2-year clinical results from this trial. METHODS: One hundred and ninety patients were randomly allocated to undergo either computer-assisted or conventional total knee replacement. One hundred and seventy-two patients were available for clinical evaluation at 2 years, and 167 (97%) of those answered all patient-reported outcome measures (PROMs), including the Knee Injury and Osteoarthritis Outcome Score (KOOS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Knee Society Score (KSS), visual analog scale (VAS), and EuroQol-5 Dimensions (EQ-5D). Patients and clinical evaluators were blinded to the method of surgery. Surgical outcome was assessed using the Outcome Measures in Rheumatology-Osteoarthritis Research Society International (OMERACT-OARSI) criteria to calculate responder rates, divided into high responders, moderate responders, and nonresponders. RESULTS: The computer-assisted group had significantly more improvement than the conventional group in the mean scores for 2 subscales of the KOOS (7.4 for symptoms [p = 0.02] and 16.2 for sport and recreation [p < 0.01]) and in 1 subscale of the WOMAC (8.8 for stiffness [p = 0.03]).The computer-assisted group also had significantly more high responders (82.8%) than the conventional group (68.8%; p = 0.03) at 2 years, with the number needed to treat determined to be 8. CONCLUSIONS: In this study, the use of computer navigation provided better pain relief and restored better function than the use of the conventional surgical technique at 2 years after total knee replacement. LEVEL OF EVIDENCE: Therapeutic Level I. See Instructions for Authors for a complete description of levels of evidence.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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, 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".