ROBOTIC-ASSISTED TOTAL KNEE ARTHROPLASTY IS ASSOCIATED WITH EARLIER RETURN OF SYMMETRICAL LIMB FUNCTION COMPARED TO CONVENTIONAL JIG-BASED TECHNIQUES USING WEARABLE SENSORS: A PROSPECTIVE COHORT STUDY
Bibliographic record
Abstract
The purpose of this study was to compare outcomes of patients undergoing robotic-assisted total knee arthroplasty (RA-TKA) to conventional jig-based techniques in the early post-operative period using traditional patient-reported outcome measures (PROMs) and wearable sensors. This was a prospective, matched, parallel cohort study of 100 patients with symptomatic end-stage knee osteoarthritis undergoing primary TKA (44 RA-TKA and 56 conventional TKA). Functional outcomes were assessed using ankle-worn inertial measurement units (IMU) and PROMs. IMU-based outcomes included impact load, impact asymmetry, maximum knee flexion angle, and bone stimulus. PROMs, including Oxford Knee Score (OKS), EuroQol-Five Dimension, EuroQol Visual Analogue Scale, and Forgotten Joint Score, were evaluated at pre-operative baseline, weeks 2 to 6 post-operatively, and at 3-month follow-up By post-operative week 6, RA-TKA was associated with significant improvements in maximum knee flexion angle compared to conventional TKA (118o ± 6.6o vs 113o ± 5.4o; p=0.04), symmetrical limb loading (82.3% vs 22.4%; p < 0 .01), cumulative impact load (146.6% vs 37%; p < 0 .01), and bone stimulus (25.1% vs 13.6%; p < 0 .01). Of note, RA-TKA demonstrated an earlier return to symmetrical limb loading, with operative limb IMU-based function reaching 80% of the non-operative limb by post-operative week 3. There were no significant differences in PROMs between the two groups, however, significantly more RA-TKA patients achieved an ‘excellent’ outcome at 6 weeks compared to conventional TKA using OKS subscales (47% vs 41%, p=0.013). RA-TKAs were associated with earlier functional improvements when assessed using IMUs compared to conventional TKA, which were not detected by traditional PROMs during the early post-operative period.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".