Does Robotic-Assisted Functional Knee Positioning Result in Better Functional Outcomes One Year After Surgery
Bibliographic record
Abstract
INTRODUCTION: Robotic-assisted total knee arthroplasty (TKA) allows surgeons to individualize implant placement based on soft tissue and bony anatomy, called functional knee positioning (FKP). We aimed to compare patient-reported outcome measures (PROMs) of mechanically aligned total knee arthroplasty (MA-TKA) with functionally positioned total knee arthroplasty (FP-TKA). MATERIALS AND METHODS: Patients who underwent primary MA-TKA and FP-TKA were propensity score matched 1:1 (145 MA-TKA: 145 FP-TKA cases) using a prospectively collected institutional dataset. For FP-TKA cases, the surgeon followed functional positioning principles, individualizing planned implant position to balance the knee prior to bone cuts while minimizing the need for soft tissue releases. For MA-TKA, cases were mechanically aligned and gap balanced using standard techniques. The postoperative reduced Western Ontario and McMaster Arthritis Score (r-WOMAC) Pain and Function scores were compared at six months and one year using average and t-tests. The length of stay (LOS), as well as knee extension and flexion at six weeks were compared. RESULTS: There was no statistically significant difference in the r-WOMAC pain and r-WOMAC function scores between both groups at six months; however, both trended towards the FP-TKA group. At one year, the r-WOMAC function scores significantly improved for the FP-TKA group compared to controls (2.94 vs. 4.38; p=0.02). There was no significant difference in the r-WOMAC pain scores at one year. The FP-TKA cohort required a shorter LOS compared to those who had MA-TKA (1.75 vs. 2.36; p<0.0001). There was no significant difference in flexion or extension at six weeks between groups (p=0.77 and 0.18, respectively). CONCLUSION: We demonstrate that patients who underwent FP-TKA trended toward functional improvements at six months and significant improvements in function at one year (which did not reach minimally clinical important difference). Functional positioning strategies may improve patient-reported outcomes due to minimizing dissection and personalizing implant position.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".