The Use of Navigation During Total Knee Replacement Improves Precision in Achieving Mechanical Alignment in Obese Patients
Bibliographic record
Abstract
Background: ) is a global health challenge and a known risk factor of knee osteoarthritis (KOA), increasing the need for total knee arthroplasty (TKA). Obese patients face higher risks of early implant failure and revision, often linked to malalignment. Navigation-assisted surgery (NAS) improves precision in achieving mechanical alignment, but its impact in obese patients remains underexplored. This randomized, controlled, open-label, multicenter trial evaluated short-term radiographic outcomes, focusing on coronal alignment, in obese patients undergoing TKA with NAS versus conventional instrumentation. The primary hypothesis was that NAS would result in a higher rate of mechanical axis alignment within a predefined target (180° ± 3°). Methods: A total of 159 obese patients with symptomatic KOA were randomized 1:1 at 2 hospitals to undergo TKA with either NAS or conventional guides. Mechanical axis alignment was assessed 1 year postoperatively using long-standing radiographs. Secondary end points included femoral and tibial component alignment, surgical time, complications, range of motion, Knee Society Score, Western Ontario and McMaster Universities Osteoarthritis Index, visual analog scale, and EuroQol-5D. Results: In total, 154 patients were analyzed. Proper mechanical axis alignment (180° ± 3°) was achieved in 69% of NAS cases vs. 47% in controls (p = 0.006; OR = 2.5; 95% confidence interval: 1.29-4.83). The mean deviation was -1.59° (SD 3.02) in NAS vs. -2.15° (SD 3.56) in controls. Tibial alignment outliers occurred in 16% (12/73) of NAS vs. 32% (23/71) in controls (p = 0.026). Surgical time was longer with NAS (70 min [interquartile range (IQR) 63-76] vs. 59 min [IQR 55-67], p < 0.001). No differences were found in complications or hospital stay. Functional outcomes improved similarly in both groups at 1 year. Conclusion: NAS significantly improves precision in achieving mechanical alignment in obese patients undergoing TKA. Despite similar clinical outcomes, NAS offers superior radiographic accuracy. Longer term studies are needed to assess effects on implant survival and patient-reported outcomes. Level of Evidence: Level I. See Instructions for Authors for a complete description of levels of evidence.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".