The Usefulness of a Simplified Navigation-Based Instrumentation for a Novice Surgeon in Primary Total Knee Arthroplasty: A Retrospective Analysis of a Randomized Controlled Trial
Bibliographic record
Abstract
Background: A novel simplified navigation-based instrumentation system has been developed. It simplifies the existing navigation system and facilitates convenient bone cutting by positioning the tracker on an existing cutting block without additional pin fixation. This study aimed to compare the outcomes of this newly developed simplified navigation-based instrumentation system in primary total knee arthroplasty (TKA) performed by a novice surgeon with those of conventional surgical techniques. Methods: From January 2020 to July 2020, 67 knees that underwent primary TKA using the ExactechGPS TKA Plus (group A) were compared to 68 knees that underwent primary TKA using a conventional technique (group B). All patients had a minimum follow-up of 24 months. The operative details such as tourniquet time were investigated. Postoperative hip-knee-ankle (HKA) angle and component position angles in the coronal and sagittal planes (α, β, γ, and δ angles) were evaluated. The outlier rates were compared between the groups as those lying outside ± 3°. Knee Injury and Osteoarthritis Outcome Score for Joint Replacement, the Western Ontario and McMaster Universities Osteoarthritis Index for pain and function, and range of motion were compared. Results: < 0.001) in group A were significantly lower than those in group B. There were no significant differences in clinical outcomes between the groups. Conclusions: Primary TKA performed by a novice surgeon using a simplified navigation-based instrumentation system did not significantly increase the operation time, and more accurate lower extremity mechanical alignment and tibial component alignment in the coronal plane could be obtained.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".