Comparison of the accelerometer-based navigation system with conventional instruments for total knee arthroplasty: a propensity score-matched analysis
Bibliographic record
Abstract
BACKGROUND: The accelerometer-based navigation (ABN) system is an emerging navigation system for total knee arthroplasty (TKA). This study aimed to determine whether the ABN system could improve the accuracy of mechanical alignment, component positioning, and short-term clinical outcomes for TKA when compared to conventional instruments (CON). METHODS: A total of 204 patients were selected and divided into two groups (CON: 135, ABN: 69) after applying the inclusion and exclusion criteria. Then, 1:1 propensity score matching was performed for age, gender, body mass index, hip-knee-ankle angle (HKA), Knee Society Score (KSS), Western Ontario and McMaster Universities (WOMAC) score, and follow-up times. A total of 82 consecutive patients (82 knees) underwent total knee arthroplasty using ABN (n = 41) or CON (n = 41) were enrolled in this study. The postoperative HKA, frontal femoral component (FFC) angle, frontal tibial component (FTC) angle, lateral femoral flexion (LFF) angle, and lateral tibial component (LTC) angle were compared between the two groups to evaluate mechanical alignment and component positioning. Additional clinical parameters, including haemoglobin reduction, the KSS, and the WOMAC score, were assessed at the final follow-up (the mean follow-up period was 20.9 months in the CON group and 21.2 months in the ABN group). RESULTS: The ABN group had a significantly improved mean absolute deviation of HKA (P = 0.033), FFC (P = 0.004), FTC (P = 0.017), LFF (P = 0.023), and LTC (P = 0.031) compared to those of the CON group. The numbers of FFCs and LTCs within 3° were significantly different (P = 0.021, P = 0.023, respectively) between the two groups. However, no differences in the numbers of FTCs within 3° (P = 0.166) and LFF within 3° (P = 0.556) were found. The ABN group had a significantly higher KS function score (P = 0.032), and the pain and stiffness scores were significantly different (P = 0.034, P = 0.020, respectively) between the two groups. Moreover, the ABN system could reduce hidden blood loss postoperatively. However, no difference was found in the KS knee score and the total WOMAC score between the two groups. CONCLUSION: This study demonstrates that ABN system improved TKA mechanical alignment and component positioning and decreased the hidden blood loss postoperatively compared to conventional instruments. However, no significant differences were found in short-term clinical outcomes between ABN and conventional instruments at the final follow-up. However, whether this system contributes to revision rates and long-term clinical outcomes requires further study.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".