Comparison of iASSIST Navigation System with Conventional Techniques in Total Knee Arthroplasty: A Systematic Review and Meta‐Analysis of Radiographic and Clinical Outcomes
Bibliographic record
Abstract
The iASSIST navigation system is a handheld accelerometer‐based navigation system that has been applied in clinical practice in recent five years. This meta‐analysis aimed to compare the radiographic and clinical outcomes of iASSIST navigation with conventional surgical techniques for patients undergoing total knee arthroplasty (TKA) and to compare the surgery time between an iASSIST group and a conventional treatment group. This systematic review and meta‐analysis included all comparative prospective and retrospective studies published in Pubmed, Embase, the Cochrane Central Register of Controlled Trials, the Web of Science and the CNKI databases over the past 20 years. Inclusion criteria were studies that compared the iASSIST navigation system with conventional TKA. The primary outcomes were mechanical axis (MA) and outliers, which means postoperative MA varus or valgus of more than 3°. Secondary outcomes were coronal femoral angle (CFA) and coronal tibial angle (CTA). Knee Society Score (KSS) was used to evaluate functional outcome. The Newcastle–Ottawa Scale (NOS) was used to assess the methodological quality of included studies. Eight studies involving 558 knees were included in this meta‐analysis. Of these, 275 patients used the iASSIST navigation system and 283 used conventional surgical techniques. A total of 5 studies were considered high quality and the other 3 were considered to be of moderate quality. The occurrence of malalignment of >3° in the iASSIST group was 13.3%, compared with 29.04% in the conventional group. Postoperative MA of the iASSIST group was significantly better than that of the conventional group (I2 = 19%, OR = −0.92, 95% CI = −1.09 to −0.75, P < 0.00001). The iASSIST navigation system provided significantly increased accuracy in the coronal femoral angle (I2 = 79%, OR = −0.88, 95% CI = −1.21 to −0.54, P < 0.00001) and the coronal tibial angle (I2 = 34%, OR = 0.39, 95% CI = −0.48 to −0.30, P < 0.00001) compared with conventional techniques. However, the duration of surgery using the iASSIST procedure was longer and there was no significant difference in the short‐term KSS in the iASSIST group compared with the conventional group. We found that when pooling the data of included studies, the number of outliers was fewer in the iASSIST group, and compared with conventional TKA techniques, the iASSIST system significantly improved the accuracy of lower limb alignment but the duration of surgery was prolonged in addition to there being no apparent advantage in terms of short‐term functional score.
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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 | 0.012 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.036 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".