Comparison of computer-assisted navigation and conventional instrumentation for bilateral total knee arthroplasty
Bibliographic record
Abstract
It remains unclear if computer-assisted surgery (CAS) technique actually improves the clinical outcomes of total knee arthroplasty (TKA) and decreases the failure rate. The purpose of this retrospective study was to compare the functional results of TKA in a series of patients who underwent staged bilateral TKAs with CAS TKA in 1 knee and conventional TKA in the contralateral knee.From January 1997 to December 2010, we collected 60 patients who were randomly assigned to receive CAS TKA in 1 limb and conventional TKA in the other. The Brainlab Vector Vision navigation system was used for CAS TKA, and the DePuy press-fit condylar sigma guide system was used for conventional TKA. Patients were assessed before surgery, 3 months and 1 year after surgery, and annually thereafter. IKS criteria were used for radiographic evaluation. Clinical and functional evaluation using the scoring system of hospital for special surgery (HSS), international knee society (IKS), Western Ontario and McMaster University osteoarthritis index (WOMAC), and short form-36 (SF-36) were obtained on each knee, before surgery, and at each follow-up visit. Pertinent statistical methods were adopted for data analysis.Fifty-six patients were available for analysis and 44 of the patients were female. The mean duration of follow-up was 8.1 years. Less blood loss (P = .007) and longer operation time were noted for CAS TKAs when compared with conventional TKAs. Precise alignment and fewer outliers of the lower limb and prosthetic component positions were found for CAS TKAs (P < .001). There were no differences between the 2 groups before surgery and at the latest follow-up with regard to scores for HSS, IKS, WOMAC, and SF-36 as well as active range of motion.The clinical outcomes of CAS TKAs at the 8-year follow-up were similar to those of conventional TKAs despite the better radiographic alignment and fewer outliers achieved with navigation assistance.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".