Surgically modifiable factors measured by computer-navigation together with patient-specific factors predict knee society score after total knee arthroplasty
- PMID: 26873695
- PMCID: PMC4752747
- DOI: 10.1186/s12891-016-0929-7
Surgically modifiable factors measured by computer-navigation together with patient-specific factors predict knee society score after total knee arthroplasty
Abstract
Background: The purpose was to investigate whether patient-specific factors (PSF) and surgically modifiable factors (SMF), measured by means of a computer-assisted navigation system, can predict the Knee Society Scores (KSS) after total knee arthroplasty (TKA).
Methods: Data from 99 patients collected during a randomized clinical trial were used for this secondary data analysis. The KSS scores of the patients were measured preoperatively and at 4-years follow-up. Multiple regression analyses were performed to investigate which combination of variables would be the best to predict the 4-years KSS scores.
Results: When considering SMF alone the combination of four of them significantly predicted the 4-years KSS-F score (p = 0.009), explaining 18 % of its variation. When considering only PSF the combination of age and body weight significantly predicted the 4-years KSS-F (p = 0.008), explaining 11 % of its variation. When considering both groups of predictors simultaneously the combination of three PSF and two SMF significantly predicted the 4-years KSS-F (p = 0.007), explaining 20 % of its variation.
Conclusions: Younger age, better preoperative KSS-F scores and lower BMI before surgery, a positive tibial component slope and small changes in femoral offset were predictors of better KSS-F scores at 4-years.
References
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- Lingard EA, Katz JN, Wright EA, Sledge CB. Predicting the outcome of total knee arthroplasty. J Bone Joint Surg Am. 2004;86-A(10):2179–86. - PubMed
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