Surgically modifiable factors measured by computer-navigation together with patient-specific factors predict knee society score after total knee arthroplasty. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Lampe, Frank; Fiedler, Franziska; Marques, Carlos; Sufi-Siavach, Anusch; Matziolis, Georg
• Is Part Of: BMC musculoskeletal disorders. Volume 17:Issue 1(2016)
• Page Start: 1
• Page End: 8
• Publication Date: 2016-12
• Subjects: Total knee replacement -- Computer-assisted surgery -- Prognosis -- Outcome assessment; Musculoskeletal system -- Diseases -- Periodicals; 616.705
• DOI: 10.1186/s12891-016-0929-7
• Languages: English
• ISSNs: 1471-2474

Abstract

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.