Artikel
Validity of Published Outcome Data concerning Anatomical Graduated Components Total Knee Arthroplasty a structured Literature Review including Arthroplasty Register Data
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Veröffentlicht: | 18. Oktober 2011 |
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Gliederung
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Questionnaire: Total knee arthroplasty (TKA) reveals good results in terms of patient's satisfaction for the treatment of end-stage osteoarthritis of the knee. There exist two major data sources for the assessment of outcome and revision rate after total joint arthroplasty, n clinical studies and national arthroplasty registers. The purpose of the present study was to analyse the outcome of Anatomical Graduated Components (AGC) TKA reported in clinical studies and to perform a comparison with the outcome reported by National Arthroplasty registers.
Methods: A systematic literature rewiew was performed using a standardized methology in order to determine the outcome and revision rate of AGC TKA. A comprehensive meta-analysis of clinical studies and worldwide register results were checked for quality of basic data and potential bias factors. Confidence intervals were calculated to determine the statistical significance of difference.
Results and Conclusions: We found significant differences between the revision rate in terms of revisions per 100 observed component years was significantly lower in clinical studies from the development team of the implant compared to worldwide register data. In fact, they reported a revision rate of 0.18 revisions per 100 observed component years whereas Annual reports of national arthroplasty registers report 0.74 revisions per 100 observed component years. A comparison of results from national arthroplasty registers of different countries revealed a significantly higher revision rate for Denmark compared to worldwide register data.
A conventional meta-analysis of clinical studies is affected by the influence of the development team and therefore subject of bias. For the assessment of outcome are to be rated superior, and, in terms of reference data for the detection of potential bias factors in the clinical literature, could make an essential contribution to scientific meta-analysis.