Pourmoghaddam Amir, Dettmer Marius, Freedhand Adam M, Domingues Brian C, Kreuzer Stefan W
Memorial Bone & Joint Research Foundation, Department of Orthopaedic Surgery, The University of Texas Health Science Center at Houston-Medical School, Houston, Texas.
J Arthroplasty. 2015 Apr;30(4):622-6. doi: 10.1016/j.arth.2014.11.021. Epub 2014 Nov 26.
Application of digital radiography during preoperative templating has shown potential to reduce complications in total hip arthroplasty. In this study, we aimed to further improve digital templating by using a predictive model built on patients' specific data. The model was significant in improving the accuracy of templating within ±1 size of acetabular component (χ(2)(1, N=468)=19.314, P<0.0001, Φ=0.604, and odds-ratio: 7.750 (95% CI 2.740-30.220)). We successfully achieved a 99% accuracy within ±2 of templated size. Additionally, patient demographics, such as height and weight, have shown significant effects on the predictive model. The outcome of this study may help reducing the costs of health care in the long term by minimizing implant inventory costs.
术前模板制作过程中使用数字射线照相术已显示出降低全髋关节置换术并发症的潜力。在本研究中，我们旨在通过使用基于患者特定数据构建的预测模型来进一步改进数字模板制作。该模型在将髋臼组件模板尺寸的准确性提高到±1尺寸范围内具有显著意义（χ(2)(1, N = 468) = 19.314，P < 0.0001，Φ = 0.604，优势比：7.750（95% CI 2.740 - 30.220））。我们成功在模板尺寸±2范围内实现了99%的准确率。此外，患者的人口统计学特征，如身高和体重，对预测模型有显著影响。本研究结果可能有助于通过最小化植入物库存成本从长远角度降低医疗保健成本。
