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基于质量登记数据的全髋关节置换术后一年健康相关生活质量共享决策工具的开发与验证

Development and validation of a shared decision-making instrument for health-related quality of life one year after total hip replacement based on quality registries data.

作者信息

Nemes Szilard, Rolfson Ola, Garellick Göran

机构信息

Swedish Hip Arthroplasty Register, Gothenburg, Sweden.

Department of Orthopaedics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.

出版信息

J Eval Clin Pract. 2018 Feb;24(1):13-21. doi: 10.1111/jep.12603. Epub 2016 Jul 27.

Abstract

RATIONALE, AIMS AND OBJECTIVES: Clinicians considering improvements in health-related quality of life (HRQoL) after total hip replacement (THR) must account for multiple pieces of information. Evidence-based decisions are important to best assess the effect of THR on HRQoL. This work aims at constructing a shared decision-making tool that helps clinicians assessing the future benefits of THR by offering predictions of 1-year postoperative HRQoL of THR patients.

METHODS

We used data from the Swedish Hip Arthroplasty Register. Data from 2008 were used as training set and data from 2009 to 2012 as validation set. We adopted two approaches. First, we assumed a continuous distribution for the EQ-5D index and modelled the postoperative EQ-5D index with regression models. Second, we modelled the five dimensions of the EQ-5D and weighted together the predictions using the UK Time Trade-Off value set. As predictors, we used preoperative EQ-5D dimensions and the EQ-5D index, EQ visual analogue scale, visual analogue scale pain, Charnley classification, age, gender, body mass index, American Society of Anesthesiologists, surgical approach and prosthesis type. Additionally, the tested algorithms were combined in a single predictive tool by stacking.

RESULTS

Best predictive power was obtained by the multivariate adaptive regression splines (R  = 0.158). However, this was not significantly better than the predictive power of linear regressions (R  = 0.157). The stacked model had a predictive power of 17%.

CONCLUSIONS

Successful implementation of a shared decision-making tool that can aid clinicians and patients in understanding expected improvement in HRQoL following THR would require higher predictive power than we achieved. For a shared decision-making tool to succeed, further variables, such as socioeconomics, need to be considered.

摘要

原理、目的和目标:考虑全髋关节置换术(THR)后健康相关生活质量(HRQoL)改善情况的临床医生必须综合多方面信息。基于证据的决策对于最佳评估THR对HRQoL的影响至关重要。这项工作旨在构建一个共享决策工具,通过预测THR患者术后1年的HRQoL,帮助临床医生评估THR的未来益处。

方法

我们使用了瑞典髋关节置换登记处的数据。2008年的数据用作训练集,2009年至2012年的数据用作验证集。我们采用了两种方法。首先,我们假设EQ-5D指数呈连续分布,并使用回归模型对术后EQ-5D指数进行建模。其次,我们对EQ-5D的五个维度进行建模,并使用英国时间权衡价值集对预测结果进行加权汇总。作为预测指标,我们使用术前EQ-5D维度、EQ-5D指数、EQ视觉模拟量表、视觉模拟疼痛量表、Charnley分类、年龄、性别、体重指数、美国麻醉医师协会分级、手术方式和假体类型。此外,通过堆叠将经过测试的算法组合在一个单一的预测工具中。

结果

多元自适应回归样条法获得了最佳预测能力(R = 0.158)。然而,这并不比线性回归的预测能力(R = 0.157)显著更好。堆叠模型的预测能力为17%。

结论

要成功实施一个能够帮助临床医生和患者理解THR后HRQoL预期改善情况的共享决策工具,需要比我们所达到的更高的预测能力。对于一个成功的共享决策工具而言,需要考虑更多变量,如社会经济学因素。

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