George Steven Z, Lentz Trevor A, Beneciuk Jason M, Bhavsar Nrupen A, Mundt Jennifer M, Boissoneault Jeff
Department of Orthopaedic Surgery, Duke Clinical Research Institute, Duke University, Durham, NC, USA.
Department of Physical Therapy, University of Florida, Gainesville, FL, USA.
Pain Rep. 2020 Mar 4;5(2):e809. doi: 10.1097/PR9.0000000000000809. eCollection 2020 Mar-Apr.
Clinical practice guidelines and the Federal Pain Research Strategy (United States) have recently highlighted research priorities to lessen the public health impact of low back pain (LBP). It may be necessary to improve existing predictive approaches to meet these research priorities for the transition from acute to chronic LBP. In this article, we first present a mapping review of previous studies investigating this transition and, from the characterization of the mapping review, present a predictive framework that accounts for limitations in the identified studies. Potential advantages of implementing this predictive framework are further considered. These advantages include (1) leveraging routinely collected health care data to improve prediction of the development of chronic LBP and (2) facilitating use of advanced analytical approaches that may improve prediction accuracy. Furthermore, successful implementation of this predictive framework in the electronic health record would allow for widespread testing of accuracy resulting in validated clinical decision aids for predicting chronic LBP development.
临床实践指南和《联邦疼痛研究战略》（美国）最近强调了研究重点，以减轻腰痛（LBP）对公众健康的影响。可能有必要改进现有的预测方法，以满足从急性LBP转变为慢性LBP的这些研究重点。在本文中，我们首先对以往研究这一转变的研究进行了映射综述，并根据映射综述的特征，提出了一个考虑到已确定研究局限性的预测框架。进一步考虑了实施这一预测框架的潜在优势。这些优势包括：（1）利用常规收集的医疗保健数据来改善对慢性LBP发展的预测；（2）促进使用可能提高预测准确性的先进分析方法。此外，在电子健康记录中成功实施这一预测框架将允许对准确性进行广泛测试，从而产生经过验证的用于预测慢性LBP发展的临床决策辅助工具。
