患者特异性疼痛模型用于识别TKA后风险患者

Ricardo Antunes, P. Jacob, Bob Marchand, Elaine Justice, Kelly B. Taylor, E. Hampp, Matthias Verstraete
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引用次数: 0

摘要

远程患者监测使临床医生能够了解患者的康复情况,而不仅仅是在诊所就诊。患者的疼痛管理是全膝关节置换术(TKA)后康复的一个重要方面,并且越来越多地通过数字应用程序远程跟踪。及时的评估可以为临床医生提供一种发现术后并发症的方法。我们提出了一个患者特异性模型,该模型预测了TKA患者在90天恢复期远程收集疼痛评分的概率,旨在检测异常疼痛评分的患者,并使临床医生能够及时进行适当的干预。我们对84例接受单侧原发性TKA的患者进行了4,782组远程收集的疼痛评分,并对该模型进行了拟合和验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Patient-Specific Pain Model for Identifying Patients at Risk Following TKA
Remote patient monitoring provides clinicians with visibility to patients’ recovery beyond what can be achieved with in clinic visits alone. Patients’ pain management is an important aspect of recovery following total knee arthroplasty (TKA), and one that is increasingly tracked remotely through digital applications. Its timely assessment may provide clinicians with a way to detect postoperative complications. We proposed a patient-specific model that predicts the probability of remotely collected pain scores for TKA patients along a 90-day recovery period, aimed at detecting patients with anomalous pain scores, and enable appropriate interventions by clinicians in a timely manner. We fitted and validated the model with a set of 4,782 remotely collected pain scores for 84 patients that underwent unilateral primary TKA.
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