Digital Biomarkers of Mobility in Parkinson's Disease During Daily Living.
Digital Biomarkers of Mobility in Parkinson's Disease During Daily Living.
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日常生活中帕金森氏病的数字生物标志物。
DOI：
10.3233/jpd-201914
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Curtze C
中科院分区：
文献类型：
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作者：
Shah VV;McNames J;Mancini M;Carlson-Kuhta P;Nutt JG;El-Gohary M;Lapidus JA;Horak FB;Curtze C
识别移动性的数字生物标记物对于帕金森病(PD)的临床试验非常重要。确定在持续监测一周后，哪些数字结果指标可以区分帕金森病患者和健康对照(HC)受试者的活动能力。我们招募了29名帕金森病患者和27名年龄匹配的HC受试者。受试者被要求佩戴三个连接在双脚和腰部的惯性传感器(OPAL，APDM)，其中一组受试者也佩戴两个手腕传感器，持续监测一周。我们得出了43项移动性的数字结果衡量标准，分为五个领域。对于每一项数字结果的流动性测量，计算曲线下面积(AUC)，并使用Logistic回归找出区分PD和HC的流动性的测量组合。PD组记录时间为66±14小时，HC组为59±16小时。在总共43个移动性数字结果指标中，我们发现了6个数字结果指标，AUC>；为0.80。转角(AUC=0.89，95%CI：0.79~0.97)和摆动时间变异性(AUC=0.87，95%CI：0.75~0.96)是最具区分性的单项指标。通过最好的子集策略来选择最一致的转身措施，以区分帕金森病患者和HC患者，其次是步态可变性指标。帕金森病患者日常生活活动的数字生物标记物的临床研究和临床实践应包括转向和变异性测量。
Identifying digital biomarkers of mobility is important for clinical trials in Parkinson’s disease (PD). To determine which digital outcome measures of mobility discriminate mobility in people with PD from healthy control (HC) subjects over a week of continuous monitoring. We recruited 29 people with PD, and 27 age-matched HC subjects. Subjects were asked to wear three inertial sensors (Opal by APDM) attached to both feet and to the lumbar region, and a subset of subjects also wore two wrist sensors, for a week of continuous monitoring. We derived 43 digital outcome measures of mobility grouped into five domains. An Area Under Curve (AUC) was calculated for each digital outcome measures of mobility, and logistic regression employing a ‘best subsets selection strategy’ was used to find combinations of measures that discriminated mobility in PD from HC. Duration of recordings was 66±14 hours in the PD and 59±16 hours in the HC. Out of a total of 43 digital outcome measures of mobility, we found six digital outcome measures of mobility with AUC>0.80. Turn angle (AUC=0.89, 95% CI: 0.79–0.97) and swing time variability (AUC=0.87, 95% CI: 0.75–0.96) were the most discriminative individual measures. Turning measures were most consistently selected via the best subsets strategy to discriminate people with PD from HC, followed by gait variability measures. Clinical studies and clinical practice with digital biomarkers of daily life mobility in PD should include turning and variability measures.