形状记忆合金*
组内相关
脊髓性肌萎缩
物理医学与康复
医学
物理疗法
同时有效性
可靠性(半导体)
神经肌肉疾病
收敛有效性
运动功能
疾病
心理测量学
内科学
计算机科学
临床心理学
功率(物理)
物理
算法
量子力学
内部一致性
作者
Thanneer M. Perumal,Detlef Wolf,Doris Berchtold,Grégoire Pointeau,Yanping Zhang,Wei‐Yi Cheng,Florian Lipsmeier,Jörg Sprengel,Christian Czech,Claudia A. Chiriboga,Michael Lindemann
标识
DOI:10.1016/j.nmd.2023.07.008
摘要
Spinal muscular atrophy (SMA) is characterized by progressive muscle weakness and paralysis. Motor function is monitored in the clinical setting using assessments including the 32-item Motor Function Measure (MFM-32), but changes in disease severity between clinical visits may be missed. Digital health technologies may assist evaluation of disease severity by bridging gaps between clinical visits. We developed a smartphone sensor-based assessment suite, comprising nine tasks, to assess motor and muscle function in people with SMA. We used data from the risdiplam phase 2 JEWELFISH trial to assess the test-retest reliability and convergent validity of each task. In the first 6 weeks, 116 eligible participants completed assessments on a median of 6.3 days per week. Eight of the nine tasks demonstrated good or excellent test-retest reliability (intraclass correlation coefficients >0.75 and >0.9, respectively). Seven tasks showed a significant association (P < 0.05) with related clinical measures of motor function (individual items from the MFM-32 or Revised Upper Limb Module scales) and seven showed significant association (P < 0.05) with disease severity measured using the MFM-32 total score. This cross-sectional study supports the feasibility, reliability, and validity of using smartphone-based digital assessments to measure function in people living with SMA.
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