Jason Leonard A, Kot Bobby, Sunnquist Madison, Brown Abigail, Evans Meredyth, Jantke Rachel, Williams Yolonda, Furst Jacob, Vernon Suzanne D
DePaul University.
Solve ME/CFS Initiative.
Health Psychol Behav Med. 2015;3(1):82-93. doi: 10.1080/21642850.2015.1014489.
Current case definitions of Myalgic Encephalomyelitis (ME) and chronic fatigue syndrome (CFS) have been based on consensus methods, but empirical methods could be used to identify core symptoms and thereby improve the reliability. In the present study, several methods (i.e., continuous scores of symptoms, theoretically and empirically derived cut off scores of symptoms) were used to identify core symptoms best differentiating patients from controls. In addition, data mining with decision trees was conducted. Our study found a small number of core symptoms that have good sensitivity and specificity, and these included fatigue, post-exertional malaise, a neurocognitive symptom, and unrefreshing sleep. Outcomes from these analyses suggest that using empirically selected symptoms can help guide the creation of a more reliable case definition.
目前，肌痛性脑脊髓炎（ME）和慢性疲劳综合征（CFS）的病例定义是基于共识方法制定的，但也可以采用实证方法来识别核心症状，从而提高其可靠性。在本研究中，我们运用了多种方法（即症状的连续评分、理论和实证推导的症状截断分数）来识别最能区分患者与对照的核心症状。此外，还进行了决策树数据挖掘。我们的研究发现了少数具有良好敏感性和特异性的核心症状，这些症状包括疲劳、劳累后不适、一种神经认知症状以及睡眠不能解乏。这些分析结果表明，使用经实证选择的症状有助于指导创建更可靠的病例定义。
