Jason Leonard A, Sunnquist Madison, Brown Abigail, Evans Meredyth, Vernon Suzanne D, Furst Jacob, Simonis Valerie
Center for Community Research, DePaul University, Chicago, IL USA.
The CFIDS Association of America.
Fatigue. 2014 Jan 1;2(1):40-56. doi: 10.1080/21641846.2013.862993.
Considerable controversy has transpired regarding the core features of myalgic encephalomyelitis (ME) and chronic fatigue syndrome (CFS). Current case definitions differ in the number and types of symptoms required. This ambiguity impedes the search for biological markers and effective treatments.
This study sought to empirically operationalize symptom criteria and identify which symptoms best characterize the illness.
Patients (=236) and controls (=86) completed the DePaul Symptom Questionnaire, rating the frequency and severity of 54 symptoms. Responses were compared to determine the threshold of frequency/severity ratings that best distinguished patients from controls. A Classification and Regression Tree (CART) algorithm was used to identify the combination of symptoms that most accurately classified patients and controls.
A third of controls met the symptom criteria of a common CFS case definition when just symptom presence was required; however, when frequency/severity requirements were raised, only 5% met criteria. Employing these higher frequency/severity requirements, the CART algorithm identified three symptoms that accurately classified 95.4% of participants as patient or control: fatigue/extreme tiredness, inability to focus on multiple things simultaneously, and experiencing a dead/heavy feeling after starting to exercise.
Minimum frequency/severity thresholds should be specified in symptom criteria to reduce the likelihood of misclassification. Future research should continue to seek empirical support of the core symptoms of ME and CFS to further progress the search for biological markers and treatments.
关于肌痛性脑脊髓炎(ME)和慢性疲劳综合征(CFS)的核心特征,已经出现了相当多的争议。目前的病例定义在所需症状的数量和类型上有所不同。这种模糊性阻碍了生物标志物的寻找和有效治疗方法的探索。
本研究旨在通过实证方法确定症状标准,并找出最能表征该疾病的症状。
患者(=236例)和对照组(=86例)完成了德保罗症状问卷,对54种症状的发生频率和严重程度进行评分。比较两组的回答,以确定最能区分患者和对照组的频率/严重程度评分阈值。使用分类与回归树(CART)算法来确定最准确区分患者和对照组的症状组合。
当仅要求存在症状时,三分之一的对照组符合常见CFS病例定义中的症状标准;然而,当提高频率/严重程度要求时,只有5%符合标准。采用这些更高的频率/严重程度要求,CART算法确定了三种症状,这些症状能将95.4%的参与者准确分类为患者或对照组:疲劳/极度疲倦、无法同时专注于多件事情以及开始运动后出现乏力/沉重感。
症状标准中应规定最低频率/严重程度阈值,以降低错误分类的可能性。未来的研究应继续寻求ME和CFS核心症状的实证支持,以进一步推进生物标志物和治疗方法的探索。