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首页> 外文期刊>Journal of neurology >In search of distinct MS-related fatigue subtypes: results from a multi-cohort analysis in 1.403 MS patients
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In search of distinct MS-related fatigue subtypes: results from a multi-cohort analysis in 1.403 MS patients

机译:寻找不同的MS相关疲劳亚型:1.403 ms患者的多队列分析结果

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Fatigue is among the most disabling symptoms in patients with multiple sclerosis (PwMS). The common distinction between cognitive and motor fatigue is typically incorporated in self-rating instruments, such as the Chalder Fatigue Questionnaire (CFQ), the Fatigue Scale for Motor and Cognitive Functions (FSMC) or the Modified Fatigue Impact Scale (MFIS). The present study investigated the factor structure of the CFQ, the FSMC and the MFIS utilizing exploratory (EFA) and confirmatory factor analysis (CFA) as well as exploratory structural equation modeling (ESEM). Data of 1.403 PwMS were analyzed, utilizing four samples. The first sample (N=605) was assessed online and split into two stratified halves to perform EFA, CFA, and ESEM on the CFQ and FSMC. The second sample (N=293) was another online sample. It served to calculate CFA and ESEM on the CFQ and FSMC. The third sample was gathered in a clinical setting (N=196) and analyzed by applying CFA and ESEM to the FSMC. The fourth sample (N=309) was assessed in a clinical setting and allowed to run a CFA and ESEM on the MFIS. Proposed factor structures of all questionnaires were largely confirmed in EFA. However, none of the calculated CFAs and ESEMs could verify the proposed factor structures of the three measures, even with oblique rotation techniques. The findings might have implications for future research into the pathophysiological basis of MS-related fatigue and could affect the suitability of such measures as outcomes for treatment trials, presumably targeting specific sub-components of fatigue.
机译:疲劳是多发性硬化症(PWMS)患者中最致残的症状之一。认知和电机疲劳之间的共同区别通常以自评仪器掺入,例如脱钙疲劳问卷(CFQ),电动机和认知功能(FSMC)或改性疲劳冲击量表(MFI)的疲劳量表。本研究研究了CFQ,FSMC和MFI的因子结构利用探索性(EFA)和确认因子分析(CFA)以及探索结构方程模型(ESEM)。分析了1.403pWM的数据,利用四个样品。第一个样品(n = 605)在线评估并分为两个分层半部,以在CFQ和FSMC上进行EFA,CFA和ESEM。第二个样本(n = 293)是另一个在线样本。它可以在CFQ和FSMC上计算CFA和ESEM。第三个样品在临床环境中收集(n = 196),并通过将CFA和ESEM施加到FSMC来分析。在临床环境中评估第四样品(n = 309),并在MFIS上运行CFA和ESEM。所有调查问卷的拟议因素结构在很大程度上在EFA中得到了证实。然而,也没有计算出的CFA和EEMS可以验证三种措施的建议系数结构,即使具有斜旋转技术。该研究结果可能对未来的研究与MS相关疲劳的病理生理学基础有影响,并且可能影响这种措施作为治疗试验的结果的适用性,可能是针对疲劳的特定子组分。

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