Department of Neurology, Hospital Clinico San Carlos, San Carlos Institute for Health Research (IdiSSC). Universidad Complutense, Profesor Martin Lagos St., Madrid 28040, Spain.
Department of Neurology, Hospital Clinico San Carlos, San Carlos Institute for Health Research (IdiSSC). Universidad Complutense, Profesor Martin Lagos St., Madrid 28040, Spain.
Mult Scler Relat Disord. 2022 Jul;63:103826. doi: 10.1016/j.msard.2022.103826. Epub 2022 Apr 23.
Fatigue is one of the most common symptoms in neurology, especially in MS patients with a prevalence of 65%. It is described as the most disabling symptom by 40% of MS patients. This study aimed to validate the Functional Assessment of Chronic Illness Therapy fatigue version (FACIT-F) and the F-2-MS scale, a new tool to distinguish between fatigue and fatigability.
One hundred and fifteen patients with relapsing-remitting MS were enrolled. All patients completed a comprehensive neuropsychological battery, previously validated in MS. Fatigue was evaluated using the Fatigue Severity Scale (FSS), the Modified version of the Fatigue Impact Scale (MFIS), the Functional Assessment of Chronic Illness Therapy measure system (fatigue version) (FCIT-F), and a new tool for the assessment of fatigue and fatigability: the F-2-MS scale. Internal consistency was estimated with Cronbach's Alpha. For intergroup comparisons, Student's t-test and Pearson's chi-squared test were used. Pearson's correlation test was calculated for quantitative variables. Cohen's d was calculated to evaluate the effect size. Binary logistic regression was performed, considering the presence of fatigue as a criterion variable, and the FACIT-F and F-2-MS scores were added as predictor variables. ROC curves were also estimated. We conducted a confirmatory factor analysis for the F-2-MS scale, considering two latent factors.
FACIT-F and F-2-MS showed high internal consistency. Both scales were highly correlated with MFIS and FSS, and showed a low correlation with Symbol Digit Modalities Test. There were significant differences between fatigued and non-fatigued patients on FACIT-F and F-2-MS scores with large effect sizes. Both scales showed AUC > 0.90 and achieved a correct classification >87%. Confirmatory factor analysis showed moderate evidence of two dimensions on the F-2-MS scale.
The FACIT-F and F-2-MS scales showed appropriated psychometric properties to be used as fatigue measures in clinical and research settings, allowing a correct distinction between patients with and without fatigue, and contributing to the understanding of the complexities of fatigue in MS.
疲劳是神经病学中最常见的症状之一,尤其是在多发性硬化症(MS)患者中,其患病率为 65%。有 40%的 MS 患者将其描述为最具致残性的症状。本研究旨在验证慢性疾病治疗功能评估疲劳量表(FACIT-F)和 F-2-MS 量表,这是一种用于区分疲劳和易疲劳的新工具。
共纳入 115 例复发缓解型 MS 患者。所有患者均完成了先前在 MS 中验证过的全面神经心理学测试。使用疲劳严重程度量表(FSS)、疲劳影响量表(MFIS)修订版、慢性疾病治疗功能评估测量系统(疲劳量表)(FACIT-F)以及用于评估疲劳和易疲劳的新工具:F-2-MS 量表评估疲劳。采用 Cronbach's Alpha 评估内部一致性。对于组间比较,使用 Student's t 检验和 Pearson's 卡方检验。对定量变量进行 Pearson 相关检验。用 Cohen's d 评估效应大小。考虑疲劳的存在作为分类变量,将 FACIT-F 和 F-2-MS 评分作为预测变量进行二元逻辑回归。还估计了 ROC 曲线。我们对 F-2-MS 量表进行了验证性因素分析,考虑了两个潜在因素。
FACIT-F 和 F-2-MS 具有较高的内部一致性。这两个量表与 MFIS 和 FSS 高度相关,与符号数字模态测验相关性较低。在 FACIT-F 和 F-2-MS 评分上,疲劳患者与非疲劳患者之间存在显著差异,且效应大小较大。两个量表的 AUC 均>0.90,正确分类率>87%。验证性因素分析表明 F-2-MS 量表存在中等程度的两个维度证据。
FACIT-F 和 F-2-MS 量表具有适当的心理测量学特性,可用于临床和研究环境中的疲劳评估,能够正确区分有疲劳和无疲劳的患者,并有助于理解 MS 中疲劳的复杂性。