Multiple sclerosis (Houndmills, Basingstoke, England) · 2020
A novel classification of fatigue in multiple sclerosis based on longitudinal assessments.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Palotai Miklos, Cavallari Michele, Healy Brian C, Guttmann Charles Rg
Аннотация
BACKGROUND: Magnetic resonance imaging (MRI) studies of multiple sclerosis-related fatigue had limited reproducibility. Temporal fatigue fluctuations have not been considered.
OBJECTIVE: To investigate whether a novel group allocation that reflects temporal dynamics of fatigue improves our ability to detect fatigue-associated structural brain abnormalities.
METHODS: Patient stratification based on biennial fatigue assessments: sustained fatigue (SF, n = 29, fatigued at the latest ⩾2 assessments), one time-point fatigue (1F, n = 15, fatigued at the latest, but non-fatigued at the penultimate assessment), reversible fatigue (RF, n = 31, non-fatigued at the latest assessment, but reported fatigue previously), and never fatigued (NF, n = 54). Brain parenchymal fraction (BPF) and T2 lesion volume (T2LV) were compared between these groups and were derived using a conventional, single time-point fatigued versus non-fatigued stratification.
RESULTS: The SF versus NF stratification yielded improved power. SF (p = 0.005) and RF (p = 0.043) showed significantly higher T2LV than NF. T2LV showed no significant differences in SF versus 1F, SF versus RF, or 1F versus RF. Fatigued versus non-fatigued patients showed significantly higher T2LV (p = 0.030). We found no significant differences in BPF between the groups.
CONCLUSION: Taking into account temporal fatigue dynamics increases the statistical power with respect to T2LV and may improve characterization of brain pathological correlates of MS-related fatigue.
OBJECTIVE: To investigate whether a novel group allocation that reflects temporal dynamics of fatigue improves our ability to detect fatigue-associated structural brain abnormalities.
METHODS: Patient stratification based on biennial fatigue assessments: sustained fatigue (SF, n = 29, fatigued at the latest ⩾2 assessments), one time-point fatigue (1F, n = 15, fatigued at the latest, but non-fatigued at the penultimate assessment), reversible fatigue (RF, n = 31, non-fatigued at the latest assessment, but reported fatigue previously), and never fatigued (NF, n = 54). Brain parenchymal fraction (BPF) and T2 lesion volume (T2LV) were compared between these groups and were derived using a conventional, single time-point fatigued versus non-fatigued stratification.
RESULTS: The SF versus NF stratification yielded improved power. SF (p = 0.005) and RF (p = 0.043) showed significantly higher T2LV than NF. T2LV showed no significant differences in SF versus 1F, SF versus RF, or 1F versus RF. Fatigued versus non-fatigued patients showed significantly higher T2LV (p = 0.030). We found no significant differences in BPF between the groups.
CONCLUSION: Taking into account temporal fatigue dynamics increases the statistical power with respect to T2LV and may improve characterization of brain pathological correlates of MS-related fatigue.