Nörolojik Rehabilitasyonda Yorgunluk: Beyin Çeşitliliği ve Nüfus Çeşitliliği Neden Önemlidir?

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BackgroundFatigue affects 50% to 90% of patients with multiple sclerosis, Parkinson's disease, stroke, ME/CFS, and long COVID and represents a primary barrier to rehabilitation participation yet remains poorly understood despite decades of research.The problemSystematic examination of recent comprehensive reviews reveals a dual diversity failure. Brain diversity is underexamined: fatigue, fundamentally a central nervous system symptom, is assessed predominantly through questionnaires (95%-100% of studies) and peripheral biomarkers, while functional neuroimaging appears in fewer than 15% of studies. Population diversity is neglected: reviews consistently document a predominance of Western European and North American cohorts, with racial and ethnic composition inconsistently reported and demographic stratification virtually absent.The solutionIdentical fatigue scores reflect heterogeneous brain mechanisms, basal ganglia hypometabolism, frontal dysfunction, inflammatory network disruption, and differentially distributed across populations. Five testable predictions distinguish this framework: (1) neuroimaging reveals distinct subtypes; (2) subtypes show different clinical phenotypes; (3) treatment responses vary by subtype; (4) populations differ in subtype distribution; and (5) stratification resolves apparently inconsistent findings.RecommendationsFatigue rehabilitation research should (1) incorporate multimodal neuroimaging as standard, with a tiered protocol accommodating participant burden; (2) intentionally recruit demographically diverse populations; (3) employ data-driven clustering to identify brain-based subtypes; and (4) conduct mechanism-stratified treatment trials. An illustrative study design incorporating multimodal neuroimaging, comprehensive clinical and biological assessment, and diverse population sampling can test core predictions within existing research infrastructure.ImpactMechanism-based patient stratification enables precision rehabilitation, reducing required trial sample sizes while identifying effective interventions and preventing harm in vulnerable subgroups.

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