Intelligence Quotient and Cognitive Fatigue are Independent Predictors of Cognitive Deficit in Pediatric MS Patients

Background: 30% of all pediatric MS patients develop cognitive impairment. This mainly concerns the cognitive domains of attention, processing speed, verbal fluidity and executive functions. The aim of this study was to examine the extent to which the total intelligence quotient (IQ), the extent of depression and fatigue, and clinical parameters are associated with cognitive impairment (below-average score ≥ 3 tests) and performance in cognitive domains.

Material and Methods: In a population of 106 pediatric MS patients and 210 controls, clinical parameters, total IQ, memory (VLMT), processing speed/attention (TMT-A/TMT-B), executive functions (RWT), visual-spatial perception (ROF), working memory (ZSP/BSP), and attention (SDMT), as well as the extent of depression (BDI-II) and fatigue (PedsQL Multidimensional Fatigue Scale) were assessed. In a subgroup of an IQ- and age-matched cohort of 99 MS patients and 99 controls, predictors of KD were investigated. Logistic regressions and multivariate covariance analyses were performed.

Results: MS patients had a significantly lower IQ (103.99 vs. 112.21; p < 0.001), stronger fatigue symptoms (61.5 vs. 77.01; p < .001), more depressive symptoms (BDI-II: 9.74 vs. 6.87; p = 0.009), and more often a cognitive deficit (28.3% vs. 15.2%; p = .007) than controls. In the IQ and age-matched cohort, significant bivariate relationships between depression and cognitive impairment (r = .158; p = .047) were found for the total sample of patients and controls, as well as a bivariate relationship between total fatigue and cognitive impairment (r = -.207, p = .040) for the sample of patients. However, these correlations were not significant after controlling for IQ. In a logistic regression analysis with the predictors depression, total fatigue and IQ, the IQ value was the only significant predictor of cognitive impairment (eb= .912 [AI: .862 - .964], p = .001). An analysis of the different dimensions of fatigue showed that cognitive fatigue was associated with cognitive impairment (logistic regression: eb= .965 [CI: .940 - .990], p = .007), while the other two dimensions (physical fatigue and resting/fatigue) had no significant association with cognitive impairment. Furthermore, the association between cognitive fatigue and cognitive impairment within the sub-sample of patients remained significant after controlling for IQ (r = -.214, p = .034). Clinical parameters (age at diagnosis, number of relapses, EDSS value, frequency of relapses) showed no associations with cognitive impairment.

Summary: The total IQ and cognitive fatigue are two independent predictors for the occurrence of cognitive impairment. Low IQ values and cognitive fatigue are associated with the risk of cognitive deficit.

No conflict of interest has been declared by the author(s).