Background and purposeCognitive impairment is a common sequel of recent small subcortical infarction (RSSI) and might be negatively affected by preexisting cerebral small vessel disease (SVD). We investigated whether the course of cognitive function in patients with RSSI is influenced by the severity of white matter hyperintensities (WMH), an important imaging feature of SVD.MethodsPatients with magnetic resonance imaging (MRI)‐proven single RSSI were tested neuropsychologically concerning global cognition, processing speed, attention, and set‐shifting. Deep and periventricular WMH severity was assessed using the Fazekas scale, and total WMH lesion volume was calculated from T1‐weighted MRI images. We compared baseline function and course of cognition 15 months after the acute event in patients with absent, mild, and moderate‐to‐severe WMH.ResultsThe study cohort comprised 82 RSSI patients (mean age: 61 ± 10 years, 23% female). At baseline, 40% had cognitive impairment (1.5 standard deviations below standardized mean), and deficits persisted in one‐third of the sample after 15 months. After age correction, there were no significant differences in set‐shifting between WMH groups at baseline. However, although patients without WMH (deep: p < 0.001, periventricular: p = 0.067) or only mild WMH (deep: p = 0.098, periventricular: p = 0.001) improved in set‐shifting after 15 months, there was no improvement in patients with moderate‐to‐severe WMH (deep: p = 0.980, periventricular: p = 0.816). Baseline total WMH volume (p = 0.002) was the only significant predictor for attention 15 months poststroke.ConclusionsThis longitudinal study demonstrates that preexisting moderate‐to‐severe WMH negatively affect the restoration of cognitive function after RSSI, suggesting limited functional reserve in patients with preexisting SVD.

Background: Efficient treatment of modifiable vascular risk factors decreases reoccurrence of ischemic stroke, which is of uttermost importance in younger patients. In this longitudinal pilot study, we thus assessed the effect of a newly developed smartphone app for risk factor management in such a cohort.Methods: The app conveys key facts about stroke, provides motivational support for a healthy lifestyle, and a reminder function for medication intake and blood pressure measurement. Between January 2019 and February 2020, we consecutively invited patients with ischemic stroke aged between 18 and 55 years to participate. Patients in the intervention group used the app between hospital discharge and 3-month follow-up. The control group received standard clinical care. Modifiable risk factors (physical activity, nutrition, alcohol consumption, smoking behavior, obesity, and hypertension) were assessed during the initial hospital stay and at a dedicated stroke outpatient department three months post-stroke.Results: The study cohort comprised 21 patients in the app intervention group (62% male; age = 41 ± 11 years; education = 12 ± 3 years) and 21 sex-, age- and education-matched control patients with a comparable stroke risk factor profile. Baseline stroke severity was comparable between groups (intervention: median NIHSS = 3; control: median NIHSS = 4; p = 0.604). Three months post-stroke, patients in the intervention group reported to be physically almost twice as active (13 ± 9 h/week) compared to controls (7 ± 5 h/week; p = 0.022). More intense app usage was strongly associated with higher physical activity (r = 0.60, p = 0.005) and lower consumption of unhealthy food (r = −0.51, p = 0.023). Smoking behavior (p = 0.001) and hypertension (p = 0.003) improved in all patients. Patients in the intervention group described better self-reported health-related quality of life three months post-stroke (p = 0.003).Conclusions: Specifically designed app interventions can be an easily to implement and cost-efficient approach to promote a healthier lifestyle in younger patients with a stroke.

Background: Cognitive impairment frequently occurs in patients with MS (pwMS). Magnetic resonance imaging (MRI) markers could help to identify patients at risk for decline. Objective: To characterize the long-term course and morphological MRI correlates of cognitive function in pwMS. Methods: We invited 116 pwMS who had undergone clinical, cognitive, and MRI evaluations between 2006 and 2012 (baseline, BL) to attend follow-up (FU) testing between 2016 and 2018. Disability (expanded disability status scale (EDSS)), cognition (brief repeatable battery of neuropsychological test (BRB-N)), global and regional T2-lesion load (T2-LL), brain volumes, and cortical thickness were assessed. Results: Sixty-three pwMS were willing to attend the FU (54%; median EDSS = 2, interquartile range (IQR) = 2) and did not differ from non-participating pwMS regarding BL characteristics. At BL, half of the participants showed cognitive deficits in at least one domain. Across the entire group, we observed no relevant changes in physical disability and cognition over 10 years. BL thalamic volume best predicted cognitive function at FU, in addition to age and BL cognition, explaining 67% of variance. Cognitive decliners (23.8%) were older, had longer disease duration, and a tendency for lower thalamic volume at BL. Conclusion: Thalamic volume predicted FU cognitive function and distinguished declining from stable pwMS, underlining the potential of MRI to define risk groups.

Objective Neurofeedback training may improve cognitive function in patients with neurological disorders. However, the underlying cerebral mechanisms of such improvements are poorly understood. Therefore, we aimed to investigate MRI correlates of cognitive improvement after EEG-based neurofeedback training in patients with MS (pwMS). Methods Fourteen pwMS underwent ten neurofeedback training sessions within 3–4 weeks at home using a tele-rehabilitation system. Half of the pwMS (N = 7, responders) learned to self-regulate sensorimotor rhythm (SMR, 12–15 Hz) by visual feedback and improved cognitively after training, whereas the remainder (non-responders, n = 7) did not. Diffusion-tensor imaging and resting-state fMRI of the brain was performed before and after training. We analyzed fractional anisotropy (FA) and functional connectivity (FC) of the default-mode, sensorimotor (SMN) and salience network (SAL). Results At baseline, responders and non-responders were comparable regarding sex, age, education, disease duration, physical and cognitive impairment, and MRI parameters. After training, compared to non-responders, responders showed increased FA and FC within the SAL and SMN. Cognitive improvement correlated with increased FC in SAL and a correlation trend with increased FA was observed. Conclusions This exploratory study suggests that successful neurofeedback training may not only lead to cognitive improvement, but also to increases in brain microstructure and functional connectivity.

Zusammenfassung Laut der INTERSTROKE Studie werden etwa 90 % des Risikos für einen ischämischen Schlaganfall durch beeinflussbare Risikofaktoren (z. B. Bluthochdruck, Übergewicht, Rauchen) bedingt. Durch eine Verringerung dieser Faktoren könnte das Schlaganfallrisiko deutlich gesenkt werden. Um die Effektivität von Smartphone Apps zur Sekundärprävention nach Schlaganfall in Bezug auf beeinflussbare Risikofaktoren und die Einstellung von Zusatzmaterial online Zusätzliche Informationen sind in der Online-Version dieses Artikels (