Longitudinal changes in global structural brain connectivity and cognitive performance in former hospitalized COVID-19 survivors: an exploratory study.

BACKGROUND: Long-term sequelae of COVID-19 can result in reduced functionality of the central nervous system and substandard quality of life. Gaining insight into the recovery trajectory of admitted COVID-19 patients on their cognitive performance and global structural brain connectivity may allow a better understanding of the diseases' relevance. OBJECTIVES: To assess whole-brain structural connectivity in former non-intensive-care unit (ICU)- and ICU-admitted COVID-19 survivors over 2 months following hospital discharge and correlate structural connectivity measures to cognitive performance. METHODS: Participants underwent Magnetic Resonance Imaging brain scans and a cognitive test battery after hospital discharge to evaluate structural connectivity and cognitive performance. Multilevel models were constructed for each graph measure and cognitive test, assessing the groups' influence, time since discharge, and interactions. Linear regression models estimated whether the graph measurements affected cognitive measures and whether they differed between ICU and non-ICU patients. RESULTS: Six former ICU and six non-ICU patients completed the study. Across the various graph measures, the characteristic path length decreased over time (ß = 0.97, p = 0.006). We detected no group-level effects (ß = 1.07, p = 0.442) nor interaction effects (ß = 1.02, p = 0.220). Cognitive performance improved for both non-ICU and ICU COVID-19 survivors on four out of seven cognitive tests 2 months later (p < 0.05). CONCLUSION: Adverse effects of COVID-19 on brain functioning and structure abate over time. These results should be supported by future research including larger sample sizes, matched control groups of healthy non-infected individuals, and more extended follow-up periods.

The squares test as a measure of hand function in multiple sclerosis.

Deterioration of hand function can be important in multiple sclerosis (MS). The standard way of assessing hand function in MS is the 9-hole peg test (9HPT), one of the three components of the MS functional composite measure. In this study we examine the squares test (ST), a test of hand function that is used extensively in handedness research. We evaluated reproducibility of the ST in 49 healthy controls, and both discriminatory power and concurrent validity of the ST in 38 MS patients and 18 age and gender matched controls. The ST proved to be a reliable and easy to administrate paper-and-pencil test of hand function. The ST showed a high and highly significant correlation with the standard 9HPT over a broad range of Expanded Disability Status Scale (EDSS) scores, and had high discriminatory power, also comparable to the 9HPT. Therefore, the ST is a candidate test for use in composite measures of MS related functional deficits for clinical practice and in clinical trials.

The Symbol Digit Modalities Test as sentinel test for cognitive impairment in multiple sclerosis.

BACKGROUND AND PURPOSE: Cognitive impairment (CI) is found in about half of the multiple sclerosis (MS) population and is an important contributor to employment status and social functioning. CI is encountered in all disease stages and correlates only moderately with disease duration or Expanded Disability Status Scale scores. Most present neuropsychological test batteries are time-demanding and expensive. The Symbol Digit Modalities Test (SDMT) has been suggested as a screening tool for CI in MS. In this paper, we aim to assess the performance of the SDMT in predicting the outcome of an extensive battery. METHODS: Neuropsychological test results from 359 patients were assessed in a multidisciplinary MS center (National MS Center Melsbroek, Belgium). Using receiver operating characteristic curves, the performance of the SDMT in predicting the general cognitive outcome of the extensive Neuropsychological Screening Battery for MS (NSBMS) could be assessed. The performance of the SDMT was assessed for different levels of CI and compared with other cognitive tests. Finally, useful covariates were included in a logistic regression model. RESULTS: At a specificity of 0.60 a high sensitivity (0.91) was obtained indicating the potential of the SDMT as a sentinel test for CI in MS. The SDMT outperformed the individual tests included in the NSBMS, used as benchmark. As the logistic regression model did not result in a relevant improvement, it is concluded that most clinical variables influence both the SDMT and the NSBMS in a similar way. Excluding patients with possible practice effects, an optimal cutoff of 40 was found for the SDMT. CONCLUSION: As the SDMT is an easy, low-cost and fast test, this result may help to detect CI in everyday clinical practice.