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Background A fraction of patients with asymptomatic to mild/moderate acute COVID-19 disease report cognitive deficits as part of the post-COVID-19 syndrome. This study aimed to assess the neuropsychological profile of these patients. Methods Assessment at baseline (three months or more following acute COVID-19) of a monocentric prospective cohort of patients with post-COVID-19 syndrome. Multidomain neuropsychological tests were performed, and questionnaires on depression, anxiety, fatigue, sleep, and general health status were administered. Results Of the 58 patients screened, six were excluded due to possible alternative causes of cognitive impairment (major depression, neurodegenerative disease). Of the remaining 52 individuals, only one had a below-threshold screening result on Mini-Mental State Examination, and 13 scored below the cut-off on Montreal Cognitive Assessment. Extended neuropsychological testing revealed a neurocognitive disorder (NCD) in 31 (59.6%) participants with minor NCD in the majority of cases (n = 26). In patients with NCD, the cognitive domains learning/memory and executive functions were impaired in 60.7%, complex attention in 51.6%, language in 35.5%, and perceptual-motor function in 29.0%. Cognitive profiles were associated with daytime sleepiness but not with depression, anxiety, sleep quality, total general health status, or fatigue. Conclusion Neurocognitive impairment can be confirmed in around 60% of individuals with self-reported deficits as part of post-COVID-19 syndrome following a mild acute COVID-19 disease course. Notably, screening tests cannot reliably detect this dysfunction. Standard psychiatric assessments showed no association with cognitive profiles. Longitudinal studies are needed to further evaluate the course of neurocognitive deficits and clarify pathophysiology.

Introduction The early diagnosis of mild cognitive impairment (PD-MCI) in Parkinson's disease (PD) is essential as it increases the future risk for PD dementia (PDD). Recently, a novel weighting algorithm for the Montreal Cognitive Assessment (MoCA) subtests has been reported, to best discriminate between those with and without cognitive impairment in PD. The aim of our study was to validate this scoring algorithm in a large sample of non-demented PD patients, hypothesizing that the weighted MoCA would have a higher diagnostic accuracy for PD-MCI than the original MoCA. Methods In 202 non-demented PD patients, we evaluated cognitive status, clinical and demographic data, as well as the MoCA with a weighted and unweighted score. Receiver operating characteristic (ROC) curve analysis was used to evaluate discriminative ability of the MoCA. Group comparisons and ROC analysis were performed for PD-MCI classifications with a cut-off