Our study further highlights the need to design an efficient sleep diagnostic algorithm for children with ADHD, thereby more accurately identifying cases in which a full sleep assessment is indicated.
Aim: To assess the prevalence of mild cognitive impairment (MCI) in medical inpatients aged 55–85 years without known cognitive deficits, and how often ward physicians mentioned MCI in their discharge notes. Moreover, we aimed to identify variables associated with MCI and to assess the sensitivity and specificity of the Mini-Mental State Examination (MMSE) for MCI. Methods: Two neuropsychologists administered a 60-min battery of validated tests to evaluate different cognitive domains. The diagnosis of MCI was based on a prespecified algorithm. The sensitivity and specificity of the MMSE for MCI were calculated. Results: Fifteen patients showed a normal cognitive profile (21.4%), while 55 patients (78.6%) showed MCI. Ward physicians, blinded to the results of the neuropsychological evaluation, did not mention MCI in their discharge notes of any of the evaluated patients. The only variable independently associated with MCI was the MMSE. A MMSE score of ≤28 showed a sensitivity of 85.5% and a specificity of 66.7% for MCI. Conclusion: MCI is frequent albeit overlooked in elderly medical inpatients without previously known cognitive deficits. In view of therapies preventing the progression of MCI to dementia, MCI screening will be crucial. The MMSE represents a promising screening tool for MCI in medical inpatients.
Study Objectives Sleep-related slow-wave activity (SWA) has been recognized as a marker of synaptic plasticity. In children affected by attention deficit hyperactivity disorder (ADHD), SWA is mainly located in the central rather than frontal regions, reflecting a maturational delay. A detailed subjective and objective sleep investigation, including a full night video-polysomnography (PSG-HD-EEG), was performed on 30 consecutive drug naïve outpatients with a diagnosis of ADHD. They received a diagnosis of sleep disorders in 29/30 cases, and most of them had a past history of sleep problems. They had a higher apnea–hypopnea index at PSG, and slept less than 9 hr at actigraphy. We aimed to describe the SWA behavior in the same group of children with ADHD. Materials and Methods The full-night PSG-HD EEG of children with ADHD was compared with the one of the 25 healthy controls. The scalp SWA mapping, the decrease of SWA during the night, and the EEG source of SWA were analyzed. Results At scalp topography, the focus of SWA was observed over the centro–parietal–occipital regions in participants with ADHD (p < 0.01), which remained significant in the subgroups divided between subgroups according to the sleep diagnosis (p < 0.01). The physiological decrease in SWA was more evident in control participants. The source analysis revealed a greater delta power over the posterior cingulate in participants with ADHD (p < 0.01). Conclusions Our results confirm static and dynamic changes in SWA behavior in children with ADHD, which may reflect a maturational delay occurring at a vulnerable age, as a consequence of chronic sleep deprivation.
Objective: Recent years saw an increasing interest towards sleep microstructure abnormalities in attention-deficit/hyperactivity disorder (ADHD). However, the existing literature on sleep electroencephalographic (EEG) power in ADHD is still controversial, often based on single electrode recordings, and mainly focused on slow wave activity (SWA) during NREM sleep. This study aimed to systematically investigate sleep power topography in all traditional frequency bands, in all sleep stages and across sleep cycles using high-density EEG (HD-EEG). Method: Thirty drug-naïve children with ADHD (10.5 ± 2.1 years, 21 male) and 23 typically developing (TD) control participants (mean age: 10.2 ± 1.6 years, 13 male) were included in the current analysis. Signal power topography was computed in classical frequency bands during sleep, contrasted between groups and sleep cycles, and correlated with measures of ADHD severity, cognitive functioning and estimated total sleep time. Results: Compared to TD subjects, patients with ADHD consistently displayed a widespread increase in low-frequency activity (between 3 and 10 Hz) during NREM sleep, but not during REM sleep and wake before sleep onset. Such a difference involved a wide centro-posterior cluster of channels in the upper SWA range, in Theta, and low-Alpha. Between-group difference was maximal in sleep stage N3 in the first sleep cycle, and positively correlated with average total sleep time. Conclusions: These results support the concept that children with ADHD, compared to TD peers, have a higher sleep pressure and altered sleep homeostasis, which possibly interfere with (and delay) cortical maturation.
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