Cognitive disengagement syndrome in pediatric patients with long COVID: associations with mood, anxiety, and functional impairment

儿童新冠长期症状患者的认知脱离综合征:与情绪、焦虑和功能障碍的关联

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Abstract

Children with long COVID often report symptoms that overlap with cognitive disengagement syndrome (CDS, previously sluggish cognitive tempo (SCT)), a set of behaviors distinct from attention-deficit/hyperactivity disorder (ADHD) including excessive daydreaming, mental fogginess, and slowed behavior and thinking. Those with long COVID also frequently report low mood and anxiety, which are linked to CDS. The relationships between cognitive difficulties, mood, and functional impairment have yet to be explored in pediatric long COVID. Specifically, it is unclear how much cognitive difficulties (CDS, inattention) contribute to functional impairment, when accounting for mood/anxiety symptoms in this population. Retrospective parent-reported data was collected from 34 patients with long COVID (22 females, M(age) = 14.06 years, SD = 2.85, range 7-19) referred for neuropsychological consultation through a multidisciplinary Post-COVID-19 clinic. Compared to community and clinically referred samples, on average, long COVID patients showed elevated CDS symptoms, including Sluggish/sleepy (e.g., fatigue) and Low Initiation subscales (e.g., difficulty performing goal directed behaviors). Low Initiation, mood, anxiety, and inattention were associated with functional impairment. In multiple hierarchical regression models, after controlling for mood and anxiety, Low Initiation and inattention were no longer predictive of functional impairment. Instead, anxiety remained the sole predictor of functional impairment. Our results demonstrate that children with long COVID have high levels of CDS symptoms. The association between cognitive difficulties and functional impairment dissipated with the inclusion of mood and anxiety, suggesting behavioral health interventions targeting anxiety may help improve daily functioning and quality of life in pediatric long COVID patients.

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