ABSTRACT
BACKGROUND: The association between autonomic dysfunction and long-COVID syndrome is established. However, the prevalence and patterns of symptoms of dysautonomia in long-COVID syndrome in a large population are lacking. OBJECTIVE: To evaluate the prevalence and patterns of symptoms of dysautonomia in patients with long-COVID syndrome. METHODS: We administered the Composite Autonomic Symptom Score 31 (COMPASS-31) questionnaire to a sample of post-COVID-19 patients who were referred to post-COVID clinic in Assiut University Hospitals, Egypt for symptoms concerning for long-COVID syndrome. Participants were asked to complete the COMPASS-31 questionnaire referring to the period of more than 4 weeks after acute COVID-19. RESULTS: We included 320 patients (35.92 ± 11.92 years, 73% females). The median COMPASS-31 score was 26.29 (0-76.73). The most affected domains of dysautonomia were gastrointestinal, secretomotor, and orthostatic intolerance with 91.6%, 76.4%, and 73.6%, respectively. There was a positive correlation between COMPASS-31 score and long-COVID duration (p < 0.001) and a positive correlation between orthostatic intolerance domain score and post-COVID duration (p < 0.001). There was a positive correlation between orthostatic intolerance domain score and age of participants (p = 0.004). Two hundred forty-seven patients (76.7%) had a high score of COMPASS-31 >16.4. Patients with COMPASS-31 >16.4 had a longer duration of long-COVID syndrome than those with score <16.4 (46.2 vs. 26.8 weeks, p < 0.001). CONCLUSIONS: Symptoms of dysautonomia are common in long-COVID syndrome. The most common COMPASS-31 affected domains of dysautonomia are gastrointestinal, secretomotor, and orthostatic intolerance. There is a positive correlation between orthostatic intolerance domain score and patients' age.
Subject(s)
COVID-19 , Orthostatic Intolerance , Primary Dysautonomias , COVID-19/complications , COVID-19/epidemiology , Cross-Sectional Studies , Female , Humans , Male , Prevalence , Primary Dysautonomias/epidemiology , Primary Dysautonomias/etiology , Syndrome , Post-Acute COVID-19 SyndromeABSTRACT
OBJECTIVE: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is protean in its manifestations, affecting nearly every organ system. However, nervous system involvement and its effect on disease outcome are poorly characterized. The objective of this study was to determine whether neurologic syndromes are associated with increased risk of inpatient mortality. METHODS: A total of 581 hospitalized patients with confirmed SARS-CoV-2 infection, neurologic involvement, and brain imaging were compared to hospitalized non-neurologic patients with coronavirus disease 2019 (COVID-19). Four patterns of neurologic manifestations were identified: acute stroke, new or recrudescent seizures, altered mentation with normal imaging, and neuro-COVID-19 complex. Factors present on admission were analyzed as potential predictors of in-hospital mortality, including sociodemographic variables, preexisting comorbidities, vital signs, laboratory values, and pattern of neurologic manifestations. Significant predictors were incorporated into a disease severity score. Patients with neurologic manifestations were matched with patients of the same age and disease severity to assess the risk of death. RESULTS: A total of 4,711 patients with confirmed SARS-CoV-2 infection were admitted to one medical system in New York City during a 6-week period. Of these, 581 (12%) had neurologic issues of sufficient concern to warrant neuroimaging. These patients were compared to 1,743 non-neurologic patients with COVID-19 matched for age and disease severity admitted during the same period. Patients with altered mentation (n = 258, p = 0.04, odds ratio [OR] 1.39, confidence interval [CI] 1.04-1.86) or radiologically confirmed stroke (n = 55, p = 0.001, OR 3.1, CI 1.65-5.92) had a higher risk of mortality than age- and severity-matched controls. CONCLUSIONS: The incidence of altered mentation or stroke on admission predicts a modest but significantly higher risk of in-hospital mortality independent of disease severity. While other biomarker factors also predict mortality, measures to identify and treat such patients may be important in reducing overall mortality of COVID-19.