ABSTRACT
Background The number of long-COVID is rising but it is not still clear which patients will develop long-covid and what will be the symptoms if they do.We followed up 95 patientswith confirmed COVID-19 after 9 months of the original study to delineate possible long COVID symptoms. Methods The original study included 201 patients who were treated in a large referral center from March to May 2020. Ninty percent of the patients reported physical or psychological symptoms within 9 months post-COVID. Findings Easy fatigability was the most common 51.04 % long-COVID symptoms followed by anxiety 38.54 %, dyspnea 38.54 %, and new headache 38.54%. There was no association between COVID-19 severity in the acute phase (admission status) and the number of long-COVID symptoms (F(1, 93) = 0.75, p = 0.45 (n.s.)), chronic fatigue syndrome (CFS) (F(1,93) = -0.49, p = 0.62 (n.s.), MOCA scores (F(1, 90) = 0.073, p = 0.787 (n.s.)) in the future. Being female (F(1, 92) = -2.27, p = 0.02), having a higher number of symptoms in the acute phase(F(1,93) = 2.76, p = 0.0068),and experiencing constitutional neuropsychiatric symptoms(F(1, 93)= 2.529, p = 0.01) in the acute phase were associated with higher occurance of CFS in follow up. Moreover, constitutional neuropsychiatric symptoms in acute phase were associated with cognitive dificits (lower MOCA score) (F(1, 93) = 10.84, p= 0.001) in the follow up. Conclusions Severity of the acute disease does not seem to be related to long-COVID symptoms. However, specific clinical presentations might be predictors of distinct long-COVID symptoms. Constitutional neuropsychiatric symptoms in the acute phase are associated with important and debilitating chronic symptoms including chronic fatigue syndrome, and cognitive deficits. These results might pave the way for findingthe underlying mechanisms of long-COVID and provide additional insight into possible candidate treatments for COVID-19.
Subject(s)
COVID-19 , Dyspnea , Anxiety DisordersABSTRACT
Background: COVID-19 has heterogeneous manifestations, though one of the most common symptoms is a sudden loss of smell (anosmia or hyposmia). We investigated whether olfactory loss is a reliable predictor of COVID-19. Methods: This preregistered, cross-sectional study used a crowdsourced questionnaire in 23 languages to assess symptoms in individuals self-reporting recent respiratory illness. We quantified changes in chemosensory abilities during the course of the respiratory illness using 0-100 visual analog scales (VAS) for participants reporting a positive (C19+; n=4148) or negative (C19-; n=546) COVID-19 laboratory test outcome. Logistic regression models identified singular and cumulative predictors of COVID-19 status and post-COVID-19 olfactory recovery. Results: Both C19+ and C19- groups exhibited smell loss, but it was significantly larger in C19+ participants (mean{+/-}SD, C19+: -82.5{+/-}27.2 points; C19-: -59.8{+/-}37.7). Smell loss during illness was the best predictor of COVID-19 in both single and cumulative feature models (ROC AUC=0.72), with additional features providing no significant model improvement. VAS ratings of smell loss were more predictive than binary chemosensory yes/no-questions or other cardinal symptoms, such as fever or cough. Olfactory recovery within 40 days was reported for ~50% of participants and was best predicted by time since illness onset. Conclusions: As smell loss is the best predictor of COVID-19, we developed the ODoR-19 tool, a 0-10 scale to screen for recent olfactory loss. Numeric ratings [≤]2 indicate high odds of symptomatic COVID-19 (10