Prevalence of depression in SARS-CoV-2 infected patients: An umbrella review of meta-analyses.

OBJECTIVE: The COVID-19 pandemic is still spreading worldwide two years after its outbreak. Depression has been reported in around 30% of SARS-CoV-2 infected patients. We aim to synthesize the available meta-analytical evidence in an umbrella review exploring the prevalence of depression during and after SARS-CoV-2 infection. METHODS: First, we performed a narrative umbrella review including only meta-analyses providing a quantitative summary of the prevalence of depression during or after SARS-CoV-2 infection. Then we extracted the prevalence and sample size from the original studies included in each meta-analysis, and after removing duplicate studies, we performed a random-effects model meta-analysis based on single original study estimates. Heterogeneity, publication bias, leave-one-out sensitivity, and subgroup analyses were performed. RESULTS: 14 meta-analyses were included in the umbrella review. The prevalence of depression ranged from 12% to 55% in the presence of high heterogeneity. The meta-analysis based on 85 original studies derived from the included 14 meta-analyses showed a pooled prevalence of depression of 31% (95% CI:25-38%) in the presence of high and significant heterogeneity (Q = 8988; p < 10-6; I2 = 99%) and publication bias (p < 0.001). CONCLUSION: The burden of post-COVID depression substantially exceeds the pre-pandemic prevalence. Health care services for COVID-19 survivors should monitor and treat emergent depression, reducing its potential detrimental long-term effects.

Prevalence, trajectory over time, and risk factor of post-COVID-19 fatigue.

Fatigue is one of the most commonly reported symptoms in the context of the post-COVID-19 syndrome. Notably, fatigue is characterised by overlapping physical and psychopathological symptoms, and questions about its trajectory over time and possible predictors remained unanswered. Thus, in the present study we aim to investigate the prevalence, the course over time, and the risk factors of post-COVID fatigue. We included 495 patients recovered from COVID-19. For all of them we collected one month demographic, clinical and psychopathological characteristics. We evaluated fatigue severity at one, three, six, and twelve-months according to Fatigue Severity Scale (FSS). We explored the potential predictor of long-term post-COVID fatigue (six or twelve months FSS) by implementing 5000 non-parametric bootstraps enhanced elastic net penalised regression. We found that 22%, 27%, 30%, and 34% of patients self-rated fatigue symptoms in the pathological range at one, three, six, and twelve months respectively. We detected a worsening of fatigue symptomatology over time. From the elastic net regression results, only depressive symptomatology at one month (ZSDS and BDI-13) predicted the presence of post-COVID-19 long-term fatigue. No other clinical or demographic variable was found to predict post-COVID fatigue. We suggest that, rather independent of COVID-19 severity, depression after COVID-19 is associated with persistent fatigue. Clarifying mechanisms and risk factors of post-COVID fatigue will allow to identify the target population and to tailor specific treatment and rehabilitation interventions to foster recovery.