Post-acute sequelae of COVID-19 and adverse psychiatric outcomes: an etiology and risk systematic review protocol

Abstract

Introduction The post-acute sequelae of COVID-19 (PASC) is a syndrome characterized by persistent COVID-19 symptoms or the onset of new symptoms following recovery from the initial or acute phase of the illness. Such symptoms often occur four or more weeks after being diagnosed with COVID-19. Although a lot of work has gone into understanding the long-term mental health effects of PASC, many questions related to the etiology and risk of this condition remain. Thus, this protocol is for a systematic review assessing the association between PASC and adverse psychiatric outcomes and whether people with PASC are at greater risk of developing an adverse psychiatric outcome than those without PASC. Methods and analysis Various medical databases (e.g., PubMed and EMBASE) will be searched for eligible articles using predefined search criteria. Gray literature will also be explored. Epidemiological observational studies and secondary analyses of randomized controlled trials that report a quantitative relationship between PASC and at least one adverse psychiatric outcome will be included. The Population, Exposure of interest, Comparator, and Outcome (PECO) framework will be used as a standardized framework for the inclusion criteria. The Joanna Briggs Institute (JBI) critical appraisal tools will be used to assess methodological quality and critically appraise the risk of bias in included studies. A random-effects meta-analysis will be conducted if possible. A narrative synthesis will be performed if a meta-analysis is impossible due to substantial heterogeneity across studies. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach will be used to rate the cumulative certainty of the evidence for all outcomes. Ethics and Dissemination Ethical approval is not required for this study. The study results will be published in a peer-reviewed journal. Prospero registration number CRD99999999999

Data-driven analysis to understand long COVID using electronic health records from the RECOVER initiative

“…Third, we investigated the potential impact of sample size difference by replicating the analyses on a downsampled INSIGHT cohort, which had the same number of patients as in the OneFlorida+. The best gradient-boosting decision tree model was selected from a set of models defined by hyperparameters including maximum depth (3,4,5), learning rate (0.01, 0.26, 0.51, 0.76), max number of leaves in one tree (5,20,35), and the minimal number of samples in one leaf (100, 200, 300), using the cross-validation algorithm as detailed in Supplementary Table 3. Subgroup analysis and negative outcome controls.…”

Understanding Post-Acute Sequelae of SARS-CoV-2 Infection through Data-Driven Analysis with Longitudinal Electronic Health Records: Findings from the RECOVER Initiative

“…We observed significant differences between the two cohorts regarding age, gender, race, area deprivation index, and outbreak waves. The INSIGHT cohort contained SARS-CoV-2 infected patients mainly from the New York metropolitan area with the median area deprivation index (ADI) 17 15 (6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24) in the SARS-CoV-2 infected patient group, indicating fewer disadvantaged neighborhoods than the OneFlorida+ cohort whose median ADI was 58 (41-76). Indeed, the OneFlorida+ cohort consisted of a mixture of urban, sub-urban and rural populations in Florida and selected cities in Georgia and Alabama (see Methods).…”

“…The global COVID-19 pandemic from late 2019 has led to more than 434 million infections and 5.9 million deaths as of March 1, 2022 4 . Growing scientific and clinical evidence has demonstrated potential post-acute and long-term effects of SARS-CoV-2 infection in multiple organ systems 5 , including cardiovascular 6 , mental health 7 , neurological 8 , and metabolic 9 among other systems. Recently, several retrospective cohort analyses have described post-acute sequelae of SARS-CoV-2 infection (PASC) using real-world patient data 2,10,11 .…”