Long COVID in Children and Adolescents: A Systematic Review and Meta-analyses. (preprint)

Objective: To estimate the prevalence of long COVID in children and adolescents and identify the full spectrum of signs and symptoms present after acute SARS-CoV-2 infection. Methods: Two independent investigators searched PubMed and Embase in order to identify observational studies that met the following criteria: 1) a minimum of 30 patients, 2) ages ranged from 0 to 18 years, 3) published in English, 4) published before February 10th, 2022, and 5) meets the National Institute for Healthcare Excellence (NICE) definition of long COVID, which consists of both ongoing (4 to 12 weeks) and post COVID 19 ([≥]12 weeks) symptoms. For COVID symptoms reported in two or more studies, random-effects meta-analyses were performed using the MetaXL software to estimate the pooled prevalence, and Review Manager (RevMan) software 5.4 was utilized to estimate the Odds Ratios (ORs) with a 95% confidence interval (CI). Heterogeneity was assessed using I2 statistics. The Preferred Reporting Items for Systematic Reviewers and Meta-analysis (PRISMA) reporting guideline was followed (registration PROSPERO CRD42021275408). Results: The literature search yielded 68 articles for long COVID in children and adolescents. After screening, 21 studies met the inclusion criteria and were included in the systematic review and meta-analyses. A total of 80,071 children and adolescents with COVID-19 were included. The prevalence of long COVID was 25.24% (95% CI 18.17-33.02), and the most prevalent clinical manifestations were mood symptoms (16.50%; 95% CI 7.37-28.15), fatigue (9.66%; 95% CI 4.45-16.46), and sleep disorders (8.42%; 95% CI 3.41-15.20). When compared to controls, children infected by SARS-CoV-2 had a higher risk of persistent dyspnea (OR 2.69 95%CI 2.30-3.14), anosmia/ageusia (OR 10.68, 95%CI 2.48, 46.03), and/or fever (OR 2.23, 95%CI 1.22-4.07). The main limitation of these meta-analyses is the probability of bias, which includes lack of standardized definitions, recall, selection, misclassification, nonresponse and/or loss of follow-up, and the high level of heterogeneity. Conclusion: These meta-analyses provide an overview of the broad symptomatology of long COVID in minors, which may help improve management, rehabilitation programs, and future development of guidelines and therapeutic research for COVID-19.

More Than 50 Long-Term Effects of COVID-19: A Systematic Review and Meta-Analysis (preprint)

Background. COVID-19, caused by SARS-CoV-2, can involve sequelae and other medical complications that last weeks to months after initial recovery, which has come to be called Long-COVID or COVID long-haulers. This systematic review and meta-analysis aims to identify studies assessing long-term effects of COVID-19 and estimates the prevalence of each symptom, sign, or laboratory parameter of patients at a post-COVID-19 stage. Methods. LitCOVID (PubMed and Medline) and Embase were searched by two independent researchers. All articles with original data for detecting long-term COVID-19 published before 1st of January 2021 and with a minimum of 100 patients were included. For effects reported in two or more studies, meta-analyses using a random-effects model were performed using the MetaXL software to estimate the pooled prevalence with 95% CI. Heterogeneity was assessed using I2 statistics. This systematic review followed Preferred Reporting Items for Systematic Reviewers and Meta-analysis (PRISMA) guidelines, although the study protocol was not registered. Results. A total of 18,251 publications were identified, of which 15 met the inclusion criteria. The prevalence of 55 long-term effects was estimated, 21 meta-analyses were performed, and 47,910 patients were included. The follow-up time ranged from 14 to 110 days post-viral infection. The age of the study participants ranged between 17 and 87 years. It was estimated that 80% (95% CI 65-92) of the patients that were infected with SARS-CoV-2 developed one or more long-term symptoms. The five most common symptoms were fatigue (58%), headache (44%), attention disorder (27%), hair loss (25%), and dyspnea (24%). All meta-analyses showed medium (n=2) to high heterogeneity (n=13). Conclusions. In order to have a better understanding, future studies need to stratify by sex, age, previous comorbidities, the severity of COVID-19 (ranging from asymptomatic to severe), and duration of each symptom. From the clinical perspective, multi-disciplinary teams are crucial to developing preventive measures, rehabilitation techniques, and clinical management strategies with whole-patient perspectives designed to address long COVID-19 care.

More than 50 Long-term effects of COVID-19: a systematic review and meta-analysis (preprint)

COVID-19, caused by SARS-CoV-2, can involve sequelae and other medical complications that last weeks to months after initial recovery, which has come to be called Long-COVID or COVID long-haulers. This systematic review and meta-analysis aims to identify studies assessing long-term effects of COVID-19 and estimates the prevalence of each symptom, sign, or laboratory parameter of patients at a post-COVID-19 stage. LitCOVID (PubMed and Medline) and Embase were searched by two independent researchers. All articles with original data for detecting long-term COVID-19 published before 1st of January 2021 and with a minimum of 100 patients were included. For effects reported in two or more studies, meta-analyses using a random-effects model were performed using the MetaXL software to estimate the pooled prevalence with 95% CI. Heterogeneity was assessed using I2 statistics. This systematic review followed Preferred Reporting Items for Systematic Reviewers and Meta-analysis (PRISMA) guidelines, although the study protocol was not registered. A total of 18,251 publications were identified, of which 15 met the inclusion criteria. The prevalence of 55 long-term effects was estimated, 21 meta-analyses were performed, and 47,910 patients were included. The follow-up time ranged from 14 to 110 days post-viral infection. The age of the study participants ranged between 17 and 87 years. It was estimated that 80% (95% CI 65-92) of the patients that were infected with SARS-CoV-2 developed one or more long-term symptoms. The five most common symptoms were fatigue (58%), headache (44%), attention disorder (27%), hair loss (25%), and dyspnea (24%). All meta-analyses showed medium (n=2) to high heterogeneity (n=13). In order to have a better understanding, future studies need to stratify by sex, age, previous comorbidities, severity of COVID-19 (ranging from asymptomatic to severe), and duration of each symptom. From the clinical perspective, multi-disciplinary teams are crucial to developing preventive measures, rehabilitation techniques, and clinical management strategies with whole-patient perspectives designed to address long COVID-19 care.

More than 50 Long-Term Effects of COVID-19: A Systematic Review and Meta-Analysis (preprint)

Background: COVID-19, caused by SARS-CoV-2, can involve sequelae that last weeks to months after initial recovery. The objective of this systematic review and meta-analysis is to identify studies assessing the long-term effects of COVID-19 and estimate the prevalence of each symptom, sign, or laboratory parameters of patients at a post-COVID-19 stage.Methods: In this systematic review and meta-analysis, LitCOVID (PubMed and Medline) and Embase were searched by two independent researchers. Studies published before 1st of January 2021 and with a minimum of 100 patients were included. For effects reported in two or more studies, meta-analyses using a random-effects model were performed using the MetaXL software to estimate the pooled prevalence with 95% CI. Heterogeneity was assessed using the I2 statistics. PRISMA guidelines were followed.Findings: A total of 18,251 publications were identified, of which 15 met the inclusion criteria. The prevalence of 55 long-term effects was estimated, 21 meta-analyses were performed, and 47,910 patients were included. The follow-up time ranged from 15 to 110 days post-viral infection. The age of the study participants ranged between 17 and 87 years. It was estimated that 80% (95% CI 65-92) of the patients that were infected with SARS-CoV-2 developed one or more symptoms. The five most common symptoms were fatigue (58%), headache (44%), attention disorder (27%), hair loss (25%), and dyspnea (24%). In order to have a better understanding, there is a need for studies to stratify by sex, age, previous comorbidities, severity of COVID-19 (including asymptomatic), and duration of each symptom.Interpretation: From the clinical perspective, multi-disciplinary teams are crucial to developing preventive measures, rehabilitation techniques, and clinical management strategies with whole-patient perspectives designed to address after-COVID-19 care.Funding: National Institute for Neurological Disorders and Stroke (NINDS), and Houston Methodist Research Institute, Houston, TX.Declaration of Interests: SLL is an employee of Novartis Pharmaceutical Company; the statements presented in the paper do not necessarily represent the position of the company. The remaining authors have no competing interests to declare.

Hidden genomic diversity of SARS-CoV-2: implications for qRT-PCR diagnostics and transmission (preprint)

The COVID-19 pandemic has sparked an urgent need to uncover the underlying biology of this devastating disease. Though RNA viruses mutate more rapidly than DNA viruses, there are a relatively small number of single nucleotide polymorphisms (SNPs) that differentiate the main SARS-CoV-2 clades that have spread throughout the world. In this study, we investigated over 7,000 SARS-CoV-2 datasets to unveil both intrahost and interhost diversity. Our intrahost and interhost diversity analyses yielded three major observations. First, the mutational profile of SARS-CoV-2 highlights iSNV and SNP similarity, albeit with high variability in C>T changes. Second, iSNV and SNP patterns in SARS-CoV-2 are more similar to MERS-CoV than SARS-CoV-1. Third, a significant fraction of small indels fuel the genetic diversity of SARS-CoV-2. Altogether, our findings provide insight into SARS-CoV-2 genomic diversity, inform the design of detection tests, and highlight the potential of iSNVs for tracking the transmission of SARS-CoV-2.