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

Research square. 2021
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Symptoms, signs, or abnormal clinical parameters persisting two or more weeks after COVID-19 onset that do not return to a healthy baseline can potentially be considered long-term effects of the disease. The aim of this study was to estimate the incidence of all the symptoms, signs, or abnormal laboratory parameters extending beyond the acute phase of COVID-19 reported to date. This study is a systematic review and meta-analysis of 15 peer-reviewed studies that reported symptoms, signs, or laboratory parameters of patients at a post-COVID-19 stage (assessed two weeks or more after initial symptoms) in cohorts of COVID-19 patients. Results indicate that 80% (95% CI 65–92) of individuals with a confirmed COVID-19 diagnosis continued to have at least one overall effect beyond two weeks following acute infection. In total, 55 effects, including symptoms, signs, and laboratory parameters, were identified, with fatigue, anosmia [partial or complete loss of the sense of smell], lung dysfunction, abnormal chest X-ray/CT scan, and neurological disorders being the most common. Authors conclude that physicians should be aware of the symptoms, signs, and biomarkers present in patients previously affected by COVID-19 to promptly assess, identify and halt long COVID-19 progression, minimize the risk of chronic effects and help re-establish pre-COVID-19 health.

Abstract

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 1 st 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 I 2 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.

Lifestyle medicine

Fundamental Clinical Imbalances : Neurological ; Immune and inflammation
Patient Centred Factors : Mediators/COVID-19
Environmental Inputs : Psychosocial influences
Personal Lifestyle Factors : Psychological
Functional Laboratory Testing : Not applicable

Methodological quality

Jadad score : Not applicable
Allocation concealment : Not applicable
Publication Type : Preprint

Metadata

Nutrition Evidence keywords : Weight loss ; Diabetes mellitus