Journal Article

A systematic review and meta-analysis of long COVID symptoms

Shetty, Ashish, Zeng, Yutian, Halabi, Sam, Phiri, Peter, Shi, Jian Qing, Delanerolle, Gayathri, Raymont, Vanessa, Natarajan, Arun, Zhang, Yingzhe, Rathod, Shanaya, Elliot, Kathryn

2023

Overview

Background Ongoing symptoms or the development of new symptoms following a SARS-CoV-2 diagnosis has caused a complex clinical problem known as “long COVID” (LC). This has introduced further pressure on global healthcare systems as there appears to be a need for ongoing clinical management of these patients. LC personifies heterogeneous symptoms at varying frequencies. The most complex symptoms appear to be driven by the neurology and neuropsychiatry spheres. Methods A systematic protocol was developed, peer reviewed, and published in PROSPERO. The systematic review included publications from the 1st of December 2019–30th June 2021 published in English. Multiple electronic databases were used. The dataset has been analyzed using a random-effects model and a subgroup analysis based on geographical location. Prevalence and 95% confidence intervals (CIs) were established based on the data identified. Results Of the 302 studies, 49 met the inclusion criteria, although 36 studies were included in the meta-analysis. The 36 studies had a collective sample size of 11,598 LC patients. 18 of the 36 studies were designed as cohorts and the remainder were cross-sectional. Symptoms of mental health, gastrointestinal, cardiopulmonary, neurological, and pain were reported. Conclusions The quality that differentiates this meta-analysis is that they are cohort and cross-sectional studies with follow-up. It is evident that there is limited knowledge available of LC and current clinical management strategies may be suboptimal as a result. Clinical practice improvements will require more comprehensive clinical research, enabling effective evidence-based approaches to better support patients.

• Publisher: BioMed Central,Springer Nature B.V,BMC
• Subject: Autonomic dysfunction / Biomedicine / Cohort analysis / COVID-19 / COVID-19 Testing / Cross-sectional studies / Data analysis / Gastrointestinal / Headaches / Health Sciences / Humans / Long COVID / Medicine / Medicine & Public Health / Mental Health / Meta-analysis / Metal fatigue / Nervous system / Neurological disorders / Neurology / Neuropsychiatry / Pain / Patients / Post-Acute COVID-19 Syndrome / SARS-CoV-2 / Severe acute respiratory syndrome coronavirus 2 / Sleep / Statistics for Life Sciences / Systematic review / Systematic Review Update