A systematic review and meta-analysis of Long COVID symptoms

Abstract:

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 analysed 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 11598 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.

Source: Arun Natarajan, Ashish Shetty, Gayathri Delanerolle, Yutian Zeng, Yingzhe Zhang, Vanessa Raymont, Shanaya Rathod, Sam Halabi, Kathryn Elliot, Peter Phiri, Jian Qing Shi. A systematic review and meta-analysis of Long COVID symptoms.

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