Long-haul COVID-19 and its associated risk factors: a systematic review and meta-analysis

Millions of people infected by the SARS-CoV2 virus are now dealing with its sequelae, mostly known as ‘Long COVID’. Multiple studies have shown that approximately 10–20% of the survivors of COVID-19 develop symptoms that can be diagnosed as Long COVID. This systematic review and meta-analysis aimed at estimating the system-wise prevalence of Long COVID sequelae at 12 months follow-up and to identify the possible risk factors attributable to the emergence of these symptoms.

Studies were assessed via electronic web-based searches of PubMed, PubMed Central and Google Scholar. We included all the studies reporting prevalence of long-haul symptoms at 3, 6 and 12 months of follow-up period after COVID-19 infection. Data was analysed using R software. Forest plot and I-squared test were carried out to assess the heterogeneity of the studies. A funnel plot and Egger’s regression test were done to check the publication bias. A random effect model was used to estimate the pooled prevalence.

Forty-three articles comprising 19,025 study participants were included in this review. The most common system affected was the cardiovascular system with a pooled prevalence of 14% (95% CI 9.6–19.9%) with severe heterogeneity (I² = 98%, p < 0.01), followed by neurological system with a pooled prevalence of 12.4% (95% CI 7.8–19.3%) and severe heterogeneity (I² = 99%, p < 0.0001). Being of female gender (OR = 1.51, 95% CI 1.05–2.17%), history of hospitalization (OR = 0.98, 95% CI 0.92–1.04%), history of sore throat (OR = 2.81, 95% CI 0.51–15.47) and history of diarrhea during acute COVID-19 infection (OR = 1.22, 95% CI 0.76–1.96) were the identified factors associated with long-haul COVID symptoms.

The maximum pooled prevalence was from the cardiovascular system with chest pain being the most common symptom reported, followed by the neurological system. Certain characteristics (gender, hospitalization status, h/o sore throat and diarrhea) were associated with long-haul COVID.