COVID-19 disease severity to predict persistent symptoms: a systematic review and meta-analysis
Emre Dirican, Tayibe Bal
Abstract
BACKGROUND: It is unclear, whether the initial disease severity may help to predict which COVID-19 patients at risk of developing persistent symptoms. AIM: The aim of this study was to examine whether the initial disease severity affects the risk of persistent symptoms in post-acute COVID-19 syndrome and long COVID. METHODS: A systematic search was conducted using PUBMED, Google Scholar, EMBASE, and ProQuest databases to identify eligible articles published after January 2020 up to and including 30 August 2021. Pooled odds ratio (OR) and confidence intervals (CIs) were calculated using random effects meta-analysis. FINDINGS: After searching a total of 7733 articles, 20 relevant observational studies with a total of 7840 patients were selected for meta-analysis. The pooled OR for persistent dyspnea in COVID-19 survivors with a severe versus nonsevere initial disease was 2.17 [95%CI 1.62 to 2.90], and it was 1.33 [95%CI 0.75 to 2.33] for persistent cough, 1.30 [95%CI 1.06 to 1.58] for persistent fatigue, 1.02 [95%CI 0.73 to 1.40] for persistent anosmia, 1.22 [95%CI 0.69 to 2.16] for persistent chest pain, and 1.30 [95%CI 0.93 to 1.81] for persistent palpitation. CONCLUSIONS: Contrary to expectations, we did not observe an association between the initial COVID-19 disease severity and common persistent symptoms except for dyspnea and fatigue. In addition, it was found that being in the acute or prolonged post-COVID phase did not affect the risk of symptoms. Primary care providers should be alert to potential most prevalent persistent symptoms in all COVID-19 survivors, which are not limited to patients with critical-severe initial disease.