Circulating mid-regional proadrenomedullin is a predictor of mortality in patients with COVID-19: a systematic review and meta-analysis

Although there is increasing understanding of the changes in the laboratory parameters of Coronavirus disease 2019 (COVID-19), the correlation between circulating Mid-regional Proadrenomedullin (MR-proADM) and mortality of patients with COVID-19 is not fully understood. In this study, we conducted a systematic review and meta-analysis to evaluate the prognostic value of MR-proADM in patients with COVID-19.

The PubMed, Embase, Web of Science, Cochrane Library, Wanfang, SinoMed and Chinese National Knowledge Infrastructure (CNKI) databases were searched from 1 January 2020 to 20 March 2022 for relevant literature. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) was used to assess quality bias, STATA was employed to pool the effect size by a random effects model, and potential publication bias and sensitivity analyses were performed.

14 studies comprising 1822 patients with COVID-19 met the inclusion criteria, there were 1145 (62.8%) males and 677 (31.2%) females, and the mean age was 63.8 ± 16.1 years. The concentration of MR-proADM was compared between the survivors and non-survivors in 9 studies and the difference was significant (P < 0.01), I² = 46%. The combined sensitivity was 0.86 [0.73–0.92], and the combined specificity was 0.78 [0.68–0.86]. We drew the summary receiver operating characteristic (SROC) curve and calculated the area under curve (AUC) = 0.90 [0.87–0.92]. An increase of 1 nmol/L of MR-proADM was independently associated with a more than threefold increase in mortality (odds ratio (OR) 3.03, 95% confidence interval (CI) 2.26–4.06, I² = 0.0%, P = 0.633). The predictive value of MR-proADM for mortality was better than many other biomarkers.

MR-proADM had a very good predictive value for the poor prognosis of COVID-19 patients. Increased levels of MR-proADM were independently associated with mortality in COVID-19 patients and may allow a better risk stratification.