Coronavirus disease 2019 (COVID-19), a new form of respiratory and systemic disorder sustained by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is now producing an outbreak of pandemic proportions, whereby nearly 110,000 people have already been infected around the world, 10–15% of whom with severe disease and over 3800 already died . A severe form of pneumonia, potentially evolving towards adult respiratory distress syndrome (ARDS) and occasionally associated with multiorgan failure, are the leading complications of this respiratory virus . Since laboratory medicine provides an essential contribution to the clinical decision making in this and many other infectious diseases , we aim to investigate here whether procalcitonin, whose values are not substantially modified in patients with viral infections , may play a role in distinguishing patients with or without severe COVID-19.
We carried out an electronic search in Medline (PubMed interface), Scopus and Web of Science, using the keywords “procalcitonin” AND “2019 novel coronavirus” OR “2019-nCoV” OR “COVID-19” without date (i.e., up to March 3, 2020) and language restrictions. The title, abstract and full text of all documents identified according to these search criteria were scrutinized by the authors, and those reporting data in COVID-19 patients with or without severe disease (defined as needing admission to intensive care unit or use of mechanical ventilation), were finally included in our meta-analysis. The reference list of each article was reviewed (forward and backward citation tracking) for identifying other potentially eligible documents. A meta-analysis was then carried out for calculating the individual and pooled odds ratios (OR) with their relative 95% confidence interval (95% CI), using MetaXL software Version 5.3 (EpiGear International Pty Ltd., Sunrise Beach, Australia). Procalcitonin values were entered as dichotomous variable, i.e., below or above the locally defined reference range (typically ≥ 0.50 ng/mL). Since the heterogeneity (I2 statistics) did not exceed 50%, a fixed effects model was finally used.
Author：Giuseppe Lippi, Mario Plebani