Systematic Reviews
Copyright ©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Infect Dis. Jun 18, 2020; 10(2): 24-32
Published online Jun 18, 2020. doi: 10.5495/wjcid.v10.i2.24
Predictors of severe and critical COVID-19: A systematic review
Sameh Hany Emile, Sualeh Muslim Khan
Sameh Hany Emile, General Surgery Department, Mansoura University Hospitals, Mansoura University, Mansoura City 35516, Egypt
Sualeh Muslim Khan, Dow Medical College, Dow University of Health Sciences, Karachi 74200, Pakistan
Author contributions: Emile SH designed and wrote the manuscript; Khan SM contributed to data collection and analysis and revision of the manuscript.
Conflict-of-interest statement: All authors declare no conflicts-of-interest related to this article.
PRISMA 2009 Checklist statement: The manuscript has been revised according to the PRISMA 2009 Checklist.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Sameh Hany Emile, MD, Associate Professor, Surgeon, General Surgery Department, Mansoura University Hospitals, Mansoura University, Dakahlia Governorate, Mansoura City 35516, Egypt. dr_sameh81@mans.edu.eg
Received: April 23, 2020
Peer-review started: April 23, 2020
First decision: May 5, 2020
Revised: May 6, 2020
Accepted: May 21, 2020
Article in press: May 21, 2020
Published online: June 18, 2020
ARTICLE HIGHLIGHTS
Research background

Coronavirus disease 2019 (COVID-19) has been declared by the World Health Organization as a global pandemic. Although the majority of patients have mild or no symptoms, about 10% of patients may present with severe or critical disease that necessitates mechanical ventilation and may progress to death.

Research motivation

Patients who develop severe/critical COVID-19 disease have higher morbidity and mortality rates. Predicting which patients who are more likely to develop severe COVID-19 is highly required in order to implement more aggressive treatment measures to prevent potential deterioration.

Research objectives

The main objectives of the study were the incidence of severe COVID-19, mortality rate, and predictive factors of severe/critical disease.

Research methods

A Preferred Reporting Items for Systematic Reviews and Meta-Analyses-compliant systematic review of the existing literature was conducted. Three databases were searched and the articles reporting the predictors of severe/critical COVID-19 were retrieved. The quality of the articles was assessed with the methodological index for non-randomized studies index. Outcomes were summarized in a qualitative form.

Research results

Five studies including 583 patients of a median age of 50.5 years were included. 242 (41.5%) of 583 hospitalized patients had critical illness. Acute respiratory distress disease occurred in 291 patients, accounting for 46.7% of total complications. The most commonly reported predictors of severe COVID-19 were older age, medical comorbidities, lymphopenia, elevated C-reactive protein, increased D-dimer, and increased neutrophil ratio. Findings on computed tomography (CT) scanning predictive of severe disease were bronchial wall thickening, CT score > 7, linear opacities, consolidation, right upper lobe affection, and crazy paving pattern.

Research conclusions

Several factors may help predict severe/critical COVID-19. Factors that were more commonly reported were older age, medical comorbidities, lymphopenia, increased neutrophil ratio, elevated C-reactive protein, and increased D-dimer. As CT scanning has paramount importance in the making the diagnosis and assessment of COVID-19, it may also have a role in predicting more severe course of COVID-19.