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Meta-Analysis
. 2020 Sep 9:9:1107.
doi: 10.12688/f1000research.26186.2. eCollection 2020.

Predictors of COVID-19 severity: a systematic review and meta-analysis

Mudatsir Mudatsir  1 , Jonny Karunia Fajar  1   2 , Laksmi Wulandari  3 , Gatot Soegiarto  4 , Muhammad Ilmawan  5 , Yeni Purnamasari  5 , Bagus Aulia Mahdi  4 , Galih Dwi Jayanto  2 , Suhendra Suhendra  5 , Yennie Ayu Setianingsih  6 , Romi Hamdani  7 , Daniel Alexander Suseno  8 , Kartika Agustina  9 , Hamdan Yuwafi Naim  10 , Muchamad Muchlas  11 , Hamid Hunaif Dhofi Alluza  5 , Nikma Alfi Rosida  5 , Mayasari Mayasari  5 , Mustofa Mustofa  5 , Adam Hartono  12 , Richi Aditya  5 , Firman Prastiwi  5 , Fransiskus Xaverius Meku  5 , Monika Sitio  5 , Abdullah Azmy  7 , Anita Surya Santoso  13 , Radhitio Adi Nugroho  5 , Camoya Gersom  2 , Ali A Rabaan  14 , Sri Masyeni  15 , Firzan Nainu  16 , Abram L Wagner  17 , Kuldeep Dhama  18 , Harapan Harapan  1   19
Affiliations
Meta-Analysis

Predictors of COVID-19 severity: a systematic review and meta-analysis

Mudatsir Mudatsir et al. F1000Res. .

Abstract

Background: The unpredictability of the progression of coronavirus disease 2019 (COVID-19) may be attributed to the low precision of the tools used to predict the prognosis of this disease. Objective: To identify the predictors associated with poor clinical outcomes in patients with COVID-19. Methods: Relevant articles from PubMed, Embase, Cochrane, and Web of Science were searched as of April 5, 2020. The quality of the included papers was appraised using the Newcastle-Ottawa scale (NOS). Data of interest were collected and evaluated for their compatibility for the meta-analysis. Cumulative calculations to determine the correlation and effect estimates were performed using the Z test. Results: In total, 19 papers recording 1,934 mild and 1,644 severe cases of COVID-19 were included. Based on the initial evaluation, 62 potential risk factors were identified for the meta-analysis. Several comorbidities, including chronic respiratory disease, cardiovascular disease, diabetes mellitus, and hypertension were observed more frequent among patients with severe COVID-19 than with the mild ones. Compared to the mild form, severe COVID-19 was associated with symptoms such as dyspnea, anorexia, fatigue, increased respiratory rate, and high systolic blood pressure. Lower levels of lymphocytes and hemoglobin; elevated levels of leukocytes, aspartate aminotransferase, alanine aminotransferase, blood creatinine, blood urea nitrogen, high-sensitivity troponin, creatine kinase, high-sensitivity C-reactive protein, interleukin 6, D-dimer, ferritin, lactate dehydrogenase, and procalcitonin; and a high erythrocyte sedimentation rate were also associated with severe COVID-19. Conclusion: More than 30 risk factors are associated with a higher risk of severe COVID-19. These may serve as useful baseline parameters in the development of prediction tools for COVID-19 prognosis.

Keywords: COVID-19; SARS-CoV-2; clinical outcome; prognosis; severity.

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Conflict of interest statement

No competing interests were disclosed.

Figures

Figure 1.
Figure 1.. A flowchart of paper selection in our study.
Figure 2.
Figure 2.. A forest plot of the association between comorbid factors and the risk of severe COVID-19.
A) Chronic respiratory disease; B) Cardiovascular diease; C) Diabetes mellitus; D) Hypertension.
Figure 3.
Figure 3.. A forest plot of the association between clinical manifestations and the risk of severe COVID-19.
A) Dyspnea; B) Anorexia; C) Fatique; D) Dizziness.
Figure 4.
Figure 4.. A forest plot of the association between clinical manifestation and the risk of severe COVID-19.
A) Respiratory rate; B) Systolic blood pressure.
Figure 5.
Figure 5.. A forest of the association between complete blood count and the risk of severe COVID-19.
A) White blood cells; B) Neutrophil count; C) Lymphocytopenia; D) Hemoglobin.
Figure 6.
Figure 6.
A forest plot of the association between the risk of severe COVID-19 and the levels of AST ( A), ALT ( B), and serum creatinine ( C).
Figure 7.
Figure 7.
A forest plot of the association between the risk of severe COVID-19 and the levels of BUN ( A), Hs-troponin ( B), and creatine kinase ( C).
Figure 8.
Figure 8.
A forest plot of the association between the risk of severe COVID-19 and the levels of CRP ( A), Hs-CRP ( B), ESR ( C), and IL-6 ( D).
Figure 9.
Figure 9.
A forest plot of the association between the risk of severe COVID-19 and the levels of D-dimer ( A), serum ferritin ( B), lactate dehydrogenase ( C), and procalcitonin ( D).
See this image and copyright information in PMC

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