Risk factors of critical & mortal COVID-19 cases: A systematic literature review and meta-analysis

Zhaohai Zheng, Fang Peng, Buyun Xu, Jingjing Zhao, Huahua Liu, Jiahao Peng, Qingsong Li, Chongfu Jiang, Yan Zhou, Shuqing Liu, Chunji Ye, Peng Zhang, Yangbo Xing, Hangyuan Guo, Weiliang Tang, Zhaohai Zheng, Fang Peng, Buyun Xu, Jingjing Zhao, Huahua Liu, Jiahao Peng, Qingsong Li, Chongfu Jiang, Yan Zhou, Shuqing Liu, Chunji Ye, Peng Zhang, Yangbo Xing, Hangyuan Guo, Weiliang Tang

Abstract

Background: An epidemic of Coronavirus Disease 2019 (COVID-19) began in December 2019 and triggered a Public Health Emergency of International Concern (PHEIC). We aimed to find risk factors for the progression of COVID-19 to help reducing the risk of critical illness and death for clinical help.

Methods: The data of COVID-19 patients until March 20, 2020 were retrieved from four databases. We statistically analyzed the risk factors of critical/mortal and non-critical COVID-19 patients with meta-analysis.

Results: Thirteen studies were included in Meta-analysis, including a total number of 3027 patients with SARS-CoV-2 infection. Male, older than 65, and smoking were risk factors for disease progression in patients with COVID-19 (male: OR = 1.76, 95% CI (1.41, 2.18), P < 0.00001; age over 65 years old: OR =6.06, 95% CI(3.98, 9.22), P < 0.00001; current smoking: OR =2.51, 95% CI(1.39, 3.32), P = 0.0006). The proportion of underlying diseases such as hypertension, diabetes, cardiovascular disease, and respiratory disease were statistically significant higher in critical/mortal patients compared to the non-critical patients (diabetes: OR=3.68, 95% CI (2.68, 5.03), P < 0.00001; hypertension: OR = 2.72, 95% CI (1.60,4.64), P = 0.0002; cardiovascular disease: OR = 5.19, 95% CI(3.25, 8.29), P < 0.00001; respiratory disease: OR = 5.15, 95% CI(2.51, 10.57), P < 0.00001). Clinical manifestations such as fever, shortness of breath or dyspnea were associated with the progression of disease [fever: 0R = 0.56, 95% CI (0.38, 0.82), P = 0.003;shortness of breath or dyspnea: 0R=4.16, 95% CI (3.13, 5.53), P < 0.00001]. Laboratory examination such as aspartate amino transferase(AST) > 40U/L, creatinine(Cr) ≥ 133mol/L, hypersensitive cardiac troponin I(hs-cTnI) > 28pg/mL, procalcitonin(PCT) > 0.5ng/mL, lactatede hydrogenase(LDH) > 245U/L, and D-dimer > 0.5mg/L predicted the deterioration of disease while white blood cells(WBC)<4 × 109/L meant a better clinical status[AST > 40U/L:OR=4.00, 95% CI (2.46, 6.52), P < 0.00001; Cr ≥ 133μmol/L: OR = 5.30, 95% CI (2.19, 12.83), P = 0.0002; hs-cTnI > 28 pg/mL: OR = 43.24, 95% CI (9.92, 188.49), P < 0.00001; PCT > 0.5 ng/mL: OR = 43.24, 95% CI (9.92, 188.49), P < 0.00001;LDH > 245U/L: OR = 43.24, 95% CI (9.92, 188.49), P < 0.00001; D-dimer > 0.5mg/L: OR = 43.24, 95% CI (9.92, 188.49), P < 0.00001; WBC < 4 × 109/L: OR = 0.30, 95% CI (0.17, 0.51), P < 0.00001].

Conclusion: Male, aged over 65, smoking patients might face a greater risk of developing into the critical or mortal condition and the comorbidities such as hypertension, diabetes, cardiovascular disease, and respiratory diseases could also greatly affect the prognosis of the COVID-19. Clinical manifestation such as fever, shortness of breath or dyspnea and laboratory examination such as WBC, AST, Cr, PCT, LDH, hs-cTnI and D-dimer could imply the progression of COVID-19.

Keywords: COVID-19; Clinical manifestation; Comorbidity; Laboratory examination; Risk factor.

Copyright © 2020 Elsevier Ltd. All rights reserved.

Figures

Fig. 1
Fig. 1
Flow diagram of the study selection process.
Fig. 2
Fig. 2
Meta-analysis for male, age>65 years old and current smoking in COVID-19 cases. Heterogeneity analysis was carried out using Q test, the among studies variation (I2 index). Forest plots depict the comparison of the incidences of male, age>65 years old and current smoking in critical/mortal and non-critical patients.
Fig. 3
Fig. 3
Meta-analysis for comorbidities in COVID-19 cases. Fix-effect model for diabetes, cardiovascular disease, respiratory disease and malignancy. Random-effect model for hypertension. Heterogeneity analysis was carried out using Q test, the among studies variation (I2 index). Forest plots depict the comparison of the incidences of the 5 diseases in critical/mortal and non-critical patients.
Fig. 4
Fig. 4
Meta-analysis for laboratory examination in COVID-19 cases. Fix-effect model for “WBC 9per L” “AST > 40U/L” “Cr ≥ 133μmol/L” and “hs-cTnI > 28 pg/mL”. Random-effect model for “PCT > 0.5 ng/mL” “LDH > 245U/L” and “D-dimer > 0.5mg/L”. Heterogeneity analysis was carried out using Q test, the among studies variation (I2 index). Forest plots depict the comparison of the incidences of the laboratory examination in critical/mortal and non-critical patients.

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Source: PubMed

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