Risk factors and predictors associated with the severity of COVID-19 in China: a systematic review, meta-analysis, and meta-regression

Abstract

Since December 2019, the pneumonia cases infected with 2019 novel coronavirus have appeared, posing a critical threat to global health. In this study, we performed a meta-analysis to discover the different clinical characteristics between severe and non-severe patients with COVID-19 to find the potential risk factors and predictors of this disease's severity, as well as to serve as a guidance for subsequent epidemic prevention and control work. PubMed, Cochrane Library, Medline, Embase and other databases were searched to collect studies on the difference of clinical characteristics of severe and non-severe patients.Meta-analysis was performed using RevMan 5.3 software, and the funnel plots could be made to evaluate the publication bias. P>0.05 means no statistical significance. Furthermore, a meta-regression analysis was performed by using Stata 15.0 to find the potential factors of the high degree of heterogeneity (I 2 >50%).Sixteen studies have been included, with 1,172 severe patients and 2,803 non-severe patients. Compared with non-severe patients, severe patients were more likely to have the symptoms of dyspnea, hemoptysis, and the complications of ARDS, shock, secondary infection, acute kidney injury, and acute cardiac injury.Interestingly, the former smokers were more prevalent in severe cases as compared to non-severe cases, but there was no difference between the two groups of 'current smokers'. Except for chronic liver disease and chronic kidney disease, the underlying comorbidities of hypertension, diabetes, cardiovascular disease, chronic obstructive pulmonary disease (COPD), malignancy, cerebrovascular disease, and HIV can make the disease worse. In terms of laboratory indicators, the decreased lymphocyte and platelet count, and the increased levels of white blood cell (WBC), D-dimer, creatine kinase, lactate dehydrogenase, procalcitonin, alanine aminotransferase, aspartate aminotransferase, and C-reactive protein were more prevalent in severe patients. Meta-regression analysis showed that patient age, gender, and proportion of severe cases did not significantly impact on the outcomes of any clinical indexes that showed high degree of heterogeneity in the meta-analysis. In conclusion, the severity of COVID-19 could be evaluated by, radiologic finding, some symptoms like dyspnea and hemoptysis, some laboratory indicators, and smoking history, especially the exsmokers. Compared with non-severe patients, severe patients were more likely to have complications and Zhang et al. Clinical characteristics of COVID-19 in China

Changes in Smoking Behaviour and Home-Smoking Rules during the Initial COVID-19 Lockdown Period in Israel

“…The uncertainty regarding the role of smoking and nicotine on the risk for infection and COVID-19 severity might also impact smoking behaviors [34,35]. Several meta-analyses have suggested that former smokers are at increased risk for a severe disease [17,36,37], while other studies have shown that the proportion of smokers among infected patients was lower than expected [17,38]. This has raised the hypothesis that nicotine might play an immune-modulator protective role in the pathogenesis of the disease [39,40].…”

Role of Cigarette Smoke on Angiotensin-Converting Enzyme-2 Protein Membrane Expression in Bronchial Epithelial Cells Using an Air-Liquid Interface Model

“…Reference tobacco cigarettes 1R6F (Kentucky University) were conditioned for at least 48 h in accordance to ISO 3402:1999 (https://www.iso.org/standard/28324.html) at 60 ± 3% relative humidity and 22 ± 1°C and then smoked under Health Canada Intense (HCI) regime (55 ml puff-volume, 2 s puff-duration, 30 s puff-frequency, bell-shaped puff-profile, with hole vents blocked) by a LM1 smoking machine (Borgwaldt KC GmbH, Hamburg, Germany). Air-liquid-interface (ALI) exposure of cells was obtained by an exposure system consisting in a perspex chamber sealed by O-rings and containing a bottom part filled with D-MEM high glucose media (20 ml) and an upper part without media (Strzelak et al, 2018;Changeux et al, 2020;Zhang T. et al, 2020) and with two polyurethane tubes connected for loading and discharging of the smoke (Supplementary Figure S1). Briefly, the culture medium is removed from the upper part of the transwell inserts which are placed in the exposure chambers on a support that allows the cells to remain basally wet with medium and to be exposed to the smoke/air apically by the LM1 smoking machine.…”

Chest CT and Clinical Features of COVID-19 Patients in the Early Stage of the Epidemic: An Observational Study from China

“…We performed a statistical analysis of radiological ndings of all enrolled patients (Table 2). The median time interval from the rst Chest CT after admission to the symptom onset was 18 [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29] days, and the time of the last CT examination was 41.5 [33-52.75] days. According to imaging examination, 94% patients showed bilateral pneumonia, and about half showed peripheral distribution.…”