The effect of smoking on COVID-19–linked biomarkers in hospitalized patients with COVID-19

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Abstract

Background: The coronavirus pandemic, an infection (coronavirus disease 2019—COVID-19), caused by severe acute respiratory disease coronavirus 2 (SARS-CoV-2), continues to have a strong influence worldwide. Although smoking is a major known risk factor for respiratory infectious disease, the effects of smoking on COVID-19 are unclear. In this study, we aimed to evaluate the relationship between smoking and important hematologic (lymphocyte count, neutrophil count, platelet count, neutrophil-lymphocyte ratio [NLR], platelet-lymphocyte ratio [PLR]), inflammatory, and biochemical biomarkers in the prognosis of hospitalized patients with COVID-19. Methods: In a COVID-19 pandemic hospital between June and August 2020, 200 adult patients aged over 18 years were hospitalized with COVID-19 inflammatory and hematologic biomarkers at their first admission and smoking data were selected for this study. Results: The rate of smokers was much higher among men (91.5%) than in women (8.5%) (p = 0.001). Neutrophil counts were evaluated and was significantly higher in current smokers (p < 0.001) and ex-smokers (p = 0.001), and NLR (p = 0.008) and ferritin (p = 0.004) levels were higher than in never smokers. The saturation of patients had a negative significant linear correlation of NLR, PLR, and pack years of smoking. Compared with never smokers, current smokers had higher neutrophil counts (OR = 0.828 [0.750–0.915]; p = 0.041), NLR values (OR = 0.948 [0.910–0.987]; p = 0.009), and CRP levels (OR = 0.994 [0.990–0.999]; p = 0.019). Conclusion: Serum neutrophil, NLR, and ferritin levels, which are widely used in determining the prognosis of COVID-19, were found higher in current smokers/ex-smokers. These results support the view that a poor prognosis of COVID-19 is associated with smoking.

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APA

Çetin Kargin, N. (2021). The effect of smoking on COVID-19–linked biomarkers in hospitalized patients with COVID-19. Journal of Clinical Laboratory Analysis, 35(10). https://doi.org/10.1002/jcla.23983

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