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      COVID-19 and Smoking

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      , MD, PhD 1 , 2 , , MD 3 , , MD, PhD 4 , , MD, MPH 2
      Nicotine & Tobacco Research
      Oxford University Press

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          Abstract

          COVID-19 is mainly a disease of the respiratory tract characterized by a severe acute respiratory syndrome; the causative agent is SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2). The virus main entrance way is through mucosal tissues: nose, mouth, upper respiratory tract, and less frequently conjunctival mucosa. Tobacco smoke exposure results in inflammatory processes in the lung, increased mucosal inflammation, expression of inflammatory cytokines and tumor necrosis factor α, increased permeability in epithelial cells, mucus overproduction, and impaired mucociliary clearance. 1 Knowledge about host factors, and in particular avoidable host factors such as smoking, may be of importance in reducing viral contamination and the severity of the disease. The SARS-CoV-2 pandemic started in Wuhan, China toward the end of 2019. To the best of our knowledge and at the time of the writing of this Commentary, six published case series reported the prevalence of smoking among individuals with COVID-19 (Table 1). The study with the highest number of patients compared severe (N = 173) to nonsevere (N = 926) cases. The percent of current and former smokers were higher among the severe cases: 17% and 5%, respectively, than among the nonsevere cases (12% and 1%, respectively). 2 More importantly, among those with the primary composite end point (admission to an intensive care unit, the use of mechanical ventilation, or death), the proportion of smokers was higher with than among those without this end point (26% vs. 12%). 2 Another case series also showed more smokers among the severe (N = 58) than among the nonsevere (N = 82) cases. 3 The single modifiable host factor associated with progression of COVID-19 pneumonia was current smoking in a multivariable logistic analysis (odds ratio = 14.3, 95% confidence interval: 1.6–25.0). 4 Among those who died the number of smokers was also been found to be somewhat higher (9%, 5/54) than among survivors (6%, 9/137). 5 Table 1. Frequency of Smoking and Former Smoking Among COVID-19 Patients. N (%) Guan et al. 2 Nonsevere, N = 926 Severe, N = 173 Primary composite end point (admission to an intensive care unit, the use of mechanical ventilation, or death) Never smoked 793/913 (86.9) 134/172 (77.9) Yes 44/66 (66.7%) No 883/1019 (86.7%) Former smoker 12/913 (1.3) 9/172 (5.2) Yes 5/66 (7.6%) No 16/1019 (1.6%) Current smoker 108/913 (11.8) 29/172 (16.9) Yes 7/66 (25.8%) No 120/1019 (11.8%) Zhang et al. 3 Hospitalized for COVID-19 Nonsevere, N = 82 Severe, N = 58 Current smokers 0/82 2/58 (3.4) Past-smokers 3/82 (3.7) 4/58 (6.9) Cigarettes smoked per day × years of smoking  <400 1/82 (1) 2/58 (3.4)  ≥400 2/82 (2) 4/58 (7) Liu et al. 4 COVID-19 induced pneumonia Improvement/ stabilization, N = 67 Progression, N = 11 Smokers 2/67 (3) 3/11 (27.3) Zhou et al. 5 Inpatients, laboratory confirmed COVID-19 Survivor, N = 137 Nonsurvivor, N = 54 Smokers 9/137 (6) 5/54 (9) Huang 6 Inpatients, laboratory confirmed COVID-19 ICU care not needed, N = 28 ICU needed, N = 13 Smokers 0 3 (23) Yang et al. 7 Admitted to ICU Survivor, N = 20 Nonsurvivor, N = 32 Smokers 2 (10) 0 ICU: intensive care unit. Vardavas and Nikitara’s recent systematic review 8 identified five studies 2–6 and concluded that “smoking is most likely associated with negative progression and adverse outcomes of COVID-19.” Conversely, Lippi and Henry’s short meta-analysis reported no association of smoking status with severity of COVID-19. 9 However, the number of cases in most studies to date is very low, and consequently the 95% confidence intervals very wide. These case series reports are descriptive and do not allow to draw firm conclusions about the association of severity of COVID-19 with smoking status. Underlying health conditions such as COPD, diabetes, and coronary heart disease are more prevalent among severe cases. 2,5 Although these can causally be associated with smoking, the specific effect of smoking on COVID-19 severity cannot be disentangled. However, the nicotine and tobacco research and health care community cannot ignore these signals. We know that tobacco smoke exposure is a major risk factor for lung disease 1 and cigarette smoking is a substantial risk factor for bacterial and viral infections. 10 In addition, Middle East Respiratory Syndrome Coronavirus (MERS-CoV) that caused a small coronavirus epidemic in 2012–215 presented the same clinical features as the current COVID-19, and reports also indicated an association between smoking status and fatality rate, 11 with current smoking also more frequent among cases than among controls (37% vs. 19%, odds ratio = 3.14, 95% confidence interval: 1.10–9.24, N = 146). 12 MERS-CoV infection involves the dipeptidyl peptidase IV (DPP4) receptor while SARS-CoV-2 involves the ACE2 receptor (angiotensin II conversion enzyme-2 receptor). Both are abundant in mucosal epithelial cells and lung alveolar tissue and have multiple physiological functions. To infect the host, both viruses attach to its receptor: MERS-CoV to DPP4 and SARS-CoV-2 to ACE2, a probably key step for coronavirus infections. DPP4 mRNA and protein expressions are significantly higher in smokers compared with never smokers without airflow limitation and are inversely correlated with lung function. 13 It has recently been reported that ACE2 gene expression is higher in ever smokers (both current and former) compared with never smokers in normal lung tissue in a sample of patients with lung adenocarcinoma, after adjustment for age, gender, and ethnicity. ACE2 gene expression was also higher in small and large airway epithelia of healthy ever smokers compared with never smokers: current smokers had the highest expression, never smokers had the lowest expression; recent former smokers (≤15 years) had higher ACE2 gene expression than nonsmokers but not long-term former smokers (>15 years). 14 The similar upregulation associated with smoking of two different virus receptors observed with two different coronaviruses suggests that smoking contributes to the higher number of viral receptors and may support the findings of the recent case series observations. It is also worth noting that smoking behavior is characterized by inhalation and by repetitive hand-to-mouth movements which are strongly advised against to reduce viral contamination. Public health interventions, such as lockdown, may increase the exposure of family members to secondhand smoke. Lockdown may be an opportune moment to quit to reduce not only the smoker’s health risk but also that of his/her family members. Finally, risk factors of COVID-19 severity (lung and cardiovascular disorders, diabetes, etc.) are more frequent among smokers. Smoking cessation by any means should be a priority among smokers with comorbidities. Future Research Directions The nicotine and tobacco research community should explore the role of tobacco in the current COVID-19 pandemic. We need stronger evidence about the association of smoking with COVID-19. Databases should be identified and analyses focused on the role of this association in virus contamination, severity of the illness, ability to recover, and so on. Smoking status data should be systematically recorded and analyzed among COVID-19 patients. We need data about the immediate and short-term benefit of quitting smoking among symptomatic COVID-19 smokers. Laboratory studies should focus on quantifying the viral contamination of tobacco products with particular attention to shared products such as waterpipes. We also need data about alternative nicotine delivery systems and their risk/benefit ratio in relation to COVID-19. Public Health Challenges/Opportunities We suggest that ongoing public health campaigns should include reference to the importance of smoking cessation during the pandemic. Health care providers should be involved in offering evidence-based pharmacological and behavioral smoking cessation interventions by remote support. Quit lines should promote contacts with smokers with or without COVID-19, symptomatic or asymptomatic. Lockdown may result in social isolation and mental distress both increasing the need for smoking; smoking is more prevalent among economically less-advantaged groups, and they are potentially at higher risk for COVID-19. Large-scale interventions should be targeted at these populations in particular. Supplementary Material A Contributorship Form detailing each author’s specific involvement with this content, as well as any supplementary data, are available online at https://academic.oup.com/ntr. Declaration of Interests None declared.

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          Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

          Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.
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            Clinical Characteristics of Coronavirus Disease 2019 in China

            Abstract Background Since December 2019, when coronavirus disease 2019 (Covid-19) emerged in Wuhan city and rapidly spread throughout China, data have been needed on the clinical characteristics of the affected patients. Methods We extracted data regarding 1099 patients with laboratory-confirmed Covid-19 from 552 hospitals in 30 provinces, autonomous regions, and municipalities in mainland China through January 29, 2020. The primary composite end point was admission to an intensive care unit (ICU), the use of mechanical ventilation, or death. Results The median age of the patients was 47 years; 41.9% of the patients were female. The primary composite end point occurred in 67 patients (6.1%), including 5.0% who were admitted to the ICU, 2.3% who underwent invasive mechanical ventilation, and 1.4% who died. Only 1.9% of the patients had a history of direct contact with wildlife. Among nonresidents of Wuhan, 72.3% had contact with residents of Wuhan, including 31.3% who had visited the city. The most common symptoms were fever (43.8% on admission and 88.7% during hospitalization) and cough (67.8%). Diarrhea was uncommon (3.8%). The median incubation period was 4 days (interquartile range, 2 to 7). On admission, ground-glass opacity was the most common radiologic finding on chest computed tomography (CT) (56.4%). No radiographic or CT abnormality was found in 157 of 877 patients (17.9%) with nonsevere disease and in 5 of 173 patients (2.9%) with severe disease. Lymphocytopenia was present in 83.2% of the patients on admission. Conclusions During the first 2 months of the current outbreak, Covid-19 spread rapidly throughout China and caused varying degrees of illness. Patients often presented without fever, and many did not have abnormal radiologic findings. (Funded by the National Health Commission of China and others.)
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              Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

              Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p<0·0001), and d-dimer greater than 1 μg/mL (18·42, 2·64–128·55; p=0·0033) on admission. Median duration of viral shedding was 20·0 days (IQR 17·0–24·0) in survivors, but SARS-CoV-2 was detectable until death in non-survivors. The longest observed duration of viral shedding in survivors was 37 days. Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.
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                Author and article information

                Journal
                Nicotine Tob Res
                Nicotine Tob. Res
                nictob
                Nicotine & Tobacco Research
                Oxford University Press (US )
                1462-2203
                1469-994X
                03 April 2020
                03 April 2020
                : ntaa059
                Affiliations
                [1 ] Département de pharmacologie, Hôpital Pitié-Salpêtrière , Paris, France
                [2 ] Centre Universitaire de Médecine Générale et Santé Publique, UNISANTE, Université de Lausanne , Lausanne, Switzerland
                [3 ] Institut de Cardiologie, Hôpital Pitié-Salpêtrière , Paris, France
                [4 ] Centre ambulatoire d’addictologie, Hôpital Européen Georges Pompidou, Assistance Publique-Hôpitaux de Paris, Centre, Fédération Hospitalo-Universitaire Network of Research in Substance Use Disorder, Université de Paris , Paris, France
                Author notes
                Corresponding Author: Ivan Berlin, MD, PhD, Département de pharmacologie, 47-83 bd de l’Hôpital, 75013 Paris, France. Telephone: 33 1 42 16 16 78; Fax: 33 1 42 16 16 88; E-mail: ivan.berlin@ 123456aphp.fr
                Author information
                http://orcid.org/0000-0002-5928-5616
                Article
                ntaa059
                10.1093/ntr/ntaa059
                7184428
                32242236
                5f15f537-40f2-460b-9b50-a5efc063bd7a
                © The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved.For permissions, please e-mail: journals.permissions@oup.com.

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                History
                : 31 March 2020
                : 01 April 2020
                : 02 April 2020
                : 15 April 2020
                Page count
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