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      Cannabis and COVID-19: Reasons for Concern

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          Abstract

          The lockdown measures implemented to curb the spread of SARS-CoV-2 may affect (illicit) drug consumption patterns. This rapid response study investigated changes in cannabis use in a non-probability sample of cannabis users in the Netherlands during the early lockdown period. We fielded an online cross-sectional survey 4–6 weeks after implementation of lockdown measures in the Netherlands on March 15, 2020. We measured self-reported \motives for changes in use, and assessed cannabis use frequency (use days), number of joints per typical use day, and route of administration in the periods before and after lockdown implementation. 1,563 cannabis users were recruited. Mean age was 32.7 ± 12.0 years; 66.3% were male and 67.9% used cannabis (almost) daily. In total, 41.3% of all respondents indicated that they had increased their cannabis use since the lockdown measures, 49.4% used as often as before, 6.6% used less often, and 2.8% stopped (temporarily). One-third of those who were not daily users before the lockdown became (almost) daily users. Before the lockdown, most respondents (91.4%) used cannabis in a joint mixed with tobacco and 87.6% still did so. Among users of joints, 39.4% reported an increase in the average number consumed per use day; 54.2% stayed the same and 6.4% used fewer joints. This rapid response study found evidence that during the lockdown more users increased rather than decreased cannabis consumption according to both frequency and quantity. These data highlight the need to invest more resources in supporting cessation, harm reduction, and monitoring longer term trends in cannabis use.

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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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            Case-Fatality Rate and Characteristics of Patients Dying in Relation to COVID-19 in Italy

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              COVID-19 and smoking: A systematic review of the evidence

              COVID-19 is a coronavirus outbreak that initially appeared in Wuhan, Hubei Province, China, in December 2019, but it has already evolved into a pandemic spreading rapidly worldwide 1,2 . As of 18 March 2020, a total number of 194909 cases of COVID-19 have been reported, including 7876 deaths, the majority of which have been reported in China (3242) and Italy (2505) 3 . However, as the pandemic is still unfortunately under progression, there are limited data with regard to the clinical characteristics of the patients as well as to their prognostic factors 4 . Smoking, to date, has been assumed to be possibly associated with adverse disease prognosis, as extensive evidence has highlighted the negative impact of tobacco use on lung health and its causal association with a plethora of respiratory diseases 5 . Smoking is also detrimental to the immune system and its responsiveness to infections, making smokers more vulnerable to infectious diseases 6 . Previous studies have shown that smokers are twice more likely than non-smokers to contract influenza and have more severe symptoms, while smokers were also noted to have higher mortality in the previous MERS-CoV outbreak 7,8 . Given the gap in the evidence, we conducted a systematic review of studies on COVID-19 that included information on patients’ smoking status to evaluate the association between smoking and COVID-19 outcomes including the severity of the disease, the need for mechanical ventilation, the need for intensive care unit (ICU) hospitalization and death. The literature search was conducted on 17 March 2020, using two databases (PubMed, ScienceDirect), with the search terms: [‘smoking’ OR ‘tobacco’ OR ‘risk factors’ OR ‘smoker*’] AND [‘COVID-19’ OR ‘COVID 19’ OR ‘novel coronavirus’ OR ‘sars cov-2’ OR ‘sars cov 2’] and included studies published in 2019 and 2020. Further inclusion criteria were that the studies were in English and referred to humans. We also searched the reference lists of the studies included. A total of 71 studies were retrieved through the search, of which 66 were excluded after full-text screening, leaving five studies that were included. All of the studies were conducted in China, four in Wuhan and one across provinces in mainland China. The populations in all studies were patients with COVID-19, and the sample size ranged from 41 to 1099 patients. With regard to the study design, retrospective and prospective methods were used, and the timeframe of all five studies covered the first two months of the COVID-19 pandemic (December 2019, January 2020). Specifically, Zhou et al. 9 studied the epidemiological characteristics of 191 individuals infected with COVID-19, without, however, reporting in more detail the mortality risk factors and the clinical outcomes of the disease. Among the 191 patients, there were 54 deaths, while 137 survived. Among those that died, 9% were current smokers compared to 4% among those that survived, with no statistically significant difference between the smoking rates of survivors and non-survivors (p=0.21) with regard to mortality from COVID-19. Similarly, Zhang et al. 10 presented clinical characteristics of 140 patients with COVID-19. The results showed that among severe patients (n=58), 3.4% were current smokers and 6.9% were former smokers, in contrast to non-severe patients (n=82) among which 0% were current smokers and 3.7% were former smokers , leading to an OR of 2.23; (95% CI: 0.65–7.63; p=0.2). Huang et al. 11 studied the epidemiological characteristics of COVID-19 among 41 patients. In this study, none of those who needed to be admitted to an ICU (n=13) was a current smoker. In contrast, three patients from the non-ICU group were current smokers, with no statistically significant difference between the two groups of patients (p=0.31), albeit the small sample size of the study. The largest study population of 1099 patients with COVID-19 was provided by Guan et al. 12 from multiple regions of mainland China. Descriptive results on the smoking status of patients were provided for the 1099 patients, of which 173 had severe symptoms, and 926 had non-severe symptoms. Among the patients with severe symptoms, 16.9% were current smokers and 5.2% were former smokers, in contrast to patients with non-severe symptoms where 11.8% were current smokers and 1.3% were former smokers. Additionally, in the group of patients that either needed mechanical ventilation, admission to an ICU or died, 25.5% were current smokers and 7.6% were former smokers. In contrast, in the group of patients that did not have these adverse outcomes, only 11.8% were current smokers and 1.6% were former smokers. No statistical analysis for evaluating the association between the severity of the disease outcome and smoking status was conducted in that study. Finally, Liu et al. 13 found among their population of 78 patients with COVID-19 that the adverse outcome group had a significantly higher proportion of patients with a history of smoking (27.3%) than the group that showed improvement or stabilization (3.0%), with this difference statistically significant at the p=0.018 level. In their multivariate logistic regression analysis, the history of smoking was a risk factor of disease progression (OR=14.28; 95% CI: 1.58–25.00; p= 0.018). We identified five studies that reported data on the smoking status of patients infected with COVID-19. Notably, in the largest study that assessed severity, there were higher percentages of current and former smokers among patients that needed ICU support, mechanical ventilation or who had died, and a higher percentage of smokers among the severe cases 12 . However, from their published data we can calculate that the smokers were 1.4 times more likely (RR=1.4, 95% CI: 0.98–2.00) to have severe symptoms of COVID-19 and approximately 2.4 times more likely to be admitted to an ICU, need mechanical ventilation or die compared to non-smokers (RR=2.4, 95% CI: 1.43–4.04). In conclusion, although further research is warranted as the weight of the evidence increases, with the limited available data, and although the above results are unadjusted for other factors that may impact disease progression, smoking is most likely associated with the negative progression and adverse outcomes of COVID-19. Table 1 Overview of the five studies included in the systematic review Title Setting Population Study design and time horizon Outcomes Smoking rates by outcome Zhou et al. 9 (2020)Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study Jinyintan Hospital and Wuhan Pulmonary Hospital, Wuhan, China All adult inpatients (aged ≥18 years) with laboratory confirmed COVID-19 (191 patients) Retrospective multicenter cohort study until 31 January 2020 Mortality 54 patients died during hospitalisation and 137 were discharged Current smokers: n=11 (6%)Non-survivors: n=5 (9%)Survivors: n=6 (4%)(p=0.20) Current smoker vs non-smokerUnivariate logistic regression(OR=2.23; 95% CI: 0.65–7.63; p=0.2) Zhang et al. 10 (2020)Clinical characteristics of 140 patients infected with SARS-CoV-2 in Wuhan, China No. 7 Hospital of Wuhan, China All hospitalised patients clinically diagnosed as ‘viral pneumonia’ based on their clinical symptoms with typical changes in chest radiology (140 patients) Retrospective 16 January to 3 February 2020 Disease Severity Non-severepatients: n=82Severe patients:n=58 Disease Severity Former smokers: n=7Severe: n=4 (6.9%)Non-severe: n=3 (3.7%) (p= 0.448) Current smokers: n=2Severe: n=2 (3.4%)Non-severe: n=0 (0%) Guan et al. 12 (2019)Clinical Characteristics of Coronavirus Disease 2019 in China 552 hospitals in 30 provinces, autonomous regions, and municipalities in mainland China Patients with laboratory-confirmed COVID-19 (1099 patients) Retrospective until 29 January 2020 Severity and admission to an ICU, the use of mechanical ventilation, or death Non-severe patients: n=926 Severe patients: n=173 By severity Severe cases16.9% current smokers5.2% former smokers77.9% never smokers Non-severe cases11.8% current smokers1.3% former smokers86.9% never smokers By mechanical ventilation, ICU or death Needed mechanical ventilation, ICU or died25.8% current smokers7.6% former smokers66.7% non-smokers No mechanical ventilation, ICU or death11.8% current smokers1.6% former smokers86.7% never smokers Huang et al. 11 (2020)Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China A hospital in Wuhan, China Laboratory-confirmed 2019-nCoV patients in Wuhan (41 patients) Prospective from 16 December 2019 to 2 January 2020 Mortality As of 22 January 2020, 28 (68%) of 41 patients were discharged and 6 (15%) patients died Current smokers: n=3ICU care: n=0Non-ICU care: n=3 (11%) Current smokers in ICU care vs non-ICU care patients (p=0.31) Liu et al. 13 (2019)Analysis of factors associated with disease outcomes in hospitalised patients with 2019 novel coronavirus disease Three tertiary hospitals in Wuhan, China Patients tested positive for COVID-19 (78 patients) Retrospective multicentre cohort study from 30 December 2019 to 15 January 2020 Disease progression 11 patients (14.1%) in the progression group 67 patients (85.9%) in the improvement/stabilization group 2 deaths Negative progression group: 27.3% smokersIn the improvement group: 3% smokers The negative progression group had a significantly higher proportion of patients with a history of smoking than the improvement/stabilisation group (27.3% vs 3.0%)Multivariate logistic regression analysis indicated that the history of smoking was a risk factor of disease progression (OR=14.28; 95% CI: 1.58–25.00; p= 0.018)
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                Author and article information

                Contributors
                Journal
                Front Psychiatry
                Front Psychiatry
                Front. Psychiatry
                Frontiers in Psychiatry
                Frontiers Media S.A.
                1664-0640
                21 December 2020
                2020
                21 December 2020
                : 11
                : 601653
                Affiliations
                [1] 1Trimbos Institute, The Netherlands Institute of Mental Health and Addiction , Utrecht, Netherlands
                [2] 2Addiction and Mental Health Group (AIM), Department of Psychology, University of Bath , Bath, United Kingdom
                [3] 3National Centre for Youth Substance Use Research, The University of Queensland , St Lucia, QLD, Australia
                Author notes

                Edited by: Giuseppe Bersani, Sapienza University of Rome, Italy

                Reviewed by: Anahita Bassir Nia, Yale University, United States; Hollis C. Karoly, Colorado State University, United States

                *Correspondence: Margriet W. van Laar mlaar@ 123456trimbos.nl

                This article was submitted to Addictive Disorders, a section of the journal Frontiers in Psychiatry

                Article
                10.3389/fpsyt.2020.601653
                7779403
                33408655
                d11b01ad-b47b-4547-a340-b4c543856ad3
                Copyright © 2020 van Laar, Oomen, van Miltenburg, Vercoulen, Freeman and Hall.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 01 September 2020
                : 16 November 2020
                Page count
                Figures: 0, Tables: 4, Equations: 0, References: 35, Pages: 6, Words: 5062
                Funding
                Funded by: Ministerie van Volksgezondheid, Welzijn en Sport 10.13039/501100002999
                Categories
                Psychiatry
                Brief Research Report

                Clinical Psychology & Psychiatry
                cannabis,corona,covid-19,route of administration,risks
                Clinical Psychology & Psychiatry
                cannabis, corona, covid-19, route of administration, risks

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