Association between COVID-19 severity and tobacco smoking status: a retrospective cohort study using propensity score matching weights analysis

IF 3.6 3区 医学 Q1 RESPIRATORY SYSTEM BMJ Open Respiratory Research Pub Date : 2024-05-01 DOI:10.1136/bmjresp-2023-001976
Musaad A Alshammari, Ahmad Alamer, Lina Al Lehaibi, Mashael Alghamdi, Haneen Alotaibi, Mukhtar Alomar, Fawaz Alasmari, Faleh Alqahtani, Abdualziz Alhossan, Tahani K Alshammari
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Abstract

Introduction The COVID-19 pandemic continues to be a global threat to public health, with over 766 million confirmed cases and more than 6 million reported deaths. Patients with a smoking history are at a greater risk of severe respiratory complications and death due to COVID-19. This study investigated the association between smoking history and adverse clinical outcomes among COVID-19 patients admitted to a designated medical centre in Saudi Arabia. Methods A retrospective observational cohort study was conducted using patient chart review data from a large tertiary medical centre in the eastern region of the country. Patients admitted between January and December 2020 were screened. The inclusion criteria were ≥18 years of age and confirmed COVID-19 infection via reverse-transcription-PCR. The exclusion criteria were unconfirmed COVID-19 infection, non-COVID-19 admissions, unconfirmed smoking status, vaccinated individuals, essential chart information missing or refusal to consent. Statistical analyses comprised crude estimates, matching weights (as the main analysis) and directed acyclic graphs (DAGs) causal pathway analysis using an ordinal regression model. Results The sample comprised 447 patients (never-smoker=321; ever-smoker=126). The median age (IQR) was 50 years (39–58), and 73.4% of the sample were males. A matching weights procedure was employed to ensure covariate balance. The analysis revealed that the odds of developing severe COVID-19 were higher in the ever-smoker group with an OR of 1.44 (95% CI 0.90 to 2.32, p=0.130). This was primarily due to an increase in non-invasive oxygen therapy with an OR of 1.05 (95% CI 0.99 to 1.10, p=0.101). The findings were consistent across the different analytical methods employed, including crude estimates and DAGs causal pathway analysis. Conclusion Our findings suggest that smoking may increase the risk of adverse COVID-19 outcomes. However, the study was limited by its retrospective design and small sample size. Further research is therefore needed to confirm the findings. Data available upon request.
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COVID-19 严重程度与吸烟状况之间的关系:利用倾向得分匹配权重分析法进行的回顾性队列研究
导言 COVID-19 大流行继续对全球公共卫生构成威胁,确诊病例超过 7.66 亿例,报告死亡人数超过 600 万。有吸烟史的患者因 COVID-19 而出现严重呼吸道并发症和死亡的风险更大。本研究调查了沙特阿拉伯一家指定医疗中心收治的 COVID-19 患者中吸烟史与不良临床结果之间的关系。方法 采用该国东部地区一家大型三级医疗中心的患者病历审查数据,开展了一项回顾性观察队列研究。研究筛选了 2020 年 1 月至 12 月期间入院的患者。纳入标准为年龄≥18岁,并通过反转录-PCR证实感染了COVID-19。排除标准为未经证实的COVID-19感染、非COVID-19入院患者、未经证实的吸烟状态、已接种疫苗者、缺少重要病历信息或拒绝同意。统计分析包括粗略估计、匹配权重(作为主要分析)和使用序数回归模型的有向无环图(DAG)因果路径分析。结果 样本包括 447 名患者(从不吸烟者=321;曾经吸烟者=126)。中位年龄(IQR)为 50 岁(39-58),73.4% 的样本为男性。为确保协变量的平衡,采用了匹配加权法。分析结果显示,曾经吸烟者组患严重 COVID-19 的几率更高,OR 值为 1.44(95% CI 0.90 至 2.32,P=0.130)。这主要是由于无创氧疗的增加,OR 值为 1.05(95% CI 0.99 至 1.10,p=0.101)。采用不同的分析方法,包括粗略估计和 DAG 因果路径分析,得出的结果都是一致的。结论 我们的研究结果表明,吸烟可能会增加 COVID-19 不良结局的风险。然而,这项研究因其回顾性设计和样本量较小而受到限制。因此,还需要进一步的研究来证实研究结果。数据可应要求提供。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BMJ Open Respiratory Research
BMJ Open Respiratory Research RESPIRATORY SYSTEM-
CiteScore
6.60
自引率
2.40%
发文量
95
审稿时长
12 weeks
期刊介绍: BMJ Open Respiratory Research is a peer-reviewed, open access journal publishing respiratory and critical care medicine. It is the sister journal to Thorax and co-owned by the British Thoracic Society and BMJ. The journal focuses on robustness of methodology and scientific rigour with less emphasis on novelty or perceived impact. BMJ Open Respiratory Research operates a rapid review process, with continuous publication online, ensuring timely, up-to-date research is available worldwide. The journal publishes review articles and all research study types: Basic science including laboratory based experiments and animal models, Pilot studies or proof of concept, Observational studies, Study protocols, Registries, Clinical trials from phase I to multicentre randomised clinical trials, Systematic reviews and meta-analyses.
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