Impact of asthma on COVID-19 mortality in the United States: Evidence based on a meta-analysis

被引:13
作者
Han, Xueya [1 ]
Xu, Jie [1 ]
Hou, Hongjie [1 ]
Yang, Haiyan [1 ,3 ]
Wang, Yadong [2 ]
机构
[1] Zhengzhou Univ, Sch Publ Hlth, Dept Epidemiol, Zhengzhou 450001, Henan Province, Peoples R China
[2] Henan Ctr Dis Control & Prevent, Dept Toxicol, Zhengzhou 450016, Henan Province, Peoples R China
[3] Zhengzhou Univ, Coll Publ Hlth, Dept Epidemiol, 100 Sci Ave, Zhengzhou 450001, Peoples R China
关键词
COVID-19; Asthma; Mortality; Meta-analysis; USA; CORONAVIRUS DISEASE 2019; OUTCOMES; PREVALENCE; RISK; CARE;
D O I
10.1016/j.intimp.2021.108390
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
Objective: The aim of this study was to investigate the impact of asthma on the risk for mortality among coronavirus disease 2019 (COVID-19) patients in the United States by a quantitative meta-analysis. Methods: A random-effects model was used to estimate the pooled odds ratio (OR) with corresponding 95% confidence interval (CI). I2 statistic, sensitivity analysis, Begg's test, meta-regression and subgroup analyses were also performed. Results: The data based on 56 studies with 426,261 COVID-19 patients showed that there was a statistically significant association between pre-existing asthma and the reduced risk for COVID-19 mortality in the United States (OR: 0.82, 95% CI: 0.74-0.91). Subgroup analyses by age, male proportion, sample size, study design and setting demonstrated that pre-existing asthma was associated with a significantly reduced risk for COVID-19 mortality among studies with age >= 60 years old (OR: 0.79, 95% CI: 0.72-0.87), male proportion >= 55% (OR: 0.79, 95% CI: 0.72-0.87), male proportion < 55% (OR: 0.81, 95% CI: 0.69-0.95), sample sizes >= 700 cases (OR: 0.80, 95% CI: 0.71-0.91), retrospective study/case series (OR: 0.82, 95% CI: 0.75-0.89), prospective study (OR: 0.83, 95% CI: 0.70-0.98) and hospitalized patients (OR: 0.82, 95% CI: 0.74-0.91). Meta-regression did reveal none of factors mentioned above were possible reasons of heterogeneity. Sensitivity analysis indicated the robustness of our findings. No publication bias was detected in Begg's test (P = 0.4538). Conclusion: Our findings demonstrated pre-existing asthma was significantly associated with a reduced risk for COVID-19 mortality in the United States.
引用
收藏
页数:10
相关论文
共 69 条
[1]   Unbiased identification of clinical characteristics predictive of COVID-19 severity [J].
Akama-Garren, Elliot H. ;
Li, Jonathan X. .
CLINICAL AND EXPERIMENTAL MEDICINE, 2022, 22 (01) :137-149
[2]   Cardiac Troponin-I and COVID-19: A Prognostic Tool for In-Hospital Mortality [J].
AL Abbasi, Baher ;
Torres, Pedro ;
Ramos-Tuarez, Fergie ;
Dewaswala, Nakeya ;
Abdallah, Ahmed ;
Chen, Kai ;
Qader, Mohamed Abdul ;
Job, Riya ;
Aboulenain, Samar ;
Dziadkowiec, Karolina ;
Bhopalwala, Huzefa ;
Pino, Jesus E. ;
Chait, Robert D. .
CARDIOLOGY RESEARCH, 2020, 11 (06) :398-404
[3]   Characteristics, comorbidities and survival analysis of young adults hospitalized with COVID-19 in New York City [J].
Altonen, Brian L. ;
Arreglado, Tatiana M. ;
Leroux, Ofelia ;
Murray-Ramcharan, Max ;
Engdahl, Ryan .
PLOS ONE, 2020, 15 (12)
[4]   Asthma and severe acute respiratory syndrome coronavirus 2019: current evidence and knowledge gaps [J].
Assaf, Sara M. ;
Tarasevych, Svitlana P. ;
Diamant, Zuzana ;
Hanania, Nicola A. .
CURRENT OPINION IN PULMONARY MEDICINE, 2021, 27 (01) :45-53
[5]   Early predictors of in-hospital mortality in patients with COVID-19 in a large American cohort [J].
Bahl, Amit ;
Van Baalen, Morgan Nees ;
Ortiz, Laura ;
Chen, Nai-Wei ;
Todd, Courtney ;
Milad, Merit ;
Yang, Alex ;
Tang, Jonathan ;
Nygren, Madalyn ;
Qu, Lihua .
INTERNAL AND EMERGENCY MEDICINE, 2020, 15 (08) :1485-1499
[6]   How to perform a meta-analysis with R: a practical tutorial [J].
Balduzzi, Sara ;
Ruecker, Gerta ;
Schwarzer, Guido .
EVIDENCE-BASED MENTAL HEALTH, 2019, 22 (04) :153-160
[7]   Machine-learning-based COVID-19 mortality prediction model and identification of patients at low and high risk of dying [J].
Banoei, Mohammad M. ;
Dinparastisaleh, Roshan ;
Zadeh, Ali Vaeli ;
Mirsaeidi, Mehdi .
CRITICAL CARE, 2021, 25 (01)
[8]   OPERATING CHARACTERISTICS OF A BANK CORRELATION TEST FOR PUBLICATION BIAS [J].
BEGG, CB ;
MAZUMDAR, M .
BIOMETRICS, 1994, 50 (04) :1088-1101
[9]   Development and validation of a prognostic 40-day mortality risk model among hospitalized patients with COVID-19 [J].
Berry, Donald A. ;
Ip, Andrew ;
Lewis, Brett E. ;
Berry, Scott M. ;
Berry, Nicholas S. ;
MrKulic, Mary ;
Gadalla, Virginia ;
Sat, Burcu ;
Wright, Kristen ;
Serna, Michelle ;
Unawane, Rashmi ;
Trpeski, Katerina ;
Koropsak, Michael ;
Kaur, Puneet ;
Sica, Zachary ;
McConnell, Andrew ;
Bednarz, Urszula ;
Marafelias, Michael ;
Goy, Andre H. ;
Pecora, Andrew L. ;
Sawczuk, Ihor S. ;
Goldberg, Stuart L. .
PLOS ONE, 2021, 16 (07)
[10]   Characteristics and outcomes of patients with COVID-19 in an intensive care unit of a community hospital; retrospective cohort study [J].
Cedano, Jorge ;
Corona, Emilio Fabian ;
Gonzalez-Lara, Melissa ;
Santana, Melvin ;
Younes, Islam ;
Ayad, Sarah ;
Kossack, Andrew ;
Purewal, Anam ;
Pullatt, Raja .
JOURNAL OF COMMUNITY HOSPITAL INTERNAL MEDICINE PERSPECTIVES, 2021, 11 (01) :27-32