Literature DB >> 34385278

Asthma and COVID-19 risk: a systematic review and meta-analysis.

Anthony P Sunjaya1,2, Sabine M Allida1,2, Gian Luca Di Tanna1,2, Christine R Jenkins3,2,4.   

Abstract

BACKGROUND: Individual case series and cohort studies have reported conflicting results in people with asthma on the vulnerability to and risk of mortality from coronavirus disease 2019 (COVID-19). RESEARCH QUESTION: Are people with asthma at a higher risk of being infected or hospitalised or poorer clinical outcomes from COVID-19?
METHODS: A systematic review and meta-analysis based on five main databases including the World Health Organization COVID-19 database between 1 December 2019 and 11 July 2021 on studies with a control (non-asthma) group was conducted. Prevalence and risk ratios were pooled using Sidik-Jonkman random-effects meta-analyses.
FINDINGS: 51 studies with an 8.08% (95% CI 6.87-9.30%) pooled prevalence of people with asthma among COVID-19 positive cases. The risk ratios were 0.83 (95% CI 0.73-0.95, p=0.01) for acquiring COVID-19; 1.18 (95% CI 0.98-1.42, p=0.08) for hospitalisation; 1.21 (95% CI 0.97-1.51, p=0.09) for intensive care unit (ICU) admission; 1.06 (95% CI 0.82-1.36, p=0.65) for ventilator use; and 0.94 (95% CI 0.76-1.17, p=0.58) for mortality for people with asthma. Subgroup analyses by continent revealed a significant difference in risk of acquiring COVID-19, ICU admission, ventilator use and death between the continents.
INTERPRETATION: The risk of being infected with severe acute respiratory syndrome coronavirus 2 was reduced compared to the non-asthma group. No statistically significant differences in hospitalisation, ICU admission and ventilator use were found between groups. Subgroup analyses showed significant differences in outcomes from COVID-19 between America, Europe and Asia. Additional studies are required to confirm this risk profile, particularly in Africa and South America, where few studies originate.
Copyright ©The authors 2022.

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Year:  2022        PMID: 34385278      PMCID: PMC8361304          DOI: 10.1183/13993003.01209-2021

Source DB:  PubMed          Journal:  Eur Respir J        ISSN: 0903-1936            Impact factor:   16.671


Introduction

Asthma is one of the most common chronic conditions with an estimated prevalence of >300 million people globally [1]. As coronavirus disease 2019 (COVID-19) continues to spread across the world with >4.05 million deaths as of 15 July 2021 [2], there are concerns that people with asthma are at a higher risk of acquiring the disease, or of poorer outcomes. There are differing reports on the vulnerability of asthmatics to COVID-19 based on various local or national level case series and analyses [3]. Several meta-analyses have been conducted, but their conclusions suffer limitations from the inclusion of COVID-19 non-PCR-confirmed cases and inclusion of case series in their analyses which confer significant selection bias [4-6] (supplementary table S1). Most focus only on mortality, but not on other important considerations such as risk of being infected, hospitalised, admission to an intensive care unit (ICU) and importantly ventilator use when admitted [7-9]. A comprehensive understanding of COVID-19 risk among asthmatics globally is crucial as countries lift lockdown, and for prioritisation of vaccine allocation considering the limited supply of vaccines globally. Hence, we aimed to conduct a comprehensive systematic review and meta-analysis based only on controlled studies with reverse transcriptase (RT)-PCR-confirmed COVID-19 cases to ascertain the pooled prevalence and overall risk of infection, hospitalisation, ICU admission, ventilator use and mortality from COVID-19 among patients with asthma.

Methods

Search strategy and selection criteria

This systematic review and meta-analysis form part of a living systematic review on the risk of COVID-19 for people with asthma. Our first meta-analysis, which included studies up to 26 May 2020, has been published previously [5] and included pre-prints due to the early stage of the pandemic at that point. The protocol was prospectively registered and published in PROSPERO (www.crd.york.ac.uk/PROSPERO CRD42020222303) (appendix 1). The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (www.prisma-statement.org) was used in reporting this study. A comprehensive search of electronic databases including Cochrane Central Register of Controlled Trials (CENTRAL), Cochrane Database of Systematic Reviews, PubMed, MEDLINE and the World Health Organization COVID-19 database were conducted between 1 December 2019 and 11 July 2021. In addition, a hand search of references of relevant systematic reviews was conducted. In the case of missing information, we contacted the authors whenever possible. If the study identified patients with chronic respiratory conditions, we asked them to specify if this included asthma and requested these data. We included all primary controlled studies reporting on adults with confirmed COVID-19 based on positive RT-PCR, with a pre-existing diagnosis of asthma, published in the English language. Asthma was defined according to definitions in the individual studies and included those sourced from medical records, physician-diagnosed and self-reported asthma. We excluded studies with ≤15 participants, pre-prints and those not published in English. The search strategy is available in appendix 2.

Data collection

Two reviewers (AS and SA) screened titles and abstracts and excluded irrelevant studies using Rayyan QCRI [10]. Full-text articles were subsequently reviewed independently, and disagreement resolved via consensus and referral to a third reviewer (CJ). Potential overlaps between studies were identified at full-text review to prevent double counting individual patients. A decision on inclusion was made by comparing the study country, location, setting (hospital/community), participant (adults/children), study period and sample size. Data extraction was conducted using a standard electronic form while quality assessment of included studies was performed using the Newcastle–Ottawa Scale [11]. Disagreements were resolved by discussion within the wider team (AS, SA, GL and CJ). No institutional review board approval was required as this study did not independently or prospectively collect patient data.

Outcomes

The outcomes were 1) the risk of acquiring COVID-19, expressed as the proportion of confirmed COVID-19 patients with a pre-existing diagnosis of asthma; 2) risk of hospitalisation from COVID-19 (proportion of confirmed COVID-19 patients hospitalised with asthma); 3) risk of being admitted to ICU (proportion of confirmed COVID-19 patients with asthma admitted to ICU); 4) risk of being ventilated (proportion of confirmed COVID-19 patients with asthma treated with mechanical ventilation once admitted to ICU); and 5) risk of death (proportion of confirmed COVID-19 patients with asthma who are dead or alive).

Data analysis

Descriptive statistics were utilised to summarise the details of the included studies in table 1. The Newcastle–Ottawa Scale [11] was used to assess the methodological quality of included studies based on the relevant study designs cohort or case–control. One star is allocated in the domains of selection and outcome or exposure and up to two stars are allocated to the comparability domain. A total of nine stars are allocated across all three domains. An overall score of 1–3 stars is categorised as low quality, 4–6 as medium quality and 7–9 as high quality.
TABLE 1

Characteristics of included studies

First author [reference] Country Setting Design Study period COVID-19 positive Age (years) Male (n) Current smokers (n) COPD (n) Diabetes (n) Hypertension (n) NOS score (out of 9)
Asthma (n) Overall (n) Mean Median
Ahlström [ 17 ] SwedenMixedCase–control study6 March to 27 May 20201331981611465755229829
Almazeedi [ 41 ] KuwaitHospitalRetrospective cohort study24 February to 20 April 2020431096418884451551779
Arslan [ 46 ] TurkeyHospitalRetrospective cohort study18 March to 15 May 20205876751.9937480431372208
Ashinyo [ 47 ] GhanaHospitalRetrospective cohort study23 March to 29 June 20202430737.9174202197
Aveyard [ 13 ] MexicoHospitalRetrospective cohort study27 February to 21 June 20204942178 30644.188 0838
Baumer [ 12 ] UKHospitalProspective cohort study9 March to 7 May 2020125254.82298
Bergman [ 18 ] SwedenMixedCase–control studyTo mid-September 2020449368 5754626 8082168489716 4169
Beurnier [ 48 ] FranceHospitalProspective cohort study15 March to 15 April 202037112604917329
Calmes [ 49 ] BelgiumHospitalRetrospective cohort study18 March to 17 April 20205759658.75#2949
Castilla [ 19 ] SpainMixedRetrospective cohort studyJuly to December 2020233035 38738.817 17261191404189345439
Chhiba [ 50 ] USAHospitalRetrospective cohort study1 March to 15 April 2020220152653.3#654439
Choi [ 20 ] South KoreaMixedRetrospective cohort studyTo 15 May 2020218737244.5#30009
Dennis [ 30 ] UKHospitalRetrospective cohort study1 March to 27 July 2020155717 6066710 5602314219
Eggert [ 51 ] USAHospitalRetrospective cohort study1 March to 30 September 2020598559638.426351238860910219
Emami [ 52 ] IranHospitalRetrospective cohort study20 February to 1 March 202025123951.48692271767
Ferastraoaru [ 53 ] USAHospitalRetrospective cohort study14 March to 27 April 2020951455860.59
Fong [ 54 ] UKHospitalRetrospective cohort study1 March to 31 May 2020102617659
Garcia-Pachon [ 14 ] SpainCommunityRetrospective cohort study3 March to 12 April 202010376541928
Green [ 21 ] IsraelMixedRetrospective cohort studyFebruary to June 2020153226633.3112001022002769
Guan [ 55 ] ChinaHospitalRetrospective cohort studyDecember 2019 to 6 May 202024439 42055.719 6559
Gude-Sampedro [ 22 ] SpainMixedRetrospective cohort study6 March to 7 May 202028810 45458417225818061914579
Gupta [ 29 ] USAHospitalRetrospective cohort studyTo 4 March 2020305297028639362894166
Hansen [ 23 ] DenmarkMixedRetrospective cohort study1 February to 10 July 2020354510454.623994325989
Ho [ 38 ] USAHospitalRetrospective cohort study7 March to 7 June 202046810 52358.355707286167926629
Je [ 56 ] AustraliaHospitalRetrospective cohort studyMarch to April 202022197459448287
Kim [ 57 ] South KoreaHospitalCase–control studyFebruary to May 202066220056.7178592303786459
Kipourou [ 58 ] KuwaitHospitalProspective cohort study24 February to 27 May 2020235399540.42814140177307789
Lee [ 15 ] South KoreaCommunityRetrospective cohort studyJanuary to 27 May 2020686727245.32927104114019
Lemus Calderon [ 59 ] SpainHospitalRetrospective cohort studyTo July 20205776310592983873164132399
Liao [ 60 ] USAHospitalRetrospective cohort study11 March to 23 June 202041113505325711189
Lieberman-Cribbin [ 61 ] USAHospitalRetrospective cohort study29 February to 24 April 202027262455730608
Lombardi [ 62 ] ItalyHospitalRetrospective cohort study20 February to 20 April 202020104352.5#7049
Louie [ 24 ] AustraliaMixedCase series19 March to 15 May 20201099545128148
Lovinsky-Desir [ 63 ] USAMixedProspective cohort study11 February to 7 May 2020163129852762559
Martos-Benítez [ 25 ] MexicoMixedRetrospective cohort study1 January to 12 May 2020118838 32446.922 3623277889716883409
Mash [64] South AfricaHospitalRetrospective cohort studyMarch to June 202067137646.357195503645648
Mather [65] USAHospitalCase–control studyFebruary to November 202088104564.6352182213078
Murillo-Zamora [66] MexicoHospitalRetrospective cohort study4 March to 15 August 2020144866 12352.440 124261921 84026 7289
Nystad [26] NorwayMixedRetrospective cohort study1 March to 13 May 2020515763233.22#1614689777
Patone [27] UKMixedRetrospective cohort study1 November to 26 January 202129 792198 42037.793 76522 134187310 34719 6369
Robinson [67] USAHospitalCase–control study4 March to 2 July 20205623248519111313211078
Rosenthal [68] USAHospitalRetrospective cohort studyMarch to May 202010572749.461652788
Salacup [69] USAHospitalRetrospective cohort study1 March to 24 April 20201824266123301181808
Schönfeld [28] ArgentinaMixedRetrospective cohort study3 March to 2 October 202012 580207 07941103 4874074440520 05839 8339
Shah [70] USAHospitalRetrospective cohort study3 February to 31 March 20204336322019168
Tutiya [71] BrazilHospitalRetrospective cohort study13 March to 7 June 2020711432.4012137
Valverde-Monge [72] SpainHospitalRetrospective cohort study31 January to 17 April 2020113253962.6612751548940310549
Wang [40] ChinaHospitalRetrospective cohort study28 January to 25 February 202068562472658
Yang [37] South KoreaCommunityRetrospective cohort study1 January to 15 May 2020725734047.1297035095116389
Yordanov [16] FranceMixedProspective cohort studyMarch to August 20208147320432301790874029786
Zhang [31] ChinaHospitalRetrospective cohort study29 December 2019 to 16 February 202012905715510627818

COVID-19: coronavirus disease 2019; NOS: Newcastle–Ottawa Scale. #: imputed values based on weighted average.

Characteristics of included studies COVID-19: coronavirus disease 2019; NOS: Newcastle–Ottawa Scale. #: imputed values based on weighted average. Two main sets of meta analyses were performed. To pool the prevalence of asthmatics among those with COVID-19, we used the binomial distribution to model the within-study variability and calculated Wilson score 95% confidence intervals. For all the binary outcomes, we performed Sidik–Jonkman random-effects meta-analysis (assuming that there is not only one true effect size, but a distribution of true effect sizes). We assessed the quantitative heterogeneity by conducting a formal test of homogeneity and evaluating the proportion of variability due to heterogeneity (I2). Pre-specified subgroup analyses were conducted by continent and by the quality of the studies (low, medium, high) and univariable meta-regressions using age and proportions of current and former smokers as covariates. The assessment of small-study effects has been done by regression-based Egger test and eyeball evaluation of the contour-enhanced funnel plots. Along with the pooled effect sizes and 95% confidence intervals, we also reported the prediction intervals. All pooled results are presented in the form of forest plots. All statistical analyses were performed using Stata 16 (StataCorp LLC, College Station, TX, USA).

Results

The searches resulted in 32 379 citations. After duplicates were removed, 20 559 titles and abstracts were screened, 19 559  articles were excluded. Of the remaining 1000 articles, 949 were excluded after full-text review. A total of 51 studies were included in the review. Studies with overlapping patient populations were excluded if they reported the same outcome (figure 1).
FIGURE 1

Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram [73]. CENTRAL: Cochrane Central Register of Controlled Trials; WHO: World Health Organization; COVID-19: coronavirus disease 2019.

Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram [73]. CENTRAL: Cochrane Central Register of Controlled Trials; WHO: World Health Organization; COVID-19: coronavirus disease 2019.

Descriptive characteristics

This review is based on a pooled sample of 1 471 643 COVID-19-tested patients, of whom 965 551 were COVID-19 positive with reported information related to asthma. The sample sizes ranged from 52 [12] to 417 366 [13]. Most of the studies were hospital-based (34 studies) while three were studies [14-16] in the community and 14 had a mixed setting [16-28]. Studies originate from 21 countries spread on all five continents: Europe (n=17), North America (n=13), Asia (n=12), South America (n=5), Africa (n=2) and Australia (n=2). The summary of included studies is presented in table 1. Among COVID-19 positive patients, based on RT-PCR assay results, the mean±sd age of participants was 52.0±12.9 years, 42.64% were male (n=459 640 from 47 out of 51 studies), 5.4% were current smokers (n=38 672 from 23 out of 51 studies) and 9.8% were former smokers (n=43 622 from 10 out of 51 studies). The prevalence of asthma among those infected with COVID-19 was 8.08% (95% CI 6.87–9.30%; test of homogeneity p<0.001). ∼25% had hypertension (n=135 274 from 35 out of 51 studies), 14.3% had diabetes (n=78 923 from 38 out of 51 studies) and 3% had COPD (n=15 636 from 29 out of 51 studies).

Risk-of-bias results

Scores on the Newcastle–Ottawa Scale ranged between 6 and 9 (maximum 9) [16, 29], with a higher score indicating a higher quality. All studies scored ≥7 and were of high quality. A full assessment is presented in supplementary table S3.

Meta-analysis of the risk of acquiring COVID-19

The pooled analysis of 10 studies (n=785 151) showed a risk ratio reduction in acquiring COVID-19 of 17% for people with asthma compared to those without asthma (risk ratio 0.83, 95% CI 0.73–0.95; p=0.01; figure 2). There was considerable heterogeneity (I2=98.46%) across the studies. Meta-regression by age revealed that older age was associated with increased risk of acquiring COVID-19 in individuals with asthma (meta-regression coefficient 0.014, 95% CI 0.004–0.025; p=0.006). Furthermore, R2 showed that 45.51% of the variance between studies can be explained by age. Heterogeneity remains high when age is included as a moderator in the meta-regression (I2=92.03%) meaning that it is not a main factor in the difference between studies. No statistically significant association for current smoker (five out of 10 studies; p=0.09) and former smoker were found (two out of 10 studies; p=0.94).
FIGURE 2

Risk of acquiring coronavirus disease 2019 (COVID-19) in individuals with asthma compared with no asthma.

Risk of acquiring coronavirus disease 2019 (COVID-19) in individuals with asthma compared with no asthma.

Meta-analysis of the risk of hospitalisation

We observed a non-statistically significant different risk for hospitalisation from COVID-19 for people with asthma compared to no asthma (risk ratio 1.18, 95% CI 0.98–1.42; p=0.08), in the 18 studies (n=411 093) included in this analysis. There was considerable heterogeneity observed (I2=98.86%) across the studies (figure 3). Meta-regression by age, current smoker (only from nine out of 18 studies) and former smoker (only from six out of 18 studies) revealed no relevant association in risk of being hospitalised with COVID-19 in individuals with asthma.
FIGURE 3

Risk of hospitalisation when infected with coronavirus disease 2019 in individuals with asthma compared with no asthma.

Risk of hospitalisation when infected with coronavirus disease 2019 in individuals with asthma compared with no asthma.

Meta-analysis of the risk of ICU admission

There was a non-statistically significant different risk of ICU admission (risk ratio 1.21, 95% CI 0.97–1.51; p=0.09) for people with asthma compared to those without asthma in a pooled analysis of 21 studies (n=192 694). Substantial heterogeneity was observed (I2=94.21%) across the studies (figure 4). Meta-regression with former smoker (four out of 21 studies) as moderator found a statistically significant decrease in risk of ICU admission (meta-regression coefficient −0.00009, 95% CI −0.0002– −2.65×106; p=0.043). Meta-regression with age and current smoker (nine out of 21 studies) as moderator did not reveal statistically significant results (p=0.15 and p=0.37, respectively).
FIGURE 4

Risk of intensive care unit (ICU) admission when infected with coronavirus disease 2019 in individuals with asthma compared with no asthma.

Risk of intensive care unit (ICU) admission when infected with coronavirus disease 2019 in individuals with asthma compared with no asthma.

Meta-analysis of the risk of ventilator use when admitted into the ICU

In relation to probability of mechanical ventilation, of the 11 studies (n=101 694) pooled for this analysis, there was no statistically significant difference in risk of being treated with ventilator once admitted to ICU for people with asthma compared to those without asthma (risk ratio 1.06, 95% 0.82–1.36; p=0.65). Considerable heterogeneity was observed (I2=87.91%) across the studies (figure 5). Meta-regression with age and current smoker (four out of 11 studies) did not reveal statistically significant results (p=0.276 and p=0.260, respectively). Whereas meta-regression with former smoker as a moderator (two out of 11 studies) found a reduction in risk of ventilator use (meta-regression coefficient −0.0022, 95% CI −0.0037– −0.0007; p=0.004).
FIGURE 5

Risk of mechanical ventilator (MV) use upon admission to intensive care unit with coronavirus disease 2019 in individuals with asthma compared with no asthma.

Risk of mechanical ventilator (MV) use upon admission to intensive care unit with coronavirus disease 2019 in individuals with asthma compared with no asthma.

Meta-analysis of the risk of death

There was a non-statistically significant different risk of death from COVID-19 for people with asthma compared to those without asthma in the 32 studies (n=379 381) pooled for this analysis (risk ratio 0.94, 95% CI 0.76–1.17; p= 0.58). Considerable heterogeneity was observed (I2=94.85%) across the studies (figure 6). When age was included as moderator for meta-regression, there was no statistically significant reduction in risk of death by age (p=0.219). No statistically significant association was also found for current smoker (14 out of 21 studies) and former smoker (seven out of 21 studies) as a moderator (p=0.458 and p=0.288, respectively).
FIGURE 6

Risk of death when infected with coronavirus disease 2019 in individuals with asthma compared with no asthma.

Risk of death when infected with coronavirus disease 2019 in individuals with asthma compared with no asthma.

Subgroup analyses

Subgroup analyses by continent revealed substantial differences in risk of acquiring COVID-19 between the continents (statistically significant at p=0.001) during the period up to 11 July 2021. It showed the lowest risk in Asia (risk ratio 0.66, 95% CI 0.57–0.75) followed by North America (risk ratio 0.78, 95% CI 0.69–0.89), South America (risk ratio 0.84, 95% CI 0.82–0.85) and Europe (risk ratio 1.01, 95% CI 0.82–1.26). No major differences were found between continents in hospitalisation (p=0.128). However, relevant differences in ICU admission were found between continents (statistically significant at p=0.007). The highest risk was found to be in Asia (risk ratio 1.81, 95% CI 1.12–2.91) followed by Europe (risk ratio 1.04, 95% CI 0.86–1.27), North America (risk ratio 0.96, 95% CI 0.72–1.27) and lowest in South America (risk ratio 0.84, 95% CI 0.75–0.93). In addition, risk of ventilator use was statistically significant different across the continents (p<0.001). The highest risk was found to be in Europe (risk ratio 1.59, 95% CI 1.26–2.00), followed by Asia (risk ratio 1.19, 95% CI 0.74–1.91), North America (risk ratio 1.02, 95% CI 0.74–1.42) and South America (risk ratio 0.50, 95% CI 0.82–1.36). Similarly, risk of death was quite different across the continents (p=0.011). The highest risk was found to be in Asia (risk ratio 2.01, 95% CI 1.19–3.39), followed by Europe (risk ratio 0.85, 95% CI 0.68–1.05), North America (risk ratio 0.79, 95% CI 0.58–1.06) and South America (risk ratio 0.72, 95% CI 0.47–1.12). Subgroup analyses by study quality for risk for death showed significantly higher risk in the one study of medium quality compared to the 30 higher-quality ones (risk ratio 1.45, 95% CI 1.14–1.87 versus risk ratio 0.92, 95% CI 0.74–1.15; p=0.007).

Publication bias

Egger's test showed evidence of small-study effects for the pooled proportion of COVID-19-positive (RT-PCR) individuals (p<0.0001) and risk of hospitalisation (p=0.0199), but not for all other outcomes (supplementary table S3). Eyeball assessment of the contour enhanced funnel plots revealed asymmetry only for the risk of hospitalisation, but not other outcomes (supplementary figures S1–S6).

Discussion

This meta-analysis aimed to rigorously assess the vulnerability of patients with asthma to COVID-19 based on controlled studies. It revealed an 8.08% prevalence of asthma among those who tested COVID-19 positive based on RT-PCR. This pooled prevalence is higher than the 7.46% prevalence in our previous meta-analysis [30] which analysed studies including pre-prints until May 2020. Only one study [31] from the previous meta-analysis was included in this meta-analysis. This is due to the tighter inclusion criteria of including only published studies with a non-asthma control group, and excluding case series and single-arm cohort studies. Furthermore, both these prevalence rates were lower than the global prevalence of self-reported asthma symptoms of 8.6% [32]. While the proportion estimated in this meta-analysis is lower than in two recent studies in the UK [27] which reported a prevalence of ∼15% in those infected with the B.1.1.7 variant; lower prevalence rates have been reported in other studies in Italy [33] and in Turkey [34] (2.1% among 2000 patients and 3.7% among 565 patients, respectively). In the studies that report them, we found a high pooled proportion of hypertension (25.7%) and diabetes (14.3%) as comorbidities. These were mostly contributed by hospital studies (22 of the 35 studies reporting hypertension and 24 of the 38 studies reporting diabetes). This study found a statistically significant risk reduction of 17% (95% CI 5–27%) for acquiring COVID-19, similar to the 14% reduction reported in our previous study [5]. This result is similar to a study from Missouri, USA which reported lower COVID-19 test positivity rates in asthmatics versus non-asthmatics (69.2% versus 81.9%) [35]. Furthermore, a community study in Mexico showed a lower proportion of asthmatics in a COVID-19 positive group compared to a negative group (2.8% versus 3.7%; OR 0.74, 95% CI 0.71–0.77) [21, 36]. Subgroup analyses by continent revealed significant differences in risk of acquiring COVID-19 between the continents, the lowest risk being in Asia (risk ratio 0.66, 95% CI 0.57–0.75) followed by North America (risk ratio 0.78, 95% CI 0.69–0.89), South America (risk ratio 0.84, 95% CI 0.82–0.85) and Europe (risk ratio 1.01, 95% CI 0.82–1.26). Additionally, we noted the consistent nature of the risk reduction in three out of the four regions where data are available. The risk reduction in Asia was found to be consistent in the three studies pooled from China [31], Israel [21] and South Korea [37]; all countries with a high testing regime which might account for this variance between regions. However, analysis of community studies such as this could better reflect the true nature of the risk compared to analysis of hospital-based studies. In addition, it is important to note that this result may not reflect other countries in Asia such as India and Southeast Asia where testing regimes have not been as extensive. Several possible mechanisms might contribute to a lower risk of acquiring COVID-19 in people with asthma compared to a non-asthmatic population. A retrospective study by Ho et al. [38] showed that not only is asthma associated with lower risk of poor outcomes, but the presence of eosinophilia (≥200 cells·μL−1) both in those with and without asthma was also reported to be associated with reduced mortality risk. While not statistically significant, a higher proportion of those with asthma in this study had eosinophilia compared to non-asthmatics (38.2% versus 32.3%) [38]. Furthermore, a lower risk of acquiring COVID-19 may be attributed to the expression of the angiotensin-converting enzyme (ACE)2 receptor, which is significantly lower in asthma patients compared to those with COPD and healthy controls, as reported in another study [6] which showed that ACE2 expression is increased with older age (at p=0.03). This supports the result of our analysis, which showed strong evidence of increasing age being associated with increased risk of acquiring COVID-19. Finally, people with asthma have been advised by health authorities to practise social distancing and be particularly careful to avoid contracting COVID-19. This was especially the case early in the pandemic when the added risks of having an underlying lung condition were assumed to be substantial. To the extent that these messages [39] were taken seriously by people with asthma, their risk of acquiring infection could have been commensurately reduced. We also found similar risks for hospitalisation, ICU admission when hospitalised and ventilator use in this study. Even so, we note that for hospitalisation, while not statistically significant, the pooled point estimate suggests a possible 18% increased risk of hospitalisation from COVID-19 for people with asthma, with a wide confidence interval (95% CI −2–42%). Similarly, for ICU admission, while not statistically significant, the pooled point estimate suggests a possible 21% increased risk of ICU admission from COVID-19 for people with asthma (95% CI −3–51%). One study from China [40] and another from Kuwait [41] reported risk ratios of 5.16 and 4.08, respectively, far greater than in other studies. These differences in risk may be linked to resource allocation and availability or difference in vulnerability due to ethnicity or other environmental factors. An important finding of this current study and our previous meta-analysis is the similar risk of death between asthmatics and non-asthmatics from COVID-19. While this may be due to a variety of factors, two recent randomised controlled trials of budesonide (an inhaled corticosteroid frequently prescribed to patients with asthma) [42, 43] have raised the possibility that this is an effect of the inhaled corticosteroid. They reported that early administration of inhaled budesonide reduced the likelihood of urgent medical care and reduced time to recovery from COVID-19. One of these studies, the STOIC open-label trial in 146 participants showed a number needed to treat of eight with budesonide to reduce COVID-19 deterioration, and that clinical recovery occurred a day faster in the budesonide group compared to usual care (7 days, 95% CI 6–9 days versus 8 days, 7–11 days; log-rank test p=0.007) [42]. The other study is an interim analysis of the PRINCIPLE trial published as a pre-print, which randomised 751 participants to budesonide compared with 1028 usual care and 643 on other interventions showed a faster recovery in the budesonide group compared to usual care (hazard ratio 1.208, 95% Bayesian credible interval (BCI) 1.076–1.356; probability of superiority 0.999, estimated benefit of 3.011 days, 95% BCI 1.134–5.41 days) [43]. A limitation of this study is the inclusion of very few studies originating from Africa and South America. Additionally, most of the studies were hospital-based, which is likely to be a consequence of including only COVID-19 cases confirmed by RT-PCR. We chose RT-PCR positivity to give more certainty to our estimation of the association between asthma and several important COVID-19 outcomes. As PCR testing regimens show substantial variation between countries, our results might not be generalisable to regions which are poorer and marginalised or to groups that might be less likely to seek testing. In these regions, it is likely that due to under-testing the true proportion of asthmatics as well as the general public with COVID-19 is substantially higher than official reports, by a magnitude of multiple folds [44, 45]. Potential selection bias to those more unwell may also be present due to the large number of hospital-based studies included in this review. Even so, 10 of the studies found to calculate the risk of getting the infection were community based (n=726 269), which we hope provides a better representation of risk for the general community. There was minimal information provided on smoking (only 23 out of 51 studies indicated the proportion of current smokers, and 10 out of 51 indicated the proportion of former smokers). Hence, based on the 10 studies, we found that being a former smoker was associated with a lower risk of ICU admission; however, this minimal information limits the generalisability of our assessment of the impact of smoking. Despite these limitations, the majority of studies we included were of high quality with minimal selection bias due to their large sample sizes, data sourcing through electronic health records or data linkages which resulted in minimal loss to follow-up. Additionally, we used hard outcome measures such as COVID-19 infection (PCR positivity), hospitalisation, ICU admission and death, which are generally well-defined globally, limiting the risk of classification bias. Funnel plots and Egger's test for small-study effects were also conducted to explore the presence of publication bias and we found that most outcomes do not show signs of publication bias. Furthermore, our conclusions are based on studies which report details of both asthma and non-asthma patients where COVID-19 infection status was confirmed by RT-PCR results and not only by symptoms or suspected cases in the context of the pandemic. We did not have access to information that would enable us to determine if people with asthma were over-represented among mild or asymptomatic cases that did not receive testing. In conclusion, the findings from this analysis indicate the prevalence of asthma was 8.08% among people who were RT-PCR-positive for COVID-19 in these controlled studies. The overall findings suggest that people with asthma are at lower risk of being infected with COVID-19 compared to those without asthma, but have a similar risk of hospitalisation, ICU admission, ventilator use and mortality when RT-PCR-positive. With the fast evolution of the severe acute respiratory syndrome coronavirus 2 virus and the emergence of variants globally, caution must be maintained for people with asthma. There remains a need for higher-quality community studies as well as regular risk assessments and review of new data throughout the pandemic. Furthermore, additional studies are required to confirm this risk profile, particularly in Africa and South America, where none of the eligible studies originated. Please note: supplementary material is not edited by the Editorial Office, and is uploaded as it has been supplied by the author. Supplementary tables and figures ERJ-01209-2021.Supplement Appendix 1 ERJ-01209-2021.Appendix_1 Appendix 2 ERJ-01209-2021.Appendix_2 This one-page PDF can be shared freely online. Shareable PDF ERJ-01209-2021.Shareable
  68 in total

1.  Low prevalence of asthma in Mexican children and adults with a positive rtRT-PCR test for SARS-CoV-2: a cross-sectional study during the 2020 pandemic.

Authors:  Martín Bedolla-Barajas; Jaime Morales-Romero; Tonatiuh Ramses Bedolla-Pulido; Carlos Meza-López; Martín Robles-Figueroa; Norma Angélica Pulido-Guillén; Luis Gustavo Orozco-Alatorre; Carlos Alberto Andrade-Castellanos
Journal:  Allergol Immunopathol (Madr)       Date:  2021-05-01       Impact factor: 1.667

2.  Prevalence and characterization of asthma in hospitalized and nonhospitalized patients with COVID-19.

Authors:  Krishan D Chhiba; Gayatri B Patel; Thanh Huyen T Vu; Michael M Chen; Amina Guo; Elizabeth Kudlaty; Quan Mai; Chen Yeh; Lutfiyya N Muhammad; Kathleen E Harris; Bruce S Bochner; Leslie C Grammer; Paul A Greenberger; Ravi Kalhan; Fei Li Kuang; Carol A Saltoun; Robert P Schleimer; Whitney W Stevens; Anju T Peters
Journal:  J Allergy Clin Immunol       Date:  2020-06-15       Impact factor: 10.793

3.  Asthma and COPD Are Not Risk Factors for ICU Stay and Death in Case of SARS-CoV2 Infection.

Authors:  Doriane Calmes; Sophie Graff; Nathalie Maes; Anne-Noëlle Frix; Marie Thys; Olivier Bonhomme; Julien Berg; Mathieu Debruche; Fanny Gester; Monique Henket; Virginie Paulus; Bernard Duysinx; Vincent Heinen; Delphine Nguyen Dang; Astrid Paulus; Valérie Quaedvlieg; Frederique Vaillant; Hélène Van Cauwenberge; Michel Malaise; Alisson Gilbert; Alexandre Ghuysen; Pierre Gillet; Michel Moutschen; Benoit Misset; Anne Sibille; Julien Guiot; Jean-Louis Corhay; Renaud Louis; Florence Schleich
Journal:  J Allergy Clin Immunol Pract       Date:  2020-10-07

4.  Asthma and COVID-19: a systematic review.

Authors:  Natália F Mendes; Carlos P Jara; Eli Mansour; Eliana P Araújo; Licio A Velloso
Journal:  Allergy Asthma Clin Immunol       Date:  2021-01-06       Impact factor: 3.406

5.  Clinical presentation and outcomes of the first patients with COVID-19 in Argentina: Results of 207079 cases from a national database.

Authors:  Daniel Schönfeld; Sergio Arias; Juan Carlos Bossio; Hugo Fernández; David Gozal; Daniel Pérez-Chada
Journal:  PLoS One       Date:  2021-02-11       Impact factor: 3.240

6.  Asthma in patients with coronavirus disease 2019: A systematic review and meta-analysis.

Authors:  Li Shi; Jie Xu; Wenwei Xiao; Ying Wang; Yuefei Jin; Shuaiyin Chen; Guangcai Duan; Haiyan Yang; Yadong Wang
Journal:  Ann Allergy Asthma Immunol       Date:  2021-02-18       Impact factor: 6.347

7.  COVID-19 severity in asthma patients: a multi-center matched cohort study.

Authors:  Lacey B Robinson; Liqin Wang; Xiaoqing Fu; Zachary S Wallace; Aidan A Long; Yuqing Zhang; Carlos A Camargo; Kimberly G Blumenthal
Journal:  J Asthma       Date:  2021-03-02       Impact factor: 2.515

8.  Clinical characteristics, treatment regimen and duration of hospitalization among COVID-19 patients in Ghana: a retrospective cohort study.

Authors:  Mary Eyram Ashinyo; Vida Duti; Stephen Dajaan Dubik; Kingsley Ebenezer Amegah; Selorm Kutsoati; Ebenezer Oduro-Mensah; Peter Puplampu; Martha Gyansa-Lutterodt; Delese Mimi Darko; Kwame Ohene Buabeng; Anthony Ashinyo; Anthony Adofo Ofosu; Nyonuku Akosua Baddoo; Samuel Kaba Akoriyea; Francis Ofei; Patrick Kuma-Aboagye
Journal:  Pan Afr Med J       Date:  2020-09-15

9.  Association between pre-existing respiratory disease and its treatment, and severe COVID-19: a population cohort study.

Authors:  Paul Aveyard; Min Gao; Nicola Lindson; Jamie Hartmann-Boyce; Peter Watkinson; Duncan Young; Carol A C Coupland; Pui San Tan; Ashley K Clift; David Harrison; Doug W Gould; Ian D Pavord; Julia Hippisley-Cox
Journal:  Lancet Respir Med       Date:  2021-04-01       Impact factor: 30.700

10.  Asthma phenotypes, associated comorbidities, and long-term symptoms in COVID-19.

Authors:  Lauren E Eggert; Ziyuan He; William Collins; Alexandra S Lee; Gopal Dhondalay; Shirley Y Jiang; Jessica Fitzpatrick; Theo T Snow; Benjamin A Pinsky; Maja Artandi; Linda Barman; Rajan Puri; Richard Wittman; Neera Ahuja; Andra Blomkalns; Ruth O'Hara; Shu Cao; Manisha Desai; Sayantani B Sindher; Kari Nadeau; R Sharon Chinthrajah
Journal:  Allergy       Date:  2021-06-19       Impact factor: 14.710

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  13 in total

1.  Insights into potential mechanisms of asthma patients with COVID-19: A study based on the gene expression profiling of bronchoalveolar lavage fluid.

Authors:  Yong Jiang; Qian Yan; Cheng-Xin Liu; Chen-Wen Peng; Wen-Jiang Zheng; Hong-Fa Zhuang; Hui-Ting Huang; Qiong Liu; Hui-Li Liao; Shao-Feng Zhan; Xiao-Hong Liu; Xiu-Fang Huang
Journal:  Comput Biol Med       Date:  2022-05-19       Impact factor: 6.698

2.  Impact of asthma, chronic obstructive pulmonary disease (COPD), and asthma-COPD overlap on the prognosis of coronavirus disease 2019.

Authors:  Eunyong Shin; Juhae Jin; Seo Young Park; Young Sang Yoo; Ji-Hyang Lee; Jin An; Woo-Jung Song; Hyouk-Soo Kwon; You Sook Cho; Hee-Bom Moon; Jung-Bok Lee; Tae-Bum Kim
Journal:  Asia Pac Allergy       Date:  2022-04-28

3.  Disease Severity and Comorbidities among Healthcare Worker COVID-19 Admissions in South Africa: A Retrospective Analysis.

Authors:  Edith Ratshikhopha; Munyadziwa Muvhali; Nisha Naicker; Nonhlanhla Tlotleng; Waasila Jassat; Tanusha Singh
Journal:  Int J Environ Res Public Health       Date:  2022-05-02       Impact factor: 4.614

4.  Asthma and prognosis of coronavirus disease 2019.

Authors:  Öner Özdemir
Journal:  World Allergy Organ J       Date:  2022-05-31       Impact factor: 5.516

Review 5.  Impact of asthma on COVID-19 mortality in the United States: Evidence based on a meta-analysis.

Authors:  Xueya Han; Jie Xu; Hongjie Hou; Haiyan Yang; Yadong Wang
Journal:  Int Immunopharmacol       Date:  2021-11-22       Impact factor: 4.932

6.  Celebrating World Asthma Day in Brazil: lessons learned from the pandemic. Can we do better?

Authors:  Marcia Margaret Menezes Pizzichini; Regina Maria de Carvalho-Pinto; Emilio Pizzichini
Journal:  J Bras Pneumol       Date:  2022-06-10       Impact factor: 2.800

7.  Significant association of pre-existing asthma with an increased risk for ICU admission among COVID-19 patients: Evidence based on a meta-analysis.

Authors:  Xueya Han; Jie Xu; Hongjie Hou; Haiyan Yang; Yadong Wang
Journal:  J Infect       Date:  2021-11-29       Impact factor: 38.637

8.  Acceptance Rates of COVID-19 Vaccine Highlight the Need for Targeted Public Health Interventions.

Authors:  Vered Shkalim Zemer; Zachi Grossman; Herman Avner Cohen; Moshe Hoshen; Maya Gerstein; Noga Yosef; Moriya Cohen; Shai Ashkenazi
Journal:  Vaccines (Basel)       Date:  2022-07-22

9.  SARS-CoV-2-Specific Adaptive Immunity in COVID-19 Survivors With Asthma.

Authors:  Li Chen; Junqing Yue; Shengding Zhang; Wenxue Bai; Lu Qin; Cong Zhang; Bihao Wu; Moxuan Li; Shuyun Xu; Qing Jiang; Lin Yang; Qingxiu Xu; Rongfei Zhu; Min Xie; Rui Gong
Journal:  Front Immunol       Date:  2022-07-18       Impact factor: 8.786

10.  In-hospital severe COVID-19 in a philanthropic tertiary hospital setting: is asthma a concern? A retrospective study.

Authors:  Gabriela Accetta Rojas; Flávia Nascimento Ost; Roberto Stirbulov; Ozíris Simões
Journal:  Sao Paulo Med J       Date:  2022 Sep-Oct       Impact factor: 1.838

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