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. 2021 Feb 18;126(5):524–534. doi: 10.1016/j.anai.2021.02.013

Asthma in patients with coronavirus disease 2019

A systematic review and meta-analysis

Li Shi ∗, Jie Xu ∗, Wenwei Xiao ∗, Ying Wang ∗, Yuefei Jin ∗, Shuaiyin Chen ∗, Guangcai Duan ∗, Haiyan Yang ∗,∗, Yadong Wang †,∗∗
PMCID: PMC7889465  PMID: 33609770

Abstract

Background

It is unclear whether asthma has an influence on contracting coronavirus disease 2019 (COVID-19) or having worse outcomes from COVID-19 disease.

Objective

To explore the prevalence of asthma in patients with COVID-19 and the relationship between asthma and patients with COVID-19 with poor outcomes.

Methods

The pooled prevalence of asthma in patients with COVID-19 and corresponding 95% confidence interval (CI) were estimated. The pooled effect size (ES) was used to evaluate the association between asthma and patients with COVID-19 with poor outcomes.

Results

The pooled prevalence of asthma in patients with COVID-19 worldwide was 8.3% (95% CI, 7.6-9.0) based on 116 articles (119 studies) with 403,392 cases. The pooled ES based on unadjusted effect estimates revealed that asthma was not associated with reduced risk of poor outcomes in patients with COVID-19 (ES, 0.91; 95% CI, 0.78-1.06). Similarly, the pooled ES based on unadjusted effect estimates revealed that asthma was not associated with the reduced risk of mortality in patients with COVID-19 (ES, 0.88; 95% CI, 0.73-1.05). However, the pooled ES based on adjusted effect estimates indicated that asthma was significantly associated with reduced risk of mortality in patients with COVID-19 (ES 0.80, 95% CI 0.74-0.86).

Conclusion

The pooled prevalence of asthma in patients with COVID-19 was similar to that in the general population, and asthma might be an independent protective factor for the death of patients with COVID-19, which suggests that we should pay high attention to patients co-infected asthma and COVID-19 and take locally tailored interventions and treatment. Further well-designed studies with large sample sizes are required to verify our findings.

Introduction

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel betacoronavirus, caused the coronavirus disease 2019 (COVID-19), which has posed huge challenges to global public health. To date (data as of September 28, 2020), more than 32.7 million confirmed cases and more than 991,000 deaths have been reported worldwide.1 The continuous increase of confirmed cases and related clinical studies has led to a greater understanding of COVID-19. Many comorbidities have been identified as risk factors for patients with COVID-19 with poor outcomes, such as diabetes, hypertension, malignancies, cardiovascular diseases, and chronic obstructive pulmonary disease, which can help clinicians identify patients with poor prognosis at an early stage and thus contribute to the control and prevention of COVID-19.2

Asthma, a common chronic disease, can be exacerbated by viral respiratory infections,3 which has recently attracted considerable attention of researchers focused on COVID-19. Nevertheless, the prevalence of asthma in patients with COVID-19 and the association between asthma and patients with COVID-19 with poor outcomes remains highly controversial. Zhang et al4 identified particularly low prevalence of asthma (0.3%) among 289 patients with COVID-19 in Wuhan, which was significantly lower than local population asthma prevalence (4.2%).5 Conversely, Latz et al6 pointed out that patients with asthma accounted for up to 26.9% of included patients with COVID-19 in the state of Massachusetts. In addition, the studies conducted by Yehia et al7 and Siso-Almirall et al8 indicated that asthma was not a predictive comorbidity for death of patients with COVID-19. However, Almazeedi et al9 reported that asthma was associated with an increased risk of death in patients with COVID-19, whereas Hernandez-Galdamez et al10 and Santos et al11 found that asthma was a protective factor of death.

In view of the above-mentioned studies, a systematic and quantitative meta-analysis to explore the prevalence of asthma in patients with COVID-19 and the relationship between asthma and patients with COVID-19 with poor outcomes would be of paramount importance.

Methods

Search Strategy and Selection Criteria

We conducted a systematical search of PubMed, Web of Science, and EMBASE databases to recognize eligible studies published from inception to September 18, 2020, using the following terms and keywords: “asthma” or “respiratory diseases” or “comorbidities” or “clinical” AND “novel coronavirus” or “nCoV” or “2019-nCoV” or “COVID-19” or “coronavirus” or “severe acute respiratory syndrome coronavirus 2” or “SARS-CoV-2.” The literature search was not restricted by language. The reference lists of all pertinent studies and reviews were sifted to identify other eligible studies. In addition, when publications with overlapping data were found, only the articles with the larger sample size or more complete analysis were included. EndNote (version X9.0, Thomson ResearchSoft, Stanford, Connecticut) was used for the management of literature. Our analyses were carried out on September 20, 2020, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis statement (eTable 1).12

Inclusion criteria were the following: (1) all patients enrolled in articles were diagnosed as having COVID-19; and (2) articles clearly reported the number of patients with co-infection of asthma and COVID-19.

Exclusion criteria were as follows: (1) abstracts, reviews, meta-analysis, and errata; (2) studies with the sample size fewer than 100 patients; (3) articles with overlapping data; and (4) articles reporting unclear prevalence of asthma in patients with COVID-19.

Data Extraction and Quality Assessment

Notably, 2 researchers (Li Shi and Wenwei Xiao) respectively reviewed all literatures according to the inclusion and exclusion criteria and excerpted the following information: author, location or country, study design, total number of patients, age, sex, settings, the number of patients co-infected asthma and COVID-19, and the number of patients with asthma with poor outcomes (eg, patients diagnosed with having severe or critical COVID-19, or admitted to intensive care unit [ICU], or required mechanical ventilation [MV], or died). Any conflicts were resolved by group discussion.

The quality of the enrolled studies was evaluated by 2 independent researchers using the Agency for Healthcare Research and Quality score checklist.13 The quality of the studies was graded as low (0-3), moderate (4-7), or high (8-11), according to the corresponding range of scores.

Statistical Analysis

All statistical analyses were carried out using R (version 3.6.3, R Foundation for Statistical Computing, Vienna, Austria) and Stata (version SE 12.1, StataCorp, College Station, Texas). A meta-analysis of the included studies was done with the metaprop command in R to calculate the pooled prevalence of asthma in patients with COVID-19. Furthermore, a meta-analysis of the included studies was done with the metan command in Stata to evaluate the risk of having poor outcomes in patients with COVID-19 and asthma co-infection. Considering the influence of various factors such as sex, age, and other comorbidities on the risk of mortality in patients with COVID-19,2 the pooled effect size (ES) and corresponding 95% confidence interval (CI) were calculated on the basis of the studies reporting the adjusted effect estimates. The χ2-based Q test (represented as χ2 and P values) and I 2 statistic were applied to evaluate the heterogeneity among studies.14 If I 2 was less than 50% or P was greater than .05, we used the fixed-effects model. Otherwise, the random-effects model was chosen. Considering the obvious heterogeneity of our analysis, subgroup and meta-regression analyses were conducted to investigate possible factors that caused heterogeneity. The factors that we investigated were sample size, study design, region, settings, and quality score. Publication bias was examined by Begg test and Egger test.15 , 16 P values less than .05 were regarded as statistically significant.

Results

Study Selection

Initially, 49,026 records were retrieved by our search strategy. By deleting duplicates of original retrieved articles, 28,553 related articles were obtained. A total of 209 articles that reported the prevalence of asthma in patients with COVID-19 were yielded after reading the titles and abstracts. Subsequently, 44 articles were excluded because of a sample size less than 100, 47 articles were eliminated owing to the potential duplicate patients, and 2 articles were removed because they reported unclear prevalence of asthma in patients with COVID-19 (eTable 2). Ultimately, 116 articles (119 studies)4 , 6, 7, 8, 9, 10, 11 , 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125 with 403,392 patients with COVID-19 passed multiple screening (Fig 1 ).

Figure 1.

Figure 1

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Study selection. COVID-19, coronavirus disease 2019.

Study Characteristics

All patients in enrolled articles were diagnosed with having COVID-19 (eTable 3). The main characteristics of the enrolled studies are found in Table 1 . The included studies were from different countries and regions around the world, of which 64 from the Americas, 28 from Europe, 22 from Asia, 1 from the Middle East, and 4 from other countries. In terms of the study design, 101 were retrospective studies, 7 prospective studies, 5 cross-sectional studies, and 3 each ambispective studies and randomized controlled trials. Through qualitative assessment, 47 studies were of high quality, 71 studies of moderate quality, and the remaining 1 study of low quality (eTable 4).

Table 1.

Baseline Characteristics of the Included Studies

Author Study design Location or country Sample size Male (%) Age (y) Settings (%) Asthma (%) Poor outcomes (%)a Quality score
America
 Adrish et al17 Retrospective US 469 279 (59.5) N/R Inpatient (100) 83 (17.7) N/R 6
 Agarwal et al18 Retrospective US 404 297 (73.5) 61 (median) Inpatient/Outpatient 25 (6.2) N/R 7
 Argyropoulos et al19 Retrospective US 205 108 (52.7) N/R Inpatient (19.5)
Outpatient (80.5)		 26 (12.7) N/R 6
 Arshad et al20 Retrospective US 2541 1298 (51.1) 63.7 (mean) Inpatient (100) 251 (9.9) N/R 9
 Bajaj et al21 Retrospective US 108 37 (34.3) 61.3 (mean) Inpatient (100) 9 (8.3) N/R 6
 Broadhurst et al22 Cross-sectional US 436 239 (50.1)b 54.7 (mean) Inpatient (100) 53 (12.2) 15 (10.8)b 4
 Capone et al23 Retrospective US 102 55 (53.9) 63.3 (mean) Inpatient (100) 12 (11.8) 12 (11.8) 6
 Chachkhiani et al24 Retrospective US 250 113 (45.2) 60 (mean) Inpatient (100) 39 (15.6) N/R 7
 Chhiba et al25 Retrospective US 1526 718 (47.1) N/R Inpatient (55.9)
Outpatient (44.1)		 220 (14.4) 8 (11.1) 7
 Cummings et al26 Prospective US 257 171 (66.5) 62 (median) Inpatient (100) 21 (8.2) 21 (8.2) 7
 Enzmann et al27 Retrospective US 150 85 (56.7) 56 (median) N/R 27 (18.0) N/R 5
 Fox et al28 Retrospective US 355 181 (51.0) 66.2 (mean) Inpatient (100) 27 (7.6) N/R 7
 Garg et al29 Retrospective US 178 N/R N/R Inpatient (100) 27 (17.0)b N/R 6
 Garibaldi et al30 Retrospective US 832 443 (51.7) 63 (median) Inpatient (100) 79 (9.5) 24 (7.9) 9
 Gavin et al31 Retrospective US 140 72 (51.4) 60 (mean) Inpatient (100) 15 (10.7) 1 (5.6) 8
 Gayam et al32 Retrospective US 408 231 (56.6) 67 (median) Inpatient (100) 54 (13.2) 16 (12.1) 7
 Gottlieb et al33 Retrospective US 8673 4045 (46.6) 41 (median) Inpatient (17.1)
Outpatient (82.9)		 736 (8.5) N/R 7
 Goyal et al34 Retrospective US 1687 1004 (59.5) 66.5 (median) Inpatient (100) 159 (9.4) N/R 7
 Gupta et al35 Retrospective US 2215 1436 (64.8) 60.5 (mean) Inpatient (100) 258 (11.6) 70 (8.9) 8
 Haberman et al36 Prospective US 103 29 (28.2) 52.7 (mean) Inpatient (26.2)
Outpatient (73.8)		 15 (14.6) N/R 6
 Hernandez-Galdamez et al10 Cross-sectional Mexico 211003 115441 (54.7) 45.7 (mean) Inpatient (31.0)
Outpatient (69.0)		 5854 (2.8) 533 (2.1) 7
 Jehi et al37 Retrospective US 2852 1372 (48.1) N/R Inpatient (20.4)
Outpatient (79.6)		 389 (13.6) N/R 6
1684 738 (43.8) N/R Inpatient (22.3)
Outpatient (77.7)		 262 (15.6) N/R
 Keller et al38 Retrospective US 1806 965 (53.4) 62.2 (mean) Inpatient (100) 344 (19.0) N/R 9
 Kim et al39 Ambispective US 867 473 (54.6) 56.9 (mean) N/R 91 (10.5) 10 (8.3) 9
 Ko et al40 Retrospective US 5416 2847 (52.6) N/R N/R 702 (13.0) N/R 8
 Krishnan et al41 Retrospective US 152 95 (62.5) 66 (mean) Inpatient (100) 25 (16.4) 16 (17.4) 6
 Lara et al42 Retrospective US 121 N/R 64 (median) Inpatient (54.5)
Outpatient (45.5)		 10 (8.3) 3 (15.0) 6
 Latz et al6 Retrospective US 1289 417 (32.4) N/R Inpatient (37.5)
Outpatient (62.5)		 347 (26.9) N/R 7
 Lovinsky-Desir et al43 Retrospective US 1298 762 (58.7) N/R Inpatient (100) 163 (12.6) 9 (8.2) 8
 Maatman et al44 Retrospective US 109 62 (56.9) 61 (mean) Inpatient (100) 16 (14.7) 16 (14.7) 7
 Magagnoli et al45 Retrospective US 807 772 (95.7) N/R Inpatient (100) 40 (5.0) N/R 7
 Magleby et al46 Retrospective US 678 414 (61.1) N/R Inpatient (100) 62 (9.1) N/R 7
 McCarthy et al47 Retrospective US 247 143 (57.9) 61 (median) Inpatient (100) 29 (11.7) 11 (9.8) 7
 Mikami et al48 Retrospective US 6493 3538 (54.5) 59 (median) Inpatient (55.1)
Outpatient (42.9)		 271 (4.2) 31 (3.8) 6
 Moll et al49 Retrospective US 210 101 (48.1) 62.2 (mean) Inpatient (100) 35 (16.7) 15 (14.7) 6
 Mughal et al50 Retrospective US 129 81 (62.8) 63 (median) Inpatient (100) 3 (2.3) 2 (6.7) 6
 Mukherjee et al51 Retrospective US 137 99 (72.3) 59 (mean) Inpatient (100) 11 (8.0) 11 (8.0) 8
 Nakeshbandi et al52 Retrospective US 504 263 (52.2) 68 (median) Inpatient (100) 41 (8.1) N/R 8
 Ng et al53 Retrospective US 10482 6239 (59.5) N/R Inpatient (100) 859 (8.2) N/R 9
 Ortizz-Brizuela et al54 Prospective Mexico 309 183 (59.2) 43 (median) Inpatient (45.3)
Outpatient (54.7)		 9 (2.9) 0 (0.0) 9
 Ramachandran et al55 Retrospective US 145 79 (54.5) N/R Inpatient (100) 23 (15.9) N/R 8
 Richardson et al56 Retrospective US 5700 3437 (60.3) 63 (median) Inpatient (100) 479 (9.0) N/R 8
 Robilotti et al57 Retrospective US 423 212 (50.1) N/R Inpatient (42.6)
Outpatient (57.4)		 43 (10.2) N/R 6
 Santos et al11 Retrospective Brazil 21408 12667 (59.2) N/R Inpatient (100) 488 (5.7)b 488 (5.7)b 7
 Shady et al58 Ambispective US 371 249 (67.1) 57 (median) Inpatient (100) 42 (11.4)b N/R 6
 Shah et al59 Retrospective US 522 218 (41.8) 63 (median) Inpatient (100) 68 (13.0) 11 (12.0) 6
 Silver et al60 Retrospective US 249 110 (44.2) 59.6 (mean) Inpatient (100) 49 (20.0) N/R 8
 Singer et al61 Retrospective US 1651 892 (54.0) 50 (mean) Inpatient (45.0)
Outpatient (55.0)		 106 (6.4) N/R 6
 Sinha et al62 Retrospective US 255 161 (63.1) 59 (median) Inpatient (100) 29 (11.4) N/R 8
 Skipper et al63 RCT US and Canada 212 89 (42.0) 41 (median) Outpatient (100) 28 (13.2) N/R 9
211 96 (45.5) 39 (median) Outpatient (100) 20 (9.5) N/R
 Smith et al64 Retrospective US 184 98 (53.3) 64.4 (mean) Inpatient (100) 18 (9.8) N/R 6
 Somers et al65 Retrospective US 154 102 (66.2) 58 (mean) Inpatient (100) 31 (20.1) 31 (20.1) 9
 Souza et al66 Cross-sectional Brazil 197 92 (46.7) N/R N/R 1 (0.5) 1 (0.5) 5
 Suleyman et al67 Retrospective US 463 204 (44.1) 57.5 (mean) Inpatient (76.7)
Outpatient (23.3)		 73 (15.8) 19 (13.5) 8
 Tartof et al68 Retrospective US 6916 3111 (45.0) 49 (median) N/R 1273 (18.4) 44 (21.4) 8
 Tenforde et al69 Cross-sectional US 350 165 (47.1) 43 (median) Inpatient (22.6)
Outpatient (77.4)		 55 (15.7) N/R 7
 Twigg et al70 Retrospective US 242 141 (58.3) 59.6 (mean) Inpatient (100) 34 (14.0) 34 (14.0) 7
 Vaughn et al71 Retrospective US 1705 885 (51.9) 64.7 (median) Inpatient (100) 215 (12.6) N/R 7
 Yao et al72 Retrospective US 242 138 (57.0) N/R Inpatient (100) 28 (11.6) N/R 7
 Yehia et al7 Retrospective US 11210 5583 (49.8) 61 (median) Inpatient (100) 628 (5.6) N/R 8
 Zhao et al73 Retrospective US 641 384 (59.9) 60 (median) Inpatient (100) 41 (6.9)b 16 (8.2) 8
 Zuniga-Moya et al74 Retrospective Honduras 877 538 (61.3) N/R Inpatient (25.1)
Outpatient (74.9)		 31 (3.5) 3 (7.9) 10
Asia
 Almazeedi et al9 Retrospective Kuwait 1096 888 (81.0) 41 (median) Inpatient (100) 43 (3.9) 4 (21.1) 9
 Alsofayan et al75 Retrospective Saudi Arabia 1519 825 (54.3) N/R N/R 54 (4.9)b N/R 5
 Asghar et al76 Retrospective Pakistan 100 69 (69.0) 52.6 (mean) Inpatient (100) 2 (2.0) N/R 6
 Gao et al77 Retrospective China 2877 1470 (51.1) N/R Inpatient (100) 22 (0.8) N/R 10
 Huang et al78 Retrospective China 336 182 (54.2) 43 (median) Inpatient (100) 5 (1.5) N/R 7
 Li et al79 Ambispective China 548 279 (50.9) 60 (median) Inpatient (100) 5 (0.9) 3 (1.1) 8
 Lian et al80 Retrospective China 232 109 (47.0) N/R Inpatient (100) 4 (1.7) 3 (3.3) 6
 Liu et al81 Retrospective China 104 63 (60.6) 42 (medina) Inpatient (100) 12 (11.5) 6 (20.0) 7
 Mao et al82 Retrospective China 188 94 (50.0) 46 (mean) Inpatient (100) 2 (1.1) N/R 9
 Ozger et al83 Retrospective Turkey 175 74 (42.3) N/R Inpatient (100) 9 (5.1) N/R 5
 Pan et al84 Retrospective China 996 465 (46.7) N/R Inpatient (100) 12 (1.2) N/R 7
 Satici et al85 Retrospective Turkey 681 347 (51.0) 56.9 (mean) Inpatient (100) 43 (6.3) 1 (1.8) 7
 Song et al86 Retrospective China 961 500 (52.0) 63 (median) Inpatient (100) 22 (2.3) 1 (0.4) 7
 Sy et al87 Retrospective Philippines 530 373 (70.4) 48.9 (mean) N/R 21 (4.0) N/R 8
 Tezcan et al88 Retrospective Turkey 408 188 (46.1) 54.3 (mean) Inpatient (100) 32 (7.8) N/R 5
 Trabulus et al89 Retrospective Turkey 336 192 (57.1) 55 (mean) Inpatient (100) 20 (6.0) 1 (2.3) 7
 Tsou et al90 Retrospective Taiwan 100 44 (44.0) 44 (median) Inpatient (100) 3 (3.0) N/R 5
 Wang et al91 Retrospective China 123 60 (48.8) 68 (median) Inpatient (100) 1 (0.8) 0 (0.0) 6
 Yang et al92 Retrospective Korea 7340 2970 (40.5) 47.1 (mean) Inpatient (100) 725 (9.9) N/R 8
 Yu et al93 Retrospective China 142 81 (57.0) 61.9 (mean) Inpatient (100) 1 (0.7) N/R 8
 Zhang et al4 Retrospective China 289 154 (53.3) 57 (median) Inpatient (100) 1 (0.3) 1 (0.8) 8
 Zhou et al94 Retrospective China 110 60 (54.5) 57.7 (mean) Outpatient (100) 1 (0.9) N/R 7
Europe
 Alkundi et al95 Retrospective UK 232 145 (62.5) 70.5 (mean) Inpatient (100) 6 (2.6) 0 (0.0) 6
 Avdeev et al96 Retrospective Russia 1307 N/R N/R Inpatient (100) 23 (1.8) 23 (1.8) 3
 Azoulay et al97 Retrospective France 379 292 (77.0) 66 (median) Inpatient (100) 23 (6.1)b 23 (6.1)b 7
 Barillari et al98 Cross-sectional Italy 294 147 (50.0) 42.1 (mean) Inpatient (16.3)
Outpatient (83.7)		 18 (6.1) N/R 4
 Barroso et al99 Retrospective Spain 189 N/R N/R Inpatient (100) 11 (5.8) N/R 6
 Berenguer et al100 Retrospective Spain 4035 2433 (61.0) 70 (median) Inpatient (100) 299 (7.5)b 69 (6.2)b 10
 Beurnier et al101 Prospective France 768 N/R N/R Inpatient (100) 37 (4.8) N/R 5
 Cellina et al102 Retrospective Italy 246 170 (69.1) 63 (mean) Inpatient (100) 10 (4.1) N/R 8
 Docherty et al103 Prospective UK 20133 12068 (59.9) 72.9 (median) Inpatient (100) 2540 (14.5)b N/R 9
 Fang et al104 Retrospective UK 100 60 (60.0) N/R Inpatient (100) 11 (11.0) N/R 9
 Ferrando et al105 Prospective Spain and Andorra 742 504 (68.1)b 64 (median) Inpatient (100) 19 (2.6) 19 (2.6) 10
 Fond et al106 Retrospective France 1092 593 (54.3) 62.5 (median) Inpatient (100) 71 (6.5) N/R 8
 Garcia-Pachon et al107 Retrospective Spain 376 192 (51.1) 54 (median) Inpatient (42.0)
Outpatient (58.0)		 10 (2.7) N/R 4
 Grandbastien et al108 Retrospective France 106 66 (62.3) 63.5 (median) Inpatient (100) 23 (21.7) N/R 7
 Helms et al109 Prospective France 140 100 (71.4) 62 (median) Inpatient (100) 5 (3.6) 5 (3.6) 10
 Ierardi et al110 Retrospective Italy 234 70 (30.0) 61.6 (mean) Inpatient (100) 10 (4.3) N/R 5
 Joseph et al111 Retrospective France 100 70 (70.0) 59 (median) Inpatient (100) 8 (8.0) N/R 7
 Lechien et al112 Retrospective Europec 702 206 (29.3) 40.3 (median) N/R 42 (6.0) N/R 6
 Lendorf et al113 Retrospective Denmark 111 67 (60.4) 68 (median) Inpatient (100) 12 (10.8) 2 (10.0) 8
 Lenti et al114 Retrospective Italy 100 79 (79.0) 70 (median) Inpatient (100) 6 (6.0) N/R 7
 Lombardi et al115 Retrospective Italy 1043 704 (67.5) N/R Inpatient (100) 20 (1.9) N/R 5
 Lund et al116 Retrospective Denmark 9236 3892 (42.1) 50 (median) N/R 629 (6.8) N/R 8
 Maguire et al117 Retrospective UK 224 124 (55.4) N/R Inpatient (100) 46 (20.5) 4 (7.7) 8
 Martinez-Del Rio et al118 Retrospective Spain 921 500 (54.3) 78 (mean) Inpatient (100) 39 (4.2) 9 (3.6) 8
 Perez-Guzman et al119 Retrospective UK 614 382 (62.2) 69 (median) Inpatient (100) 56 (9.1) N/R 7
 Poblador-Plou et al120 Retrospective Spain 771 407 (52.8) 84.2 (mean) N/R 25 (3.2) 25 (3.2) 6
 Sapey et al121 Retrospective UK 2217 1290 (58.2) 73 (median) Inpatient (100) 439 (19.8) 143 (18.6) 8
 Siso-Almirall et al8 Retrospective Spain 322 161 (50.0) 56.7 (mean) Inpatient (49.1)
Outpatient (50.9)		 13 (4.0) 2 (3.6) 7
Middle East
 Jalili et al122 Retrospective Iran 28981 16361 (56.5) 57.3 (mean) Inpatient (100) 573 (2.0) 141 (2.5) 7
Othersc
COVIDSurg Collaborative123 Retrospective Countries 1128 605 (53.6) N/R Inpatient (100) 78 (7.0)b 21 (7.8) 9
Mato et al124 Retrospective Countries 198 125 (63.1) 70.5 (median) Inpatient (89.9)
Outpatient (10.1)		 12 (6.1)b 7 (10.8) 7
Olender et al125 RCT Countries 298 182 (61.1) N/R Inpatient (100) 42 (14.1) N/R 8
Retrospective Countries 816 490 (60.0) N/R Inpatient (100) 90 (11.0) N/R
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Abbreviations: N/R, not (clearly) reported; RCT, randomized controlled trial; UK, United Kingdom; US, United States.

a

The prevalence of asthma in patients with coronavirus disease 2019 with poor outcomes.

b

Data missing for patients.

c

Patients were collected from multiple countries of different regions.

The Pooled Prevalence of Asthma in Patients With COVID-19

The estimated prevalence of asthma in patients with COVID-19 ranged from 0.3% to 26.9%. By combining 119 studies (a total of 403,392 patients) reporting the data of patients with co-infection of asthma and COVID-19, the pooled prevalence of asthma in patients with COVID-19 was 8.3% (95% CI, 7.6-9.0; random-effects model) and heterogeneity was obvious (χ2 = 9311.76; P < .01; I 2 = 98.7%) (Fig 2 ). Therefore, we conducted subgroup and meta-regression analyses to explore the possible factors that caused heterogeneity according to sample size, study design, region, settings, and quality score (Table 2 and eFigs 1-5). The pooled prevalence of asthma among patients with COVID-19 was 3.3% (95% CI, 1.9-4.6; χ2 = 712.56, P < .01; I 2 = 97.1%) in Asia, 11.1% (95% CI, 9.9-12.3; χ2 = 5466.42, P < .01; I 2 = 98.8%) in the Americas, 7.0% (95% CI, 5.0-9.0; χ2 = 1608.20, P < .01; I 2 = 98.3%) in Europe, and 9.4% (95% CI, 6.2-12.5; χ2 = 18.82, P < .01; I 2 = 84.1%) in other countries. Only 1 study was completed in the Middle East, and the prevalence of asthma in patients with COVID-19 was 2.0% (95% CI, 1.8-2.1). The results of univariate meta-regression revealed that region (P < .001) might be a factor caused by heterogeneity, whereas no significant differences were observed in sample size (P = .131), settings (P = .337), study design (P = .936), or quality score (P = .610).

Figure 2.

Figure 2

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Forest plot of the pooled prevalence of asthma in patients with COVID-19 on a basis of 119 studies. CI, confidence interval; COVID-19, coronavirus disease 2019.

Table 2.

Subgroup Analysis and Meta-Regression

Variables No. of studies Meta-regression
 Subgroup analysis
 Heterogeneity
Tau2 t value P value Pooled ES (95% CI) P value I2 (%) χ2 P value
Sample size (continuous) 0.0018 −1.52 .131
 ≥500 53 0.081 (0.072-0.091) <.01 99.4 8339.83 <.01
 <500 66 0.088 (0.075-0.100) <.01 93.2 962.03 <.01
Settings (continuous) 0.0018 −0.96 .337
 Inpatient 85 0.082 (0.073-0.092) <.01 98.5 5633.00 <.01
 Outpatient 3 0.077 (0.000-0.157) <.01 94.2 34.41 <.01
 Others 31 0.090 (0.073-0.107) <.01 99.1 3475.58 <.01
Region 0.0015 — <.001
 Asia 22 — 0.45 .656 0.033 (0.019-0.046) <.01 97.1 712.56 <.01
 Americas 64 — 2.22 .029 0.111 (0.099-0.123) <.01 98.8 5466.42 <.01
 Europe 28 — 1.30 .197 0.070 (0.050-0.090) <.01 98.3 1608.20 <.01
 Middle East 1 — — — 0.020 (0.018-0.021) <.01 — — —
 Others 4 — 1.52 .132 0.094 (0.062-0.125) <.01 84.1 18.82 <.01
Study design 0.0019 −0.08 .936
 Prospective/RCT 10 0.086 (0.042-0.130) <.01 98.4 549.08 <.01
 Others 109 0.082 (0.076-0.089) <.01 98.6 7491.52 <.01
Quality score 0.0019 −0.51 .610
 High 46 0.088 (0.073-0.103) <.01 98.9 4017.89 <.01
 Moderate/low 73 0.079 (0.072-0.086) <.01 98.1 3855.35 <.01
Open in a new tab

Abbreviations: CI, confidence interval; ES, effect sizes; RCT, randomized controlled trial.

Italic value indicates statistical significance.

The Association Between Asthma and the Poor Outcomes of Patients With COVID-19

Poor outcomes included severe or critical illness, ICU admission, requirement of MV, or death. A total of 40 studies comprising 274,395 patients reported the data on asthma in patients with COVID-19 with poor outcomes and patients with COVID-19 without poor outcomes (eTable 5). The pooled results revealed that asthma was not significantly associated with the reduced risk of poor outcomes in COVID-19 (ES, 0.91; 95% CI, 0.78-1.06; χ2 = 90.97, P < .001; I 2 = 57.1%; random-effects model) based on unadjusted effect estimates (Fig 3 ).

Figure 3.

Figure 3

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Forest plot of unadjusted ES for the association between asthma and the poor outcomes of patients with COVID-19 on a basis of 40 studies. CI, confidence interval; COVID-19, coronavirus disease 2019; ES, effect size; ID, identification.

The Association Between Asthma and the Risk of Mortality in Patients With COVID-19

A meta-analysis of 24 studies reporting the unadjusted ES (eTable 5) and a meta-analysis of 12 studies reporting the adjusted ES (eTable 6) were conducted to evaluate the association between asthma and the risk of mortality in patients with COVID-19, respectively. The pooled results of unadjusted effect estimates revealed that asthma was not significantly associated with the reduced risk of mortality in patients with COVID-19 (ES, 0.88; 95% CI, 0.73-1.05; χ2 = 75.65, P < .001; I 2 = 69.6%; random-effects model) (Fig 4A). However, the pooled results of adjusted effect estimates indicated that asthma was significantly associated with the reduced risk of mortality in patients with COVID-19 (ES, 0.80; 95% CI, 0.74-0.86; χ2 = 16.31; P = .13; I 2 = 32.6%; fixed-effects model) (Fig 4B).

Figure 4.

Figure 4

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Forest plots of the pooled ES for the relationship between asthma and the risk of mortality in patients with COVID-19. A, The unadjusted ES on a basis of 24 studies. B, The adjusted ES on a basis of 12 studies. CI, confidence interval; COVID-19, coronavirus disease 2019; ES, effect size; ID, identification.

Publication Bias

Significant publication bias was found by Begg test (P = .038) and Egger test (P < .001) within our analysis (eFig 6).

Discussion

Our quantitative meta-analysis suggested that the pooled prevalence of asthma in patients with COVID-19 worldwide was 8.3%, which was contained in a range (4.3%-8.6%) of the global prevalence rates of asthma.126 The pooled prevalence of asthma in patients with COVID-19 worldwide (8.3%) was more similar to the global prevalence of wheezing (8.6%) using the least stringent definition of asthma.126 Considering the obvious heterogeneity of our analysis, we subsequently performed subgroup analysis and meta-regression according to sample size, study design, region, settings, and quality score. The univariate meta-regression implied that region (P < .001) might be a potential source of heterogeneity. According to the results of subgroup analysis, the pooled prevalence of asthma among patients with COVID-19 was 3.3%, 11.1%, 7.0%, 2.0%, and 9.4% in Asia, the Americas, Europe, the Middle East, and other countries, respectively, which highlighted the demand for locally tailored interventions and initiatives. Interestingly, Gibson et al127 reported that the prevalence of asthma in the European population was 4% to 7%. Huang et al5 identified that the overall prevalence of asthma in 57,779 participants of China was 4.2%. Furthermore, the US Centers for Disease Control and Prevention pointed out that adult self-reported asthma prevalence was 9.2%.128 All of these evidences indicate that the prevalence of asthma among patients with COVID-19 in different regions and countries seemed to be similar to that of asthma in the general population.

To explore the relationship between asthma and patients with COVID-19 with poor outcomes (including severe or critical illness, ICU admission, requirement of MV, or death), we calculated the pooled unadjusted ES based on 40 studies comprising 274,395 patients. The pooled unadjusted ES was less than 1, which revealed that asthma might be associated with the reduced risk of poor outcomes in patients with COVID-19, although the corresponding 95% CI crossed 1 (ES, 0.91; 95% CI, 0.78-1.06). We hypothesized that the different poor outcomes reported in the included articles and the known factors (such as sex, age, and other comorbidities) influencing the risk of poor outcomes in patients with COVID-19 might contribute to the results.2 , 129 , 130 Therefore, we specifically explored the association between asthma and the risk of mortality in patients with COVID-19 based on the limited data reported by the included articles. Similarly, the pooled unadjusted ES was less than 1, which also revealed that asthma might be significantly associated with the reduced risk of mortality in patients with COVID-19 (ES, 0.88; 95% CI, 0.73-1.05). Considering that this result might be because of the influence of various factors on the risk of mortality in patients with COVID-19, we subsequently calculated the pooled ES on the basis of adjusted effect estimates. The corresponding results suggested that asthma was significantly associated with the reduced risk of mortality in patients with COVID-19 (ES, 0.80; 95% CI, 0.74-0.86). In summary, asthma might be an independent protective factor for death of patients with COVID-19. There are some complicated and multifactorial reasons. One reason is immune response triggered by asthma. Li et al79 speculated that TH2 immune response in patients with asthma may counter the inflammation process induced by SARS-CoV-2 infection. Another is the use of inhaled corticosteroids or bronchodilators, which can suppress viral replication and decrease the impact of the inflammatory storm.131 , 132

Several limitations inevitably exist in our meta-analysis. First, most studies we included were retrospective; therefore, the interpretation of our results should be taken with caution because of their inherent limitations. Further well-designed prospective studies with large sample sizes are required to verify our findings. Second, the substantial heterogeneity across the studies should not be ignored, which was why we conducted subgroup analysis and meta-regression, and thus identified the region as a potential source of heterogeneity. Third, in the included studies, the definitions of asthma were not uniform and relatively diverse, including patients' self-report, which might lead to a certain bias. Fourth, we did not carry out statistics and analysis on the use of corticosteroids because of insufficient data provided in the original publications. Fifth, different poor outcomes including severe illness, critical illness, ICU admission, MV, and death were reported in the selected studies; we only specifically explored the association between asthma and the risk of mortality in patients with COVID-19 based on the limited data reported by the included articles. Further subgroup analysis on the relationship between asthma and certain outcomes of patients with COVID-19 should be performed when sufficient data are available. Finally, obvious publication bias was observed in our study, which might be because of the unrecognized duplicate population.

The pooled prevalence of asthma in patients with COVID-19 was similar to that in the general population. Asthma was not associated with the reduced risk of poor outcomes in patients with COVID-19. Interestingly, asthma might be an independent protective factor for the death of patients with COVID-19, which suggests that we should pay high attention to patients with co-infection of COVID-19 and asthma and take locally tailored interventions and treatment. Further well-designed studies with large sample sizes are required to verify our findings.

Acknowledgments

We thank Xuan Liang, Peihua Zhang, and Jian Wu (all are from the Department of Epidemiology, College of Public Health, Zhengzhou University) for their kind help in searching articles and collecting data and valuable suggestions for data analysis.

Footnotes

Disclosures: The authors have no conflicts of interest to report.

Funding: This work was supported by grants from the National Natural Science Foundation of China (grant number 81973105), Key Scientific Research Project of Henan Institution of Higher Education (grant number 21A330008), the National Science and Technology Major Projects of China (grant number 2018ZX10301407), and Joint Construction Project of Henan Medical Science and Technology Research Plan (grant number LHGJ20190679). The funders have no role in the data collection, data analysis, preparation of manuscript, and decision to submit the article for publication.

Supplementary data related to this article can be found at https://doi.org/10.1016/j.anai.2021.02.013.

Supplementary Data

Supplementary Material
mmc1.docx (64.2MB, docx)

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