Results
Age and gender distribution for all included hospitalized COVID-19
cohorts stratified for the presence of asthma are shown in Table 1. The
participating German centers included asthmatics who were significantly
younger than the non-asthmatic group, while Stanford asthma group had
significantly more male patients (Table 1, p-value = 0.0343). The vast
majority (> 90%) of patients included in the German and
Russian cohorts were Caucasian, albeit we could not collect precise data
on ethnicity for these cohorts. The US cohort comprised of 246 (50.7%)
Hispanics and 18 (3.7%) Afro-Americans. Asthma was significantly
underrepresented (vs. prevalence among adults in local community) in
hospitalized COVID-19 cohorts of all included countries in our study
with the exception of the Stanford cohort. The latter encompassed
asthmatics with a prevalence of 18.35% as compared to a 10.56%
prevalence of asthma in the broader California area (Figure 1). We
assessed the prevalence of asthma among intensive care unit (ICU)
patients and found that it did not significantly differ from the
prevalence among patients in normal care for any of the participating
centers (Supplementary Figure 1).
We next examined the presence of comorbidities among hospitalized
COVID-19 patients across our centers and found that the Stanford cohort
exhibits an over-representation of asthma & COPD patients versus
non-asthma & COPD patients (Figure 2a, p-value = 0.0046). We observed a
similar trend for other comorbidities (concurrent or past) such as
cancer and chronic renal disease for patients hospitalized in Stanford,
however these differences between asthma and non-asthma hospitalized
COVID-19 patients did not reach statistical significance (Figure 2a).
Furthermore, the patients in Stanford had more (total) comorbidities
compared to Germany and Moscow (Figure 2a). Importantly, the asthma
group in Stanford had more additional preconditions than the non-asthma
group with over 85% of asthmatics having an additional comorbidity
(Figure 2b, p-value = 0.0346). This was not the case with the German and
Moscow centers, where asthmatics and non-asthmatics showed a similar
pattern in terms of frequency of additional comorbidities (Figure 2b,
Germany: p=0.216, Moscow: p=0.8256). Furthermore, a second ‘wave’ of
comorbidity frequency was recorded with a second peak after 3
comorbidities on top of asthma and COVID-19 (Figure 2b). The
overrepresentation of asthmatics among hospitalized COVID-19 patients in
Stanford can be explained by confounders, like age, sex, and
comorbidities. To mitigate the effect of these confounders we performed
logistic regression to predict asthma using the center (“moscow” or
“stanford”, where microdata was available), sex and the 11
comorbities. This resulted in a decrease in the Odds to be asthmatic
given that the center was “stanford”, the sex was “female” and no
comorbidity was present in all four age groups (Figure 3). The 95%
confidence intervals of so-adjusted Odds reach the population level and
lower Odds than the population level are not excluded.
We next analyzed basic lab values of all included patients across study
centers and observed a peripheral blood eosinopenia at admission in all
centers except Stanford, followed by a recovery close to discharge
(Figure 4, Supplementary Figure 2). The Stanford group showed higher
levels at admission and overlapping values until discharge i.e., no
significant change throughout their hospitalization. Platelet counts
showed a somewhat similar pattern; however, both asthma and non-asthma
patients at Stanford had relatively stable counts throughout. Values of
all other studied laboratory parameters did not significantly deviate
between centers of our network (Supplementary Figure 2).