Asthma as a comorbidity in COVID‐19 pediatric ICU admissions in a large metropolitan children's hospital

Abstract

Rationale

Children contribute to 5% of coronavirus disease of 2019 (COVID‐19)‐related hospitalizations in the United States. There is mounting evidence suggesting childhood asthma is a risk factor for severe disease. We hypothesized that asthma is associated with longer length of stay (LOS) and need for respiratory support among children admitted to pediatric intensive care unit (PICU) with COVID‐19.

Methods

We reviewed 150 charts of children and young adults with a positive severe acute respiratory syndrome coronavirus 2polymerase chain reaction test admitted to the PICU at Children's National Hospital, Washington, DC between 2020 and 2021. We recorded demographics, anthropometrics, past medical history, clinical course, laboratory findings, imaging, medication usage, respiratory support, and outcomes. Functional Status Scale (FSS), which measures an Intensive Care Unitpatient's physical function, was used to characterize children with multiple comorbidities; FSS and obesity were included as covariates in multivariate analysis. Statistical analysis was performed using SPSS v25.0.

Results

Sixty‐Eight patients ages 0–21 years met inclusion criteria. Median age was 14.9 years, 55.9% were female, median Body Mass Index percentile was 62, and 42.6% were African American. Compared with those without asthma, patients with asthma averaged longer LOS (20.7 vs. 10.2 days, p = 0.02), with longer PICU stay (15.9 vs. 7.6 days, p = 0.033) and prolonged maximum respiratory support (8.3 vs. 3.3 days, p = 0.016). Adjusted for obesity and poor physical function (FSS > 6), asthma remained a significant predictor of hospital LOS, PICU LOS, and days on maximum respiratory support.

Conclusion

Asthma can cause severe disease with prolonged need for maximum respiratory support among children with COVID‐19.

1. BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), the virus that causes coronavirus disease of 2019 (COVID‐19), has affected 91 million individuals in the United States (US) and led to over 1 million deaths as of July 2022. ¹ Nineteen percent of COVID‐19 cases have been in children less than 18 years of age. As of March 3, 2022, children made up 1.3%–4.7% of all cumulative COVID‐19‐related hospitalizations in the United States, ² and up to 30% of pediatric hospitalizations were in the pediatric intensive care unit (PICU). ³

Studies evaluating risk factors for poor outcomes in adults with COVID‐19 demonstrated that specific chronic illnesses, including obesity, hypertension, and diabetes were associated with longer hospital length of stay (LOS) and longer duration of respiratory support including mechanical ventilation. ⁴ , ⁵ In children, comorbidities such as obesity, obstructive sleep apnea, chromosomal abnormalities, neurologic diseases, and metabolic conditions have been linked to higher severity of illness  ⁶ , ⁷ , ⁸ , ⁹ , ¹⁰ , ¹¹ and an association has been observed between a total number of comorbidities in an individual patient and disease severity, including the need for critical care treatment. ⁷ , ⁸ , ⁹ , ¹⁰

There is mixed evidence on the contribution of asthma to the severity of COVID‐19 presentation. Studies done in the early phase of the pandemic suggested that asthma may not be a risk factor for poor outcomes in people hospitalized with COVID‐19. ¹² , ¹³ In contrast, more recent data has suggested otherwise. ¹⁰ , ¹⁴  British children ages 5–17 years with at least one hospitalization for asthma in the previous 2 years had a six‐fold higher risk for COVID‐19‐related hospitalization than children without asthma. ¹⁴ In another cohort less than 21 years old from Colorado, US, Graff et al. ¹⁰ found asthma to be a risk factor for hospitalization and need for respiratory support. Asthma prevalence was also high among COVID‐19 hospitalizations to the PICU. ³ , ⁴ , ⁷ , ¹⁵ , ¹⁶ Despite these studies, there is limited data characterizing disease presentation and management needs among children with asthma hospitalized with COVID‐19. ³ , ⁴ , ⁷ , ¹⁵ , ¹⁶

To address these gaps in knowledge, we report on clinical presentation of COVID‐19 among children with and without asthma hospitalized in the PICU. We hypothesized that the presence of asthma in children hospitalized in the Intensive Care Unit (ICU) with COVID‐19 is associated with a higher disease burden, including greater need for respiratory support, including mechanical ventilation, and longer LOS.

2. METHODS

2.1. Study cohort

We conducted a retrospective chart review of patients admitted to the PICU between March 2020 and May 2021 at Children's National Hospital in Washington, DC, which is a 323‐bed tertiary medical center serving District of Columbia, parts of Virginia, and Maryland. This study was approved by the Institutional Review Board at Children's National Hospital (IRB Protocol 00015729).

Data were collected from the electronic medical record (EMR) (Cerner Millennium; Cerner Crop.) on all patients with a confirmed positive SARS‐CoV‐2 polymerase chain reaction (PCR) test from nasal, nasopharyngeal, or endotracheal aspirate during their hospital stay in the PICU. Among the 150 COVID‐19‐positive patients admitted to the PICU in this time duration, 73 were hospitalized for a primary respiratory problem (i.e., ICD‐10 codes J18.9, J21.9, J45.9, and J98.00). Of these 73 patients, five were young adults (defined as >22 years of age) and were further excluded, limiting our study cohort to a total of 68 patients.

2.2. Patient data variables

Patient demographic data included age, sex, race, and ethnicity. Anthropometric data included Body Mass Index (BMI), Weight versus Length (WvL), and Weight for Age. Co‐morbid and chronic conditions recorded included asthma, bronchopulmonary dysplasia and/or chronic lung disease of infancy (BPD/CLD), history of home ventilation including home mechanical ventilation or Bilevel Positive Airway Pressure (BiPAP), and a history of G‐tube placement. Using the validated Functional Status Scale (FSS), ¹⁷ , ¹⁸ we characterized children with multiple other comorbidities admitted to the PICU. FSS is a validated score for measuring patient's physical function in the PICU. ¹⁷ All patients classified as having asthma had been previously diagnosed with asthma by their primary care manager or their pulmonologist. Their asthma severity was classified based on their daily inhaled corticosteroid total daily dose in the low, medium, or high dose range as per the National Heart, Lung and Blood Institute's 2020 focused guidelines (Table S4). ¹⁹ Since healthy patients without chronic comorbidities have an FSS score of 6 while those with one or more comorbidities have a score >6, we used a cutoff of 6 as a marker of the absence or presence of chronic comorbidities. ¹⁷ , ¹⁸ For each patient's clinical course, FSS was calculated at admission and at discharge by two different physicians based on previous documentation from each patient's EMR. When discrepancies occurred, our study team of five physicians decided on the final value.

For lab investigations, we abstracted White Blood Cell Count (WBC), Absolute Neutrophil Count, C‐Reactive Protein (CRP), Ferritin, d‐Dimer, Brain Natriuretic Protein, Troponin level, and Erythrocyte Sedimentation Rate (ESR). We also included culture positivity and identified organisms for blood, respiratory, and urine cultures, as well as results from a PCR‐based multirespiratory viral detection test (Quest Diagnostics [CPT 95512]). For imaging, we abstracted chest x‐ray findings reported by pediatric radiologists including pneumonia or infiltrate, effusion, or evidence of barotrauma. If an echocardiograph was performed, we abstracted details on ejection fraction and fractional shortening.

Medications abstracted from EMR included use of remdesivir, antibiotics, inotropes or vasopressors, systemic corticosteroids, and inhaled therapies, including albuterol or levalbuterol, racemic epinephrine, a helium‐oxygen gas mixture, and inhaled nitrous oxide. Respiratory support included the use of nasal cannula or tracheostomy collar, High Flow Nasal Cannula, Continuous Positive Airway Pressure (CPAP), bilevel positive pressure including BiPAP or CPAP with pressure support. Invasive modes of mechanical ventilation included use of conventional pressure or volume control ventilation, and advanced ventilation defined as Airway Pressure Release Ventilation (APRV) or High Flow Oscillatory Ventilation (HFOV). Patient positioning (prone vs. supine) and the presence of a chest tube were additionally captured.

Primary outcomes included hospital LOS and duration of maximum respiratory support, measured in days. Maximum respiratory support was defined as the highest escalation of respiratory support a patient required such as nasal cannula, noninvasive positive pressure, or mechanical ventilation. Secondary outcomes included mortality, cardiac arrest, hemodialysis or continuous renal replacement therapy, extracorporeal membrane oxygenation (ECMO), need for new placement of tracheostomy, and discharge location (chronic care facility or home).

2.3. Statistical analysis

Statistical analysis was performed using SPSS v25.0. Unless otherwise indicated, qualitative variables are expressed as absolute frequencies and percentages, while quantitative variables are expressed as mean ± standard error. Statistical significance of continuous variables was determined with independent‐sample t‐tests. When appropriate, ordinal regression (i.e., ethnicity) and chi‐square test were performed for categorical data. Multivariate regression was performed for primary outcomes to include variables (obesity, medically complex/co‐morbid conditions) previously reported to be associated with greater COVID‐19 severity. Results with a p value < 0.05 were considered significant.

3. RESULTS

3.1. Clinical characteristics of the study cohort

Sixty‐Eight patients met the inclusion criteria (Table 1). The median age of the cohort was 14.9 years and 55.9% were female. The mean BMI percentile was 84.9 for those 2 years and older and mean WvL was 71.9 for patients less than 2 years old. Forty‐two percent were of African American race. Thirty‐Four percent had a diagnosis of asthma before admission, 38.2% were obese, 20.6% had a diagnosis of BPD or CLD, and 10.3% were on home mechanical ventilation.

Table 1.

Characteristics of the study sample

	Overall (n = 68)	Asthma (n = 23)	No asthma (n = 45)	p Value
Demographics
Age (mean ± SE)	11.7 ± 0.87	13.2± 1.35	10.9 ± 1.11	0.19
Age (median [IQR])	14.9 (3.3–17.6)	14.8 (9.2–17.9)	15.1 (9.2–17.9)	0.26
Gender (% female [n])	55.9 (38)	56.5 (13)	55.6 (25)	0.94
Mean BMI (percentile ± SE [n])	84.9 ± 3.327	89.3 ± 4.705 (21)	82.3 ± 4.489 (36)	0.32
Median BMI (percentile, [IQR])	97.6 (78.1–99.4)	97.1 (89.8–99.4)	98.1 (69.6–99.6)	0.76
WvL (<2 year old) (mean ± SE [n])	71.9 ± 8.05 (10)	96.9 ± 0.575 (2)	65.7 ± 8.726 (8)	0.13
Weight for age (mean ± SE [n])	66.8 ± 4.77 (60)	66.5 ± 9.24 (19)	66.9 ± 5.59 (41)	0.97
Race, % (n)				0.39
Asian	2.9 (2)	0.0 (0)	4.4 (2)
Black or African American	42.6 (29)	52.2 (12)	37.8 (17)
Caucasian	10.3 (7)	13.0 (3)	8.9 (4)
Other	44.1 (30)	34.8 (8)	48.9 (22)
Ethnicity (% [n])				0.31
Hispanic	30.8 (21)	17.4 (4)	37.8 (17)
Not Hispanic	69.2 (47)	82.7 (19)	62.2 (28)
Presentation, past medical history, and outcomes (% [n])
Asthma	33.8 (23)	100 (23)	0.0 (0)	1.0
Hx of BPD/CLD	20.6 (14)	30.4 (7)	15.6 (7)	0.15
Prior pulm visits	35.3 (24)	56.5 (13)	24.2 (11)	0.01
Vent at home (trach)	10.3 (7)	4.3 (1)	13.3 (6)	0.25
G‐tube at baseline	27.9 (19)	39.1(9)	22.2 (10)	0.14
BiPAP at home	10.0 (7)	17.4 (4)	6.7 (3)	0.17
FSS > 6 (abnormal)	38.2 (26)	47.8 (11)	33.3 (15)	0.25
FSS on admission (mean ± SE)	9.2 ± 0.59	10.3 ± 1.15	8.9 ± 0.67	0.09
Chronic care facility (% [n])	10.3 (7)	21.7 (5)	4.4 (2)
Hospital LOS (days [mean ± SE])	13.8 ± 1.9	20.7 ± 4.7	10.2 ± 1.3	0.02
PICU LOS (days [mean ± SE])	10.4 ± 1.6	15.9 ± 4.2	7.6 ± 1.1	0.03
Max respiratory support (days [mean ± SE])	5.0 ± 0.8	8.3 ± 2.2	3.3 ± 0.5	0.02

Abbreviations: BiPAP, Bilevel Positive Airway Pressure; BMI, Body Mass Index; BPD, bronchopulmonary dysplasia; CLD, chronic lung disease of infancy; FSS, Functional Status Scale; IQR, interquartile range; LOS, length of stay; PICU, pediatric intensive care unit; SE, standard error; WvL, Weight versus Length.

The average WBC was 7.2 K/mcL. When performed, the average CRP was 6.7 mg/L and the average ESR was 34.3 mm/h (Table S1). Four patients (5.9%) had a positive blood culture but three grew Staphylococcus epidermidis and were deemed a contaminant. The other patient grew Methicillin‐Sensitive Staphylococcus aureus. Eight patients (11.7%) had positive respiratory cultures with Staphylococcus aureus being the most prevalent organism (n = 4). Seven individuals (10.3%) tested positive on respiratory viral panel and all were human rhinovirus/enterovirus. For patients who received chest x‐rays, 76.5% were found to have infiltrates, 20.6% had effusions, and only one patient was diagnosed with barotrauma (pulmonary interstitial emphysema). Sixteen patients underwent echocardiographic evaluation. Quantified in 12 patients, the average ejection fraction was 53.4% and average fractional shortening was 37.3% (n = 4 patients).

With regard to medication usage and outcomes, 69.1% received systemic corticosteroids, either IV or oral. Seventy‐seven percent received remdesivir, and 76.5% also received antibiotics, 13.2% were given an inotrope or a vasopressor, 72.1% were placed on a bronchodilator such as albuterol or levalbuterol, and 4.4% were placed on inhaled nitric oxide (Table S1).

In terms of respiratory support, 45.6% of our patients received noninvasive ventilatory support with BiPAP and CPAP with pressure support. Conventional ventilation was used in 36.8% of patients, 4.4% were placed on advanced ventilation including APRV or HFOV, 4.4% were placed prone, 2.9% patients required a chest tube, one for empyema and the other for a parapneumonic effusion, and one patient required ECMO (Table S2).

With regard to outcomes (Table S3), 85.3% of patients were discharged home while 13.2% either were transferred back to or were discharged to a chronic care facility; two patients required placement of a new tracheostomy. One patient died secondary to cardiogenic shock.

3.2. Association with diagnosis of asthma

In patients with underlying asthma, age, sex, and BMI did not significantly differ from patients without asthma (Table 1). Total LOS was an average of 20.7 days for patients with asthma compared with 10.2 days (p = 0.02) for patients without asthma (Table 2). Patients with asthma were also more likely to require longer duration of maximum respiratory support (8.3 vs. 3.3 days, p = 0.02), have a longer ICU stay (15.9 vs. 7.6 days, p = 0.03), require a vasopressor (13.2% vs. 8.9%, p = 0.008) and to be discharged to a chronic care facility (30.4% vs. 4.4%, p = 0.003). They were also more likely to have radiological findings consistent with a pneumonia (91.3% vs. 68.9%, p = 0.04). There were no significant differences in BiPAP usage, conventual ventilation usage, or laboratory findings between those with or without asthma.

Table 2.

Multivariate analysis of the association of asthma, obesity, and FSS with length of stay and need for respiratory support

Primary outcomes	History of asthma	Obesity	FSS > 6
	(n = 23), β (95% CI, p value)	(n = 26), β (95% CI, p value)	(n = 23), β (95% CI, p value)
Hospital length of stay (days)	0.33 (0.07–0.59, 0.01)	0.05 (−0.21–0.31, 0.70)	−0.22 (−0.49–0.05, 0.11)
PICU length of stay (days)	0.29 (0.03–0.56, 0.03)	0.12 (−0.15–0.39, 0.39)	−0.18 (−0.46–0.09, 0.19)
Maximum respiratory support (days)	0.32 (0.06–0.58, 0.01)	0.16 (−0.10–0.43, 0.23)	−0.11 (−0.39–0.17, 0.42)

Abbreviations: CI, confidence interval; FSS, Functional Status Scale; PICU, pediatric intensive care unit.

Because of past studies demonstrating multiple comorbidities and obesity as potential confounders, we adjusted for their presence in multivariate analysis. ⁷ , ⁸ , ⁹ , ¹⁰ We found that asthma remained a significant predictor of hospital LOS, PICU LOS, and days on maximum respiratory support, when adjusting for obesity as well as FSS (Table 2). Neither obesity nor FSS was independently associated with these outcomes.

4. DISCUSSION

In our retrospective study, we evaluated the association of existent asthma diagnosis among 68 children ages 21 and younger admitted to our tertiary, inner‐city children's hospital ICU to further characterize its contribution to pediatric disease burden caused by COVID‐19. In comparison to several studies characterizing critical care admissions in children, our total length of hospitalization was longer, and was similar to data published on adults. ⁵ , ²⁰ However, mortality rate, as well as need for ICU interventions such as ECMO use, tracheostomy placement, vasopressor use, and renal replacement therapy, was lower than that among adults. ⁵ , ²⁰

Our study is the first to report in detail the impact of existent asthma diagnosis on clinical course, laboratory, and imaging results, need for respiratory support, and outcomes in pediatric patients with COVID‐19 requiring hospitalization in a PICU. The prevalence of asthma in our study was 33.8%, far higher than the 10% in the general population of children 21 years and younger, but similar to prior critical care studies on pediatric COVID‐19. ⁵ , ¹⁰ , ¹⁶ , ²¹ We also found an association between asthma and hospital LOS as well as days on maximum respiratory support, even when we accounted for the presence of obesity and underlying chronic medical conditions, two comorbidities which have been associated with higher severity of COVID‐19 infection. These findings are novel evidence that supports asthma as an independent risk factor for severe prolonged COVID‐19 disease in children.

Thus far, there is a lack of evidence supporting a clear link between asthma and severe COVID‐19 disease in children. Graff et al. ¹⁰ reported that presence of asthma among children and young adults ages 11–23 years in Colorado increased the risk for admission by two‐fold, and the need for respiratory support by three‐fold, but was not associated with greater need for critical care. In a cohort of 43,465 patients with COVID‐19 aged 18 years or younger, Kompaniyets et al. ⁹ found that asthma was the most common co‐morbidity, present in 10.2% of patients, but was not associated with severe illness in children ages 2–5 years. For unclear reasons, similar details were not reported on the older age groups. Similar findings were reported by Choi et al. ⁴ and Lovinsky‐Desir et al. ²² , where the latter showed that LOS in the 55 patients less than age 21 years (mean age 15 years) admitted to New York Presbyterian Hospital in New York City were not significantly different between those with and without asthma. We speculate that the differences in our findings and those of these prior studies may potentially be driven by differences in the SARS‐CoV‐2 viral strain underlying the COVID‐19 infection. This speculation is supported by the low disease burden among children in the early half of the pandemic as compared with the latter half of the pandemic. Although our study period includes 14 months of the pandemic, 59% of children in our cohort were hospitalized in the latter 7 months compared with 41% in the first 7 months—an increase of almost 50%.

There is stronger evidence for the contribution of asthma to severe or prolonged illness in the adult literature. Sunjaya et al. ²³ and Caminati et al. ²⁴  found that asthma to be a risk factor for severe disease in hospitalized adults, as quantified by need for intubation and ultimate outcome of death. In keeping with these findings, Mahdavinia et al. ²⁵ demonstrated that asthma was associated with a longer duration of intubation (p = 0.01) but not with duration of hospitalization (p = 0.25). In contrast, Chhiba et al. ²⁶ showed that the risk of hospitalization and ICU admission was significantly higher (RR: 1.39 [95% CI: 0.90–2.15]) among those with asthma, even when adjusted for comorbidities such as obesity. Given these observations in adults who have asthma for a longer duration than children, a third of children with asthma in our study also carried a diagnosis of chronic lung disease, suggesting that chronicity of airway disease may be an additional risk factor that may explain the overlap between our findings and those among adults. Since airway inflammation is the best understood mechanism underlying disease chronicity in asthma, the overlap between these observations highlights the need for mechanistic studies to identify immune pathways that may be common between the effects of SARS‐CoV‐2 on pediatric and adult airways.

Obesity has been linked to severe COVID‐19 illness in adults. However, the same association in children has been less conclusive. ⁶ , ¹⁰ , ¹⁶ Reasons for this discrepancy could include the occurrence of other medical comorbidities associated with obesity, and differences in race/ethnicity and socioeconomic or behavioral factors that can coexist with obesity. ⁶ , ¹⁰ , ¹⁶ The prevalence of obesity remains high in the Maryland, Virginia, and District of Columbia regions covered by our health system. Maryland itself is ranked 17th in the United States for obesity in children 10–17 years of age. ²⁷ Obesity has been associated with asthma as well as asthma severity in children ²⁸ due to underlying mechanisms including high leptin levels, innate immune dysfunction, and metabolic dysregulation. ²⁹ Although we found an association between obesity and need for mechanical ventilation, we did not find that obesity independently contributed to longer hospitalizations, longer PICU LOS, or days on maximum respiratory support, suggesting that its association with mechanical ventilation may be due to its association with asthma.

Although the pathobiology of COVID‐19 and its variability based on the underlying strain are still being defined, several pathobiological effects of asthma may explain our findings. Diffuse alveolar damage reported in COVID‐19 patients would be exacerbated by patients with asthma suffering from airflow limitation due to bronchospasm and mucous plugging. ³⁰ Dysfunction of the airway epithelium in asthma patients can also lead to a weakened immune defense mechanism predisposing patients with asthma to more severe respiratory illness. ⁴ Conversely, coexistent atopy has been found to decrease COVID‐19 risk and severity due to downregulation of the angiotensin‐converting enzyme 2 receptor. ³¹ , ³² , ³³ Our findings, in context of these existing data, further support the need to better phenotype childhood asthma to allow for better prediction of the asthma phenotype that may be more susceptible to COVID‐19.

This study is the first to report in detail the effect of the presence of asthma on clinical course, laboratory and imaging results, need for respiratory support, and outcomes in pediatric patients with COVID‐19 requiring hospitalization in a PICU. However, our study has many limitations. Our data was observational and derived from a single, unique, academic, urban medical center with a limited sample size. Our studies date preceded the rise of both the Delta and Omicron variants, so may not accurately reflect disease from these strains. Additionally, although asthma patients represent 33% of the entire population, 72% of our study population were placed on a bronchodilator. As much of the management of COVID‐19 during 2020–2021 remained uncharted, we speculate that albuterol was used even in children without asthma in an attempt to facilitate recovery. Our patient population with asthma also had high rates of comorbidities. However, the association with asthma and prolonged severe illness using multivariable analysis remained high suggesting that the coexistent chronic comorbidities did not independently affect the association of asthma with worse outcomes in children hospitalized with COVID‐19 in the PICU.

In conclusion, these findings from our study population support that asthma is an independent risk factor for hospital LOS, PICU LOS, and days on maximum respiratory support for children hospitalized with COVID‐19. Our findings are distinct from earlier studies that found that asthma is not a risk factor for COVID‐19 among children and may alert clinicians caring for children with COVID‐19, or similar viruses in the future, on the potential of asthma to cause severe, prolonged disease. Healthcare officials may also consider prevalence of asthma in vaccine prioritization efforts and for use of emerging or novel medications to treat COVID‐19 aimed at children. Our research serves as a platform for larger studies with longer periods of follow‐up to validate these findings.

AUTHOR CONTRIBUTIONS

J. C. Schroeder: Conceptualization; writing–original draft; methodology; visualization; writing–review & editing; validation; data curation; investigation; project administration. M. P. Sharron: Conceptualization; investigation; methodology; validation; writing–review & editing; data curation; resources; project administration. K. Wai: Conceptualization; investigation; writing–review & editing; validation; methodology; data curation; resources; project administration. D. K. Pillai: Formal analysis; software; conceptualization; investigation; writing–review & editing; methodology; validation; project administration; resources; supervision. D. Rastogi: Conceptualization; investigation; writing–review & editing; writing–original draft; supervision; resources; methodology; validation; visualization; project administration.

CONFLICTS OF INTEREST

The authors declare no conflicts of interest.

Supporting information

Supporting information.

Schroeder JC, Sharron MP, Wai K, Pillai DK, Rastogi D. Asthma as a comorbidity in COVID‐19 pediatric ICU admissions in a large metropolitan children's hospital. Pediatric Pulmonology. 2023;58:206‐212. 10.1002/ppul.26184

DATA AVAILABILITY STATEMENT

Data is currently under local IRB approval. It can be made available with appropriate IRB approval.