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. Author manuscript; available in PMC: 2021 Oct 1.
Published in final edited form as: Cardiol Young. 2020 Dec 14;31(4):547–555. doi: 10.1017/S1047951120004333

Acute respiratory infections in hospitalized infants with congenital heart disease

Namrata Ahuja a,b, Wendy J Mack c, Susan Wu a,b, John C Wood b,d, Christopher J Russell a,b
PMCID: PMC8058167  NIHMSID: NIHMS1645999  PMID: 33308367

Abstract

Objectives:

To assess the overall burden and outcomes of acute respiratory infections in pediatric inpatients with congenital heart disease (CHD).

Methods:

This is a retrospective cross-sectional study of non-neonates <1 year with CHD in the Kid’s Inpatient Database from 2012. We compared demographics, clinical characteristics, cost, length of stay, and mortality rate for those with and without respiratory infections. We also compared those with respiratory infections who had critical CHD versus non-critical CHD. Multivariable regression analyses were done to look for associations between respiratory infections and mortality, length of stay, and cost.

Results:

Of the 28,696 infants with CHD in our sample, 26% had respiratory infections. Respiratory infection associated hospitalizations accounted for $440 million in costs (32%) for all CHD patients. After adjusting for confounders including severity, mortality was higher for those with respiratory infections (OR 1.5, p = 0.003), estimated mean length of stay was longer (14.7 days versus 12.2, p<0.001), and estimated mean costs were higher ($53,760 versus $46,526, p<0.001). Compared to infants with respiratory infections and non-critical CHD, infants with respiratory infections and critical CHD had higher mortality (4.5% versus 2.3%, p<0.001), longer mean length of stay (20.1 days versus 15.5 days, p<0.001), and higher mean costs ($94,284 versus $52,585, p<0.001).

Conclusion:

Acute respiratory infections are a significant burden on infant inpatients with CHD and is associated with higher mortality, costs, and longer length of stay; particularly in those with critical CHD. Future interventions should focus on reducing the burden of respiratory infections in this population.

Keywords: Respiratory infection, Bronchiolitis, Congenital heart disease

INTRODUCTION

Acute respiratory infections such as pneumonia and bronchiolitis are common for both healthy infants and those with congenital heart disease (CHD). Previous studies showed children with CHD and viral bronchiolitis stay hospitalized 3 times longer,1 have up to 37 times the mortality rate,1,2 and have hospitalizations that cost 3 times more1 when compared to children with bronchiolitis without CHD. While most research on respiratory infections hospitalizations in infants with CHD focuses on viral bronchiolitis, studies that examine non-bronchiolitis respiratory infections in children with CHD suggest high incidence rates and poor outcomes. A multicenter study in Italy showed that non-bronchiolitis respiratory infections accounted for two-thirds of respiratory infections related hospitalizations in children under 2 years of age with CHD.3 A population study in Sweden showed higher relative risks for hospitalization for children with CHD who have non-Respiratory Syncytial Virus (RSV) infections including non-RSV pneumonia (8.87-10.26), compared to those with RSV infection (5.99-7.23).4 Despite the high prevalence of non-bronchiolitis respiratory infections in children with CHD, to our knowledge no studies in the United States have published on this broader population. Due to global differences in demographics, models of care, and practice standards, the findings in European studies are unlikely to be generalizable to a United States cohort.

The objectives of this study are (1) to quantify the burden of all acute respiratory infections in pediatric inpatients with CHD in the United States; and (2) to compare length of stay, cost, and mortality for those with acute respiratory infections, versus those without.

MATERIAL AND METHODS

Data source and sample

We conducted a multicenter, retrospective cross-sectional study using data from Kids’ Inpatient Database from 2012, a national administrative dataset of inpatients from age 0 to 20 discharged in 2012 from all non-rehabilitation hospitals in 44 participating states in the US.5 Our sample included patients under the age of 1 year old with International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes consistent with CHD (745-747.49). We excluded neonates ≤ 28 days old to exclude birth hospitalizations.

Acute respiratory infections

Acute respiratory infection was defined as having a qualifying Clinical Classifications Software category as defined by the Kids’ Inpatient Database for Respiratory Infections,7 which includes ICD-9-CM codes for pneumonia, influenza, bronchitis/bronchiolitis, and other upper respiratory infections (e.g., tonsillitis, croup), in any of the patient’s 25 discharge diagnoses.

Critical versus non-critical congenital heart disease

Using ICD-9-CM codes, we stratified our sample into those with critical CHD, defined as conditions that require surgical or cardiac catheterization intervention within the first year of life6 (e.g. hypoplastic left heart syndrome) and those without critical CHD (e.g. ventricular septal defects; supplementary table 1).

Patient demographics and clinical characteristics

Demographics include sex, race (categorized as non-Hispanic White, non-Hispanic Black, Hispanic, and other), and payer (categorized as Medicaid/Medicare, private insurance/HMO, and other). Clinical characteristics include, complex chronic conditions using Feudtner et al’s classification system,8 severity of illness defined by Hospitalization Resource Intensity Score for Kids (calculated using cost and All Patient Refined Diagnosis Related Group Severity of Illness score),9 whether the admission was for cardiac surgery (defined as cardiac surgery occurring on day 0 or 1 of hospitalization, identified by using Clinical Classification Software procedure category for ‘Operations on the Cardiovascular System” as well as a database defined variable for number of days from admission to procedure.

Outcome variables

Primary outcomes of interest studied include in-hospital mortality rate, length of stay (in days), and estimated cost (in dollars). Cost was estimated from charge data provided for each discharge, using hospital specific cost-to-charge ratios provided by the database.10

Statistical analyses

All analyses reflected the Kids’ Inpatient Database complex sampling design; the stratification, hospital-level clustering, and sampling weight variables from the database, as well as definition of the specified study group (infants with CHD) as a study subpopulation, were used to obtain national estimates as well as standard errors and 95% confidence intervals. We conducted one set of bivariate analyses to assess the relationships between respiratory infections and all other variables for all infants with CHD, and another set to assess the relationships between non-critical and critical CHD for all infants with respiratory infections (specifying the survey subpopulation as infants with CHD and respiratory infections). Descriptive statistics generated national estimates of numbers and proportions (with 95% confidence interval) of patients by patient demographics, and patient clinical characteristics. Differences in proportions on each characteristic between respiratory infections and no respiratory infections, followed by non-critical and critical CHD were statistically tested with a Pearson’s chi-square test statistic that was corrected for the survey design effects and reported as an F-statistic.

A multivariable logistic regression model was used to estimate the association between presence of respiratory infections and mortality, and generalized linear models were used to estimate the association between presence of respiratory infections and the dependent outcome variables of length of stay and cost. Length of stay used a negative binomial regression (negative binomial random variable, log link function); cost used a gamma regression (gamma random variable, log link function). The stratification, clustering, and sampling weight variables were incorporated into the analysis to provide appropriate estimates of standard errors. Associations for the generalized linear models are presented as exponentiated regression estimates, with 95% confidence intervals; exponentiated regression coefficients for these models represent the fold-difference (i.e., ratio) in the covariate-adjusted mean length of stay (or cost) in discharges from respiratory infections compared to non-respiratory infections discharges. p-Covariates used in the adjusted mortality, length of stay and cost models included sex, race, payer, critical CHD, admitted for cardiac surgery, Hospitalization Resource Intensity score (in quartiles), presence of complex chronic condition, and type of complex chronic condition.

All analyses used two-tailed tests with a significance level of 0.05. Statistical analysis was carried out using Stata (Version 15, StataCorp, College Station TX) software for survey data analysis.

RESULTS

There were 28,696 discharges (including deaths) that met inclusion criteria (Figure 1). Of these, 73% had non-critical CHD and 26% had an acute respiratory infection. The most common non-critical congenital heart lesions were ostium secundum atrial septal defect, ventricular septal defect and patent ductus arteriosus. The most common critical congenital heart lesion was Tetralogy of Fallot, hypoplastic left heart syndrome, and coarctation of the aorta. Acute respiratory infections accounted for 32% of the hospital days (121, 686 days) and costs ($438 million) for all hospitalizations in children with CHD. The overall mortality rate was 2%.

Figure 1:

Figure 1:

Flow-chart depicting sample selection, inclusion and exclusion criteria, and subgroups for children with congenital heart disease (CHD) admitted with and without acute respiratory infection (ARI).

1The sample was weighted using a weighting variable provided in the KID 2012 database, to obtain national estimates from the raw data.

Table 1 compares patient characteristics and outcomes for those without respiratory infections versus with respiratory infections. Patient demographics varied between the two groups: for those with a respiratory infection, a higher proportion of discharges were male, nonwhite, and had public insurance. Clinical characteristics also varied; a higher proportion of discharges with a respiratory infection had non-critical CHD, were not admitted for cardiac surgery, had a lower mean Hospitalization Resource Intensity score, and had a respiratory complex chronic condition. Mortality rate was higher in discharges with a respiratory infection, as was mean length of stay and cost.

Table 1:

Patient characteristics and outcomes for infant inpatients with congenital heart disease (CHD) with acute respiratory infection (ARI) versus without ARI.

No ARI
n = 21,240
ARI
n = 7,456
Number Percent
(95% CI)
Number Percent
(95% CI)
p-value
Patient demographics
Gender
  Male 11,310 53.3% (52.3-54.2) 4,125 55.3% (54.0-56.7) 0.007
  Female 9,930 46.8% (45.8-47.7) 3,331 44.7% (43.4-46.0)
Race/Ethnicity
  White 9,389 49.8% (45.9-53.7) 2,848 42.2% (38.6-45.9) <0.001
  Black 2,962 15.7% (13.9-17.7) 1,304 19.3% (17.1-21.8)
  Hispanic 4,132 21.9% (18.7-25.5) 1,872 27.7% (24.0-31.9)
  Other 2,379 12.6% (10.7-14.8) 728 10.8% (9.2-12.7)
Payer
  Public insurance 11,903 56.2% (53.2-59.2) 4,932 66.3% (63.9-68.6) <0.001
  Private insurance/HMO 1,538 36.5% (34.0-39.1) 2,030 27.3% (25.6-29.1)
  Other 1538 7.3% (5.5-9.6) 475 6.4% (4.8-8.4)
Clinical characteristics
Has critical congenital heart disease 6,449 30.4% (28.5-32.3) 1,337 17.9% (16.4-19.6) <0.001
Type of acute respiratory illness
  Pneumonia/influenza - - 2,732 36.7% (34.6-38.8)
  Bronchitis/bronchiolitis - - 3,640 48.8% (46.7-50.9)
  Other upper respiratory infection - - 2,331 31.3% (29.3-33.3)
Admitted for cardiac surgery 5,237 24.7% (22.5-26.9) 489 6.6% (5.6-7.6) <0.001
APR-DRG Severity of Illness Score
  Minor to Moderate Severity 7,271 34.3% (32.7-35.9) 2,540 34.1% (32.0-36.2) 0.85
  Major to Extreme Severity 13,946 65.7% (64.1-67.3) 4,911 65.9% (63.8-68.0)
Mean H-RISK score (95% CI) 6.8 (6.5-7.2) 6.2 (5.7-6.7) 0.002
Has a complex chronic condition (CCC) 18,508 87.1% (86.0-88.2) 5,850 78.5% (76.6-80.2) <0.001
Type of CCC
  Cardiovascular 14,338 67.5% (65.5-69.4) 4,319 57.9% (56.1-59.7) <0.001
  Respiratory 2,200 10.4% (9.6-11.1) 1,252 16.8% (15.5-18.2) <0.001
  Gastrointestinal 4,517 21.3% (20.1-22.5) 1,465 19.7% (18.1-21.3) 0.05
  Other congenital or genetic 5,040 23.7% (22.7-24.7) 1,961 26.3% (24.7-28.0) 0.002
  Metabolic 879 4.1% (3.7-4.6) 292 3.9% (3.4-4.6) 0.49
  Hematologic/immunologic/malignancy 943 4.4% (4.0-4.9) 404 5.4% (4.7-6.2) 0.008
  Technology dependence 5,208 24.5% (23.3-25.8) 1,902 25.5% (23.7-27.4) 0.26
  Neonatal 2,215 10.4% (9.5-11.4) 863 11.6% (10.5-12.8) 0.09
  Renal/urologic/transplant 1,282 6.0% (5.5-6.6) 336 4.5% (3.9-5.2) <0.001
Mean number of CCC (95% CI) 1.56 (1.53-1.60) 1.53 (1.47-1.59) 0.27
Outcomes
Mortality 410 1.9% (1.7-2.2) 200 2.7% (2.2-3.2) 0.002
Mean length of stay in days (95% CI) 12.0 (11.4-12.7) 16.3 (14.9-17.8) <0.001
Mean cost in dollars (95% CI) 45,906 (41,720-50,092) 60,070 (52,096-68,044) <0.001

Table 2 shows the differences in characteristics and outcomes for infants with respiratory infections between those with non-critical CHD versus critical CHD. There were no significant differences in patient demographics between groups. The distribution of types of respiratory infections differed between groups, with a higher proportion of those with non-critical CHD with pneumonia and bronchiolitis. The vast majority of children in the ‘Other upper respiratory infection’ group had non-tonsillitis illnesses (with only 55 with tonsillitis). A higher proportion of those with critical CHD had other upper respiratory infections, were admitted for cardiac surgery, and had a gastrointestinal complex chronic condition, technology dependence, or hematologic/immunologic/malignancy complex chronic condition, and had higher mean Hospitalization Resource Intensity scores. Proportions with respiratory complex chronic condition were similar in both groups. Outcomes were worse in discharges with critical CHD, with more than double the mortality, longer mean length of stay, and higher mean cost.

Table 2:

Patient characteristics and outcomes for infant inpatients with acute respiratory infection (ARI), with non-critical congenital heart disease (CHD) versus critical CHD.

Non-critical CHD and ARI
n = 6,117
Critical CHD and ARI
n = 1,337
Number Percent
(95% CI)
Number Percent
(95% CI)
p-value
Patient demographics
Gender
  Male 3,348 54.7% (53.2-56.2) 776 58.0% (54.0-61.9) 0.15
  Female 2,769 45.3% (43.8-46.8) 561 42.0% (38.1-46.0)
Race/Ethnicity
  White 2,314 41.9% (38.4-45.4) 534 43.7% (37.9-49.6) 0.05
  Black 1,107 20.0% (17.8-22.5) 197 16.1% (12.7-20.1)
  Hispanic 1,498 27.1% (23.5-31.0) 375 30.6% (24.9-37.0)
  Other 610 11.0% (9.4-13.0) 118 9.7% (7.3-12.7)
Payer
  Medicaid/Medicare 4,063 66.6% (64.3-68.7) 870 65.2% (60.5-69.7) 0.59
  Private insurance/HMO 1,663 27.2% (25.4-29.1) 367 27.6% (24.2-31.2)
  Other 379 6.2% (4.7-8.1) 96 7.2% (4.8-10.6)
Clinical characteristics
Type of acute respiratory illness
  Pneumonia/influenza 2,290 37.4% (35.3-39.6) 442 33.0% (29.5-36.8) 0.01
  Bronchitis/bronchiolitis 3,141 51.3% (49.2-53.4) 499 37.4% (33.9-41.0) <0.001
  Other upper respiratory infection 1,805 29.5% (27.6-31.5) 526 39.3% (35.4-43.4) <0.001
Admitted for cardiac surgery 260 4.3% (3.5-5.2) 229 17.1% (14.3-20.3) <0.001
APR-DRG Severity of Illness Score
  Minor to Moderate Severity 2,330 38.1% (35.9-40.4) 210 15.7% (13.6-18.2) <0.001
  Major to Extreme Severity 3,784 61.9% (59.6-64.1) 1,127 84.3% (81.8-86.5)
Mean H-RISK score (95% CI) 5.5 (5.0-5.9) 9.5 (8.4-10.6) <0.001
Has a complex chronic condition (CCC) 4,513 73.8% (71.7-75.7) 1,337 100% <0.001
Type of CCC
  Cardiovascular 2,981 48.7% (47.0-50.5) 1,337 100% <0.001
  Respiratory 1,040 17.0% (15.6-18.5) 212 15.9% (13.5-18.5) 0.41
  Gastrointestinal 1,090 17.8% (16.3-19.5) 375 28.1% (24.8-31.6) <0.001
  Other congenital or genetic 1,692 27.7% (25.9-29.5) 268 20.1% (17.1-23.3) <0.001
  Metabolic 247 4.1% (3.4-4.8) 44 3.3% (2.3-4.8) 0.32
  Hematologic/immunologic/malignancy 273 4.5% (3.8-5.2) 131 9.8% (7.6-12.5) <0.001
  Technology dependence 1,464 23.9% (22.1-25.8) 439 32.8% (29.4-36.4) <0.001
  Neonatal 813 13.3% (12.0-14.7) 50 3.8% (2.5-5.5) <0.001
  Renal/urologic/transplant 271 4.4% (3.8-5.2) 65 4.8% (3.6-6.5) 0.59
Mean number of CCC (95% CI) 1.5 (1.4-1.5) 1.9 (1.8-2.0) <0.001
Outcomes
Mortality 141 2.3% (1.9-2.8) 60 4.5% (3.3-6.0) <0.001
Mean length of stay in days (95% CI) 15.5 (14.0-17.0) 20.1 (17.7-22.4) <0.001
Mean cost in dollars (95% CI) 52,585 (45,277-59,893) 94,284 (77,204-111,364) <0.001

Table 3 displays results of our multivariable logistic regression model, which shows associations between respiratory infections and mortality, adjusting for demographic and clinical covariates that were significantly different between those with and without respiratory infections. Respiratory, neonatal, and renal/urologic/transplant complex chronic condition; and increasing H-RISK score were all independent risk factors for increased odds of mortality. Non-White race (Black, Hispanic, and Other) was independently associated with increased odds of mortality. Admission for cardiac surgery was independently associated with decreased odds of mortality. Discharges with a respiratory infection continued to have higher odds of mortality (1.50 (95% CI 1.15-1.95)) despite adjustments for covariates.

Table 3:

Logistic regression model for acute respiratory infection and other demographic and clinical covariates, versus mortality

Variable Odd ratios of mortality
(95% CI)
p-value
Unadjusted model
Had an acute respiratory infection 1.40 (1.14-1.74) 0.002
Adjusted model
Had an acute respiratory infection 1.50 (1.15-1.95) 0.003
Race
 White Ref
 Black 1.47 (1.10-1.96) 0.009
 Hispanic 1.43 (1.09-1.87) 0.009
 Other 1.55 (1.10-2.19) 0.012
Payer
 Public insurance Ref
 Private insurance/HMO 1.29 (1.02-1.63) 0.034
 Other 1.30 (0.89-1.89) 0.176
Has critical congenital heart disease 1.36 (1.05-1.78) 0.02
Admitted for cardiac surgery 0.46 (0.33-0.63) <0.001
Type of Complex Chronic Condition
 Respiratory 1.52 (1.14-2.01) 0.004
 Neonatal 2.07 (1.57-2.74) <0.001
 Renal/urologic/transplant 2.31 (1.78-2.99) <0.001
H-risk score
 First quartile (<1.4) Ref
 Second quartile (1.4-3.19) 3.47 (1.24-9.72) 0.02
 Third quartile (3.2-8.49) 13.49 (5.13-35.47) <0.001
 Fourth quartile (>8.5) 44.30 (17.14-114.49) <0.001

Variables included in model without statistically significant odds ratios: sex, has a complex chronic condition (CCC), congenital or genetic CCC, hematologic/immunologic/malignancy CCC

Table 4 displays results of our multivariable negative binomial regression model which shows associations between respiratory infections and length of stay. Respiratory, neonatal, and renal/urologic/transplant complex chronic condition; and increasing H-Risk score were all independent risk factors for increased fold-difference in length of stay. Black and Other race were independently associated with increased fold-difference in length of stay. Black and Other race were independently associated with increased fold-difference in length of stay. Private insurance, and admission for cardiac surgery were independently associated with decreased fold-difference in length of stay. Discharges with respiratory infections continued to have higher fold-difference in length of stay (1.19 (95% CI 1.13-1.24)), despite adjustments for covariates.

Table 4:

Unadjusted and Multivariable-adjusted negative binomial regression model of association between acute respiratory infection and length of stay (LOS)

Patient Characteristic Fold-difference in LOS
(95% CI) 1
p-value Estimated Mean LOS
in days (95% CI)
Unadjusted model
Had an acute respiratory infection
   No Ref <0.001 12.03 (11.37-12.69)
   Yes 1.36 (1.25-1.48) 16.33 (14.87-17.79)
Adjusted model
Had an acute respiratory infection
   No Ref 12.37 (11.73-13.00)
   Yes 1.19 (1.13-1.24) <0.001 14.70 (13.91-15.49)
Race
   White Ref
   Black 1.09 (1.02-1.17) 0.009
   Hispanic 1.06 (0.99-1.13) 0.122
   Other 1.12 (1.04-1.20) 0.002
Payer
   Public insurance Ref
   Private insurance/HMO 0.93 (0.88-0.97) 0.002
   Other 1.05 (0.88-1.26) 0.588
Has critical congenital heart disease 0.90 (0.85-0.96) 0.001
Admitted for cardiac surgery 0.60 (0.56-0.64) <0.001
Type of Complex Chronic Condition
   Respiratory 1.49 (1.39-1.59) <0.001
   Neonatal 1.97 (1.84-2.12) <0.001
   Renal/urologic/transplant 1.29 (1.19-1.39) <0.001
   Hematologic/immunologic 1.15 (1.06-1.25) 0.001
H-risk score
   First quartile (<1.4) Ref
   Second quartile (1.4-3.19) 1.66 (1.53-1.79) <0.001
   Third quartile (3.2-8.49) 2.93 (2.68-3.20) <0.001
   Fourth quartile (>8.5) 7.32 (6.59-8.12) <0.001
1

Exponentiated Poisson regression estimates (95% CI) estimating fold-difference in mean LOS (ARI/ No ARI)

Variables included in model without statistically significant fold-different in LOS: sex, has a complex chronic condition (CCC), congenital or genetic CCC.

Table 5 displays our multivariable gamma regression model which shows associations between respiratory infections and cost. Hispanic and other race; respiratory, neonatal, and renal/urologic/transplant complex chronic condition; private insurance; and increasing Hospitalization Resource Intensity score were all independent risk factors for increased fold-difference in cost. Discharges with respiratory infections continued to have higher fold-difference in cost (1.16 (95% CI 1.10-1.22)) despite adjustments for covariates.

Table 5:

Unadjusted and Multivariable-adjusted gamma regression model of association between presence of acute respiratory infection and cost

Patient Characteristic Fold-difference in cost
(95% CI) 1
p-value Estimated Mean Cost
in dollars (95% CI)
Unadjusted model
Had an acute respiratory infection
   No Ref <0.001 45,906 (41,711-50,101)
   Yes 1.31 (1.18-1.46) 60,070 (52,078-68,062)
Adjusted model
Had an acute respiratory infection
   No Ref 46,526 (43,040-50,012)
   Yes 1.16 (1.10-1.22) <0.001 53,760 (49,193-58,328)
Race
   White Ref
   Black 1.03 (0.96-1.11) 0.392
   Hispanic 1.14 (1.04-1.24) 0.003
   Other 1.17 (1.08-1.27) <0.001
Payer
   Public insurance Ref
   Private insurance/HMO 1.07 (1.01-1.14) 0.024
   Other 1.12 (0.97-1.29) 0.118
Has a complex chronic condition 1.06 (1.01-1.13) 0.032
Type of Complex Chronic Condition
   Respiratory 1.46 (1.36-1.57) <0.001
   Neonatal 1.67 (1.54-1.82) <0.001
   Renal/urologic/transplant 1.33 (1.21-1.45) <0.001
H-risk score
   First quartile (<1.4) Ref
   Second quartile (1.4-3.19) 1.99 (1.88-2.12) <0.001
   Third quartile (3.2-8.49) 5.33 (4.98-5.70) <0.001
   Fourth quartile (>8.5) 14.39 (14.07–16.83) <0.001
1

Exponentiated gamma regression estimates (95% CI) estimating fold-difference in mean cost (ARI/ No ARI)

Variables included in model without statistically significant fold-different in cost: sex, has a critical congenital heart disease, admitted for cardiac surgery, congenital or genetic complex chronic condition (CCC), hematologic or immunologic CCC.

DISCUSSION

In this cross-sectional retrospective cohort study of over 28,000 infant discharges with CHD, acute respiratory infections accounted for over 25% of hospitalizations, 33% hospital days and 33% of costs for all hospitalizations in infants with CHD. Having a respiratory infection during hospitalization was associated with a higher mortality, longer length of stay, and higher cost compared to those without respiratory infection, particularly in those with critical CHD. The differences in outcomes persisted even after accounting for demographic and clinical differences between those with and without a respiratory infection.

The poor outcomes of infants with CHD with respiratory infections are likely due to a combination of factors. This includes baseline deleterious effects on the lungs by CHD such as lung injury from over or under-perfusion, alterations in the composition of surfactant, and differences in lower airway resistance.11 Additionally for those with certain types of heart lesions, respiratory infections can precipitate pulmonary hypertensive crisis and/or heart failure. As a result of these factors, infants with CHD and respiratory infections may be more likely to have more severe illness with higher morbidity and mortality. In our study children with critical CHD and respiratory infections had longer mean length of stay, almost double the mean cost, and almost double the mortality rate compared to those with non-critical CHD and respiratory infections, demonstrating that children with critical CHD are particularly susceptible to poor sequelae from respiratory infections. Our study also demonstrated that some co-morbidities such as respiratory complex chronic conditions (CCC) are independent risk factors for worse outcomes. Respiratory CCC were more prevalent in those with ARI, and was associated with higher odds of mortality, longer LOS, and higher cost. This supports that the added insult of ARI in a child with both cardiac disease and a respiratory co-morbidity can lead to significantly worse outcomes.

The mortality rate in our study of infants with CHD and acute respiratory infections is similar to a that of a study of infants with Respiratory Syncytial Virus and CHD conducted outside the United States,12 but higher than one conducted in the United States.1 Our mean lengths of stay are longer and our costs higher the same United States study. These differences can be likely explained by our broader definition for respiratory infections which included illnesses other than bronchiolitis, as well as differences in how we defined critical CHD versus how the US study defined high risk CHD.

Of note, our study demonstrated minority race as an independent risk factor for differential outcomes. All non-White races (ie Black, Hispanic, and Other), had significantly higher odds of mortality. Black and ‘Other’ children additionally had significantly increased LOS, even after controlling for other co-variates, whereas Hispanic and ‘Other’ children had significantly increased costs. Future studies should further investigate the reasons for these differences, including the potential role of systemic differences in the way we care for children of different races, leading to worse outcomes for minority children.

There are several limitations to the current study. CHD can have varying degrees of severity based on the underlying lesion as well as stage of repair which can affect outcomes, and these can be challenging to classify using ICD-9-CM codes. We used non-critical versus critical CHD for our classification system, but there are instances where non-critical CHD such as large ventricular septal defects can lead to significant sequelae from respiratory infections. Due to the cross-sectional nature of the database we were unable to examine when a respiratory infection occurred during a hospitalization. Our study relied on the use of ICD-9-CM codes to identify patients who were billed for CHD, and respiratory infections which may not have been accurately coded by the medical coders; therefore, our study may have underestimated the true prevalence of these conditions. These limitations are balanced by some important strengths of our study. The large sample size in the Kids’ Inpatient Database provided adequate power to look at our relatively rare population of pediatric inpatients with CHD and respiratory infections, and the rare outcome of mortality. Additionally, Kids’ Inpatient Database 2012 represents discharges from most states, and from both children’s and non-children’s hospitals which makes our findings more generalizable.

There are several strategies that could potentially decrease the burden of children with CHD with respiratory infections, including measures to decrease the incidence of respiratory infections prior to hospitalization such as vaccination, and measures to decrease hospital-acquired respiratory infections. Palivizumab prophylaxis has demonstrated great efficacy in reducing the morbidity of respiratory syncytial viral infections in infants with hemodynamically significant CHD,13-15 yet studies suggest sub-optimal rates of administration to eligible infants, 16-19 and several studies highlight interventions to increase compliance.20-23 Similarly, influenza vaccination reduces mortality in children with CHD,24 yet only about half of children with high risk conditions such as cardiac disease receive it.25 Measures to reduce hospital-acquired respiratory infection include hand hygiene, personal protective equipment when appropriate, patient cohorting in facilities with shared rooms, and judicious hospital visitor restrictions.26

New infection prevention protocols will be in effect during respiratory viral season this year in the US due to the SARS-CoV-2 (COVID-19) pandemic including universal masking of workers in healthcare settings, as well as increased masking and social-distancing in the general populace. Future studies should evaluate the impact of these measures on the overall incidence and morbidity and mortality of acute respiratory illnesses in children with CHD this season.

Lastly, for those pediatric inpatients with CHD who develop respiratory infections despite preventative measures, there is little literature to guide their clinical care. Future studies should assess interventions and care guidelines that may improve the overall clinical course and outcomes of this population, with a particular focus on improving the care of children who are racial minorities and demonstrate some of the worst outcomes.

Supplementary Material

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Acknowledgments:

We would like to acknowledge Amir Hassan, BA, Clinical Research Assistant, for his help in creating and formatting the tables for this manuscript.

Financial Support:

This work was supported by grants UL1TR001855 and UL1TR000130 from the National Center for Advancing Translational Science (NCATS) of the U.S. National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

Conflict of Interest:

All authors have no potential conflicts of interest to disclose.

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