Rhinovirus-induced bronchiolitis: Lack of association between virus genomic load and short-term outcomes.

To the Editor:

Rhinovirus infection is a common trigger of bronchiolitis and early wheezing in children. Its detection is clinically important because rhinovirus-induced bronchiolitis/early wheezing probably is an important risk factor for recurrent wheezing and childhood asthma.1, 2 The mechanisms behind the undesirable long-term sequela remain poorly understood, but potential factors include atopic inheritance, weak antiviral defense, and viral factors.

Looking closely at previous reports on quantitative rhinovirus detection, we did not find any on the rhinovirus genomic load in bronchiolitis and short-term clinical outcomes, including the need for intensive care treatment. In other conditions, however, higher rhinovirus genomic load is related to the severity and/or duration of acute lower respiratory tract illness, and 1 study reported that it discriminated the response to systemic corticosteroids in terms of less recurrent wheezing.1, 4, 5 Data on the link between rhinovirus genomic load and clinical outcomes, however, are discordant because studies in subjects with asthma have not shown any clinical association. For these reasons and the relatively small samples in earlier studies, we examined the clinical significance of rhinovirus genomic load in bronchiolitis in 694 children with severe bronchiolitis. Our aim was to prospectively investigate whether rhinovirus genomic load in standardized nasopharyngeal aspirate (NPA) samples is associated with short-term outcomes of bronchiolitis. On the basis of previous literature, our hypothesis was that higher rhinovirus genomic load in bronchiolitis is associated with worse short-term outcomes.

For this analysis, we combined data from 2 multicenter prospective cohort studies of children younger than 2 years hospitalized for bronchiolitis; both studies used the same protocol. The US study was carried out at 16 sites across 12 US states during the 2007-2010 winter seasons (Multicenter Airway Research Collaboration [MARC]-30 USA) (see Table E1 in this article's Online Repository at www.jacionline.org), whereas the Finnish counterpart study was carried out in 3 Finnish sites during the 2008-2010 winter seasons (MARC-30 Finland). See more details of the MARC-30 and recruitment in this article's Online Repository at www.jacionline.org. The study protocol was approved by the ethics committees of participating hospitals, and the study was commenced only after obtaining written informed consent from the guardian.

Table E1

Principal investigators at the 19 participating sites in MARC-30

MARC-30 US sites
Besh Barcega, MD	Loma Linda University Children's Hospital, Loma Linda, Calif
John Cheng, MD, and Carlos Delgado, MD	Children's Healthcare of Atlanta at Egleston, Atlanta, Ga
Dorothy Damore, MD, and Nikhil Shah, MD	New York Presbyterian Hospital, New York, NY
Haitham Haddad, MD	Rainbow Babies & Children's Hospital, Cleveland, Ohio
Paul Hain, MD, and Mark Riederer, MD	Monroe Carell Jr. Children's Hospital at Vanderbilt, Nashville, Tenn
Frank LoVecchio, DO	Maricopa Medical Center, Phoenix, Ariz
Charles Macias, MD, MPH	Texas Children's Hospital, Houston, Tex
Jonathan Mansbach, MD, MPH	Boston Children's Hospital, Boston, Mass
Eugene Mowad, MD	Akron Children's Hospital, Akron, Ohio
Brian Pate, MD	Children's Mercy Hospital & Clinics, Kansas City, Mo
M. Jason Sanders, MD	Children's Memorial Hermann Hospital, Houston, Tex
Alan Schroeder, MD	Santa Clara Valley Medical Center, San Jose, Calif
Michelle Stevenson, MD, MS	Kosair Children's Hospital, Louisville, Ky
Erin Stucky Fisher, MD	Rady Children's Hospital, San Diego, Calif
Stephen Teach, MD, MPH	Children's National Medical Center, Washington, DC
Lisa Zaoutis, MD	Children's Hospital of Philadelphia, Philadelphia, Pa
MARC-30 Finland sites
Tuomas Jartti, MD	Turku University Hospital, Turku, Finland
Matti Korppi, MD	Tampere University Hospital, Tampere, Finland
Sami Remes, MD	Kuopio University Hospital, Kuopio, Finland

Investigators interviewed a guardian using a standard questionnaire and conducted a hospital chart review for further clinical data. NPA sampling was performed using a standardized protocol. Samples were stored at −80°C for later virus diagnostics, which included real-time PCR for adenovirus, coronaviruses NL-63, HKU1, OC43, and 229E, enterovirus, human metapneumovirus, influenza virus types A and B, 2009 novel H1N1, parainfluenza virus types 1, 2, and 3, rhinovirus, respiratory syncytial virus (RSV) A and B, Bordetella pertussis, and Mycoplasma pneumonia, as previously described. Rhinovirus genomic load was quantified by using real-time RT-PCR as the number of amplification cycles needed for a positive PCR test result (cycle threshold [CT]). CT values provide a semi-quantitative measure of genomic load, with a highly significant inverse linear relationship between genomic load and CT values. See more details of the virus diagnostics in this article's Methods section in the Online Repository at www.jacionline.org.

Our primary outcome measure was hospital length of stay (LOS) of 3 days or more.7, 8 The secondary outcome measure was intensive care treatment, defined as use of mechanical ventilation (continuous positive airway pressure and/or intubation during inpatient stay regardless of location) and/or admission to the intensive care unit. Tertiles of rhinovirus CT values permitted classification into 3 rhinovirus genomic load groups: low (CT ≥ 32.7), intermediate (CT, 27.2-32.6), and high (CT < 27.2). The association between rhinovirus genomic load and the outcomes was analyzed using unadjusted and multivariable logistic regression models. Several sensitivity analyses were performed to assess the robustness of the findings. All analyses were performed using SAS 9.4 (SAS Institute, Cary, NC). See more details of the outcomes and statistical methods in the Online Repository at www.jacionline.org.

Of 2615 enrolled children with bronchiolitis from 19 sites, 694 children (27%) had rhinovirus and comprised the analytic cohort (564 US children and 130 Finnish children). Among these children, the median age was 6 months (interquartile range, 3-12 months), 63% were boys, and 46% were non-Hispanic white. Two hundred sixty (37%) children had an LOS of 3 days or more, and 102 (15%) required intensive care treatment. See more details of demographics and clinical course in Table E2, Table E3 in this article's Online Repository at www.jacionline.org.

Table E2

Demographic characteristics and medical history of children hospitalized with rhinovirus bronchiolitis by genomic load category

Characteristic	Virus genomic load∗
	Low (n = 234)	Intermediate (n = 230)	High (n = 230)	P value
Age (mo)				.15
<2	35 (15)	45 (20)	42 (18)
2-5.9	79 (34)	66 (29)	66 (29)
6-11.9	73 (31)	54 (24)	71 (31)
12-23.9	47 (20)	65 (28)	51 (22)
Sex: male	144 (62)	158 (69)	136 (59)	.09
Race/ethnicity				<.001
Non-Hispanic white	80 (34)	124 (54)	118 (51)
Non-Hispanic black	71 (30)	42 (18)	38 (17)
Hispanic	72 (31)	58 (25)	70 (30)
Other	11 (5)	6 (3)	4 (2)
Insurance				.52
Nonprivate	154 (66)	162 (70)	160 (70)
Private	80 (34)	68 (30)	70 (30)
Family history of asthma				.36
Neither parent	152 (65)	153 (67)	166 (72)
Either mother or father	66 (28)	66 (29)	56 (24)
Both parents	10 (4)	8 (4)	4 (2)
Unknown/missing	6 (3)	3 (1)	4 (2)
Maternal smoking during pregnancy	41 (18)	38 (17)	37 (16)	.91
Gestational age				.84
<32 wk	16 (7)	21 (9)	16 (7)
32-36 wk	41 (18)	42 (18)	41 (18)
≥37 wk or “full term”	173 (74)	160 (70)	171 (74)
Is or was breast-fed	147 (63)	149 (65)	159 (69)	.34
History of wheezing	74 (32)	82 (36)	77 (34)	.66
History of eczema	62 (27)	34 (15)	52 (23)	.006
History of intubation	24 (10)	22 (10)	28 (12)	.64
Major, relevant, comorbid medical disorder†	65 (28)	48 (21)	48 (21)	.12
Cohort				<.001
United States	211 (90)	176 (77)	177 (77)
Finland	23 (10)	54 (23)	53 (23)

Data are expressed as n (%) unless otherwise indicated.

Categorized CT values into tertiles to classify patients into 3 rhinovirus genomic load status groups: low (CT ≥ 32.7), intermediate (CT, 27.2-32.6), and high (CT < 27.2).

Defined by respiratory, cardiac, neurologic, gastrointestinal, and immunologic diseases.

Table E3

Clinical course of children hospitalized with rhinovirus bronchiolitis by genomic load category

Characteristic	Virus genomic load∗			P value
	Low (n = 234)	Intermediate (n = 230)	High (n = 230)
When difficulty breathing began (prehospitalization)				.10
≥1 d	66 (28)	74 (32)	87 (38)
<1 d	160 (68)	153 (67)	135 (59)
No difficulty prehospitalization	8 (3)	3 (1)	8 (3)
Presence of apnea (chart)	14 (6)	13 (6)	15 (7)	.92
Weight (kg), median (IQR)	7.3 (5.1-9.5)	7.0 (4.7-10.0)	7.3 (4.7-9.6)	.92
Pulse (bpm), median (IQR)	160 (144-176)	160 (144-173)	160 (147-176)	.94
Respiratory rate per minute, median (IQR)	48 (40-60)	50 (40-60)	48 (40-58)	.86
Oxygen saturation by pulse oximetry or ABG				.81
<90%	32 (14)	31 (13)	24 (10)
90% to 93.9%	40 (17)	39 (17)	41 (18)
≥94%	155 (66)	155 (68)	163 (71)
Retractions				.68
None	33 (14)	44 (19)	36 (16)
Mild	94 (40)	83 (36)	85 (40)
Moderate or severe	88 (38)	91 (40)	85 (37)
Missing	19 (8)	12 (5)	24 (10)
Oral intake				.01
Adequate	102 (44)	132 (57)	123 (53)
Inadequate	96 (41)	68 (30)	82 (36)
Missing	36 (15)	30 (13)	25 (11)
Coinfection				<.001
Rhinovirus + RSV	131 (56)	97 (42)	69 (30)
Rhinovirus + non-RSV pathogens	36 (15)	47 (20)	55 (24)
Sole rhinovirus infection	67 (29)	86 (37)	106 (46)
Length of stay (d), median (IQR)	2 (1-4)	2 (1-4)	2 (1-3)	.39
≥3	96 (41)	85 (37)	79 (34)	.33
Intensive care treatment	39 (17)	30 (13)	33 (14)	.71
Intubation and/or CPAP	20 (9)	12 (5)	11 (5)	.20
Intensive care unit admission	37 (16)	29 (13)	30 (13)	.65

Data are expressed as n (%) unless otherwise indicated.

ABG, Arterial blood gas; bpm, beats per minute; CPAP, continuous positive airway pressure; IQR, interquartile range.

Categorized CT values into tertiles to classify patients into 3 rhinovirus genomic load status groups: low (CT ≥ 32.7), intermediate (CT, 27.2-32.6), and high (CT < 27.2).

Overall, there was no significant association between rhinovirus genomic load (an inverse of the CT value) and risk of LOS of 3 days or more or risk of intensive care treatment, either in unadjusted analyses or in multivariable models adjusting for 8 patient-level variables and clustering of patients within sites (all P ≥ .40, Fig 1 , A; see Table E4 in this article's Online Repository at www.jacionline.org). Likewise, a sensitivity analysis focused on the first episode in infants younger than 12 months showed no significant associations (all P > .30; see Table E4). Similarly, rhinovirus genomic load had no significant associations with the outcomes, by country (see Fig E1, A and B, in this article's Online Repository at www.jacionline.org), coinfection (see Table E5 in this article's Online Repository at www.jacionline.org), atopy status (Fig 1, B; see Table E6, Table E7 in this article's Online Repository at www.jacionline.org), comorbid status (see Table E8 in this article's Online Repository at www.jacionline.org), or respiratory distress severity score (see Table E9 in this article's Online Repository at www.jacionline.org).

Fig 1

The relation between rhinovirus CT value and hospital LOS overall (A) and by atopic status (B) in children hospitalized for bronchiolitis.

Table E4

Unadjusted and multivariable associations of rhinovirus genomic load with bronchiolitis outcomes

Outcome and rhinovirus genomic load category	Unadjusted model∗		Adjusted model†		Sensitivity analysis‡
	OR (95% CI)	P value	OR (95% CI)	P value	OR (95% CI)	P value
Length of stay ≥3 d
Low	Reference	—	Reference	—	Reference	—
Intermediate	0.85 (0.56-1.29)	.78	1.07 (0.75-1.54)	.70	0.89 (0.58-1.37)	.60
High	0.96 (0.73-1.27)	.43	1.05 (0.65-1.68)	.85	0.92 (0.63-1.34)	.65
Intensive care treatment
Low	Reference	—	Reference	—	Reference	—
Intermediate	0.89 (0.58-1.37)	.60	0.97 (0.67-1.40)	.87	0.69 (0.30-1.54)	.36
High	0.92 (0.63-1.34)	.65	0.78 (0.43-1.40)	.40	0.84 (0.45-1.55)	.58

OR, Odds ratio.

Unadjusted model adjusting for clustering of patients within the sites using the generalized estimating equations.

Multivariable model adjusting for 8 patient-level variables (age, sex, race, gestational age, history of wheezing, history of eczema, comorbid medical disorder, and viral coinfection status [rhinovirus plus RSV and rhinovirus plus non-RSV pathogens]) and clustering of patients within the sites.

Multivariable model using a restrictive definition of children with bronchiolitis—ie, those younger than 12 months and without history of wheezing (n = 389).

Fig E1

The relation between rhinovirus CT value and hospital LOS in US (A) and Finnish (B) cohorts of children with bronchiolitis.

Table E5

Unadjusted and multivariable associations of rhinovirus genomic load with bronchiolitis outcomes, according to the coinfection status

Outcome and rhinovirus genomic load category	Rhinovirus only				Rhinovirus plus RSV				Rhinovirus plus non-RSV pathogens
	Unadjusted model∗		Adjusted model†		Unadjusted model∗		Adjusted model†		Unadjusted model∗		Adjusted model†
	OR (95% CI)	P value	OR (95% CI)	P value	OR (95% CI)	P value	OR (95% CI)	P value	OR (95% CI)	P value	OR (95% CI)	P value
Length of stay ≥3 d
Low	Reference	—	Reference	—	Reference	—	Reference	—	Reference	—	Reference	—
Intermediate	0.97 (0.52-1.82)	.92	1.24 (0.50-3.06)	.64	1.02 (0.68-1.52)	.94	1.12 (0.79-1.59)	.53	1.63 (0.80-3.33)	.18	2.44 (1.06-5.63)	.04
High	1.17 (0.61-2.25)	.63	1.27 (0.62-2.59)	.52	0.86 (0.52-1.43)	.56	0.83 (0.45-1.55)	.57	1.52 (0.54-4.26)	.43	2.25 (0.86-5.90)	.10
Intensive care treatment
Low	Reference	—	Reference	—	Reference	—	Reference	—	Reference	—	Reference	—
Intermediate	0.98 (0.28-3.44)	.98	1.06 (0.22-5.12)	.94	0.84 (0.50-1.44)	.53	0.56 (0.32-0.98)	.04	0.69 (0.21-2.29)	.54	0.97 (0.40-2.43)	.95
High	1.06 (0.52-2.16)	.88	1.07 (0.37-3.07)	.90	0.90 (0.59-1.37)	.61	0.88 (0.54-1.43)	.60	0.77 (0.21-2.83)	.69	1.23 (0.43-3.51)	.70

OR, Odds ratio.

Unadjusted model adjusting for clustering of patients within the sites using the generalized estimating equations.

Multivariable model adjusting for 7 patient-level variables (age, sex, race, gestational age, history of wheezing, history of eczema, and comorbid medical disorder) and clustering of patients within the sites.

Table E6

Unadjusted and multivariable associations of rhinovirus genomic load with bronchiolitis outcomes in atopic children∗ (n = 148)

Outcome and rhinovirus genomic load category	Unadjusted model†		Adjusted model‡
	OR (95% CI)	P value	OR (95% CI)	P value
Length of stay ≥3 d (n = 51 for outcome)
Low	Reference	—	Reference	—
Intermediate	0.50 (0.28-0.88)	.02	0.35 (0.13-0.91)	.03
High	0.57 (0.31-1.02)	.06	0.61 (0.26-1.40)	.24
Intensive care treatment (n = 15 for outcome)
Low	Reference	—	Reference	—
Intermediate	0.39 (0.08-1.89)	.24	0.12 (0.02-0.81)	.03
High	0.67 (0.21-2.16)	.51	0.55 (0.12-2.60)	.45

OR, Odds ratio.

Children with history of eczema.

Unadjusted model adjusting for clustering of patients within the sites using the generalized estimating equations.

Multivariable model adjusting for 7 patient-level variables (age, sex, race, gestational age, history of wheezing, comorbid medical disorder, and viral coinfection status [rhinovirus plus RSV and rhinovirus plus non-RSV pathogens]) and clustering of patients within the sites.

Table E7

Unadjusted and multivariable associations of rhinovirus genomic load with bronchiolitis outcomes in nonatopic children∗ (n = 546)

Outcome and rhinovirus genomic load category	Unadjusted model†		Adjusted model‡
	OR (95% CI)	P value	OR (95% CI)	P value
Length of stay ≥3 d (n = 209 for outcome)
Low	Reference	—	Reference	—
Intermediate	1.05 (0.74-1.50)	.78	1.18 (0.81-1.71)	.39
High	0.95 (0.56-1.60)	.84	1.12 (0.62-2.04)	.70
Intensive care treatment (n = 87 for outcome)
Low	Reference	—	Reference	—
Intermediate	0.89 (0.53-1.50)	.67	0.74 (0.39-1.41)	.36
High	0.88 (0.60-1.29)	.51	0.86 (0.59-1.27)	.46

OR, Odds ratio.

Children without history of eczema.

Unadjusted model adjusting for clustering of patients within the sites using the generalized estimating equations.

Multivariable model adjusting for 7 patient-level variables (age, sex, race, gestational age, history of wheezing, comorbid medical disorder, and viral coinfection status [rhinovirus plus RSV and rhinovirus plus non-RSV pathogens]) and clustering of patients within the sites.

Table E8

Unadjusted and multivariable associations of rhinovirus genomic load with bronchiolitis outcomes in children without comorbid medical disorder (n = 528)

Outcome and rhinovirus genomic load category	Unadjusted model∗		Adjusted model†
	OR (95% CI)	P value	OR (95% CI)	P value
Length of stay ≥3 d (n = 198 for outcome)
Low	Reference	—	Reference	—
Intermediate	0.88 (0.64-1.22)	.44	1.00 (0.69-1.44)	.99
High	0.82 (0.52-1.30)	.40	1.07 (0.68-1.70)	.77
Intensive care treatment (n = 81 for outcome)
Low	Reference	—	Reference	—
Intermediate	0.88 (0.52-1.49)	.63	0.80 (0.37-1.73)	.57
High	0.93 (0.69-1.26)	.64	0.99 (0.60-1.63)	.98

OR, Odds ratio.

Unadjusted model adjusting for clustering of patients within the sites using the generalized estimating equations.

Multivariable model adjusting for 8 patient-level variables (age, sex, race, gestational age, history of wheezing, comorbid medical disorder, and viral coinfection status [rhinovirus plus RSV and rhinovirus plus non-RSV pathogens]) and clustering of patients within the sites.

Table E9

Unadjusted and multivariable associations of rhinovirus genomic load with respiratory distress severity score∗† at presentation (n = 694)

Rhinovirus genomic load category	Unadjusted model†		Adjusted model‡
	β Coefficient (95% CI)	P value	β Coefficient (95% CI)	P value
Low	Reference	—	Reference	—
Intermediate	0.03 (0.47-0.40)	.88	0.02 (0.42-0.45)	.94
High	0.11 (0.55-0.34)	.64	0.14 (0.31-0.59)	.55

Bajaj L, Turner CG, Bothner J. A randomized trial of home oxygen therapy from the emergency department for acute bronchiolitis. Pediatrics 2006;117:633-40.

Linear regression model with respiratory distress severity score as the dependent variable.

Multivariable linear regression model adjusting for 8 patient-level variables (age, sex, race, gestational age, history of wheezing, history of eczema, comorbid medical disorder, and viral coinfection status [rhinovirus plus RSV and rhinovirus plus non-RSV pathogens]).

In summary, we found no association between rhinovirus genomic load and short-term outcomes of bronchiolitis. Our hypothesis was justified on the basis of previous clinical data,1, 4, 5 which were also supported by in vitro data. Although multiple viral infections are relatively common in severe bronchiolitis (15% to 30%),7, 8 the interplay between viruses is poorly understood. Coinfection with RSV and rhinovirus has been linked to more severe short-term outcomes of bronchiolitis compared with RSV alone, but we found no link between rhinovirus genomic load, coinfections, and these same outcomes. Even when examining the rhinovirus-only group, the association was null. Moreover, investigation of the interaction between the rhinovirus genomic load and atopic status was interesting because atopic children appear to be more susceptible than nonatopic children to rhinovirus-induced wheezing.

Considering the large sample size, careful standardization of NPA sampling, and virus diagnostics done with the same protocol in a single laboratory, our results truly suggest no significant association between rhinovirus genomic load and an LOS of 3 days or more or need for intensive care treatment. Although 1 study suggested that rhinovirus genomic load has more clinical relevance in children older than 12 months, this association is not supported by our data or other reports. Because our results contrast the direct association between RSV genomic load and short-term outcomes of bronchiolitis, we speculate that a host response to infection may be more important than virus load in determining the short-term clinical course of rhinovirus-induced bronchiolitis.

The study has potential limitations. First, bronchiolitis is a clinical diagnosis without a common international definition, so we included children up to age 2 years with recurrent wheezing. Results, however, remained consistent when the analysis was restricted to children experiencing their first episode of breathing difficulty during infancy (age <12 months). Second, clinical decisions (eg, hospital admission/discharge or intensive care treatment) were not based on standardized criteria, which may have caused further variability of care. However, the significant association persisted after adjusting for clustering at the hospital level. Third, one might argue that samples from the upper respiratory tract do not reflect conditions in the lower respiratory tract and that nasal airway epithelial cells may respond differently than bronchial epithelial cells to rhinovirus infections. To our knowledge, there are no data on the comparison of rhinovirus genomic load between upper and lower airway samples and their relation to symptoms. Fourth, one could also argue whether we measured the peak of rhinovirus replication due to lack of longitudinal sampling. A peak in virus concentration typically occurs at 48 to 72 hours after infection in experimental models. Because the duration of prehospital symptoms is typically 1 to 3 days in rhinovirus-induced bronchiolitis, our time window of the first 24 hours of the hospitalization may have been optimal. Fifth, we did not sequence rhinoviruses.14, 15 Last, the results may not be generalizable to outpatient clinics because all our study subjects were hospitalized.

Challenges in future studies include more careful standardization of analysis (ie, standardization to housekeeping gene), investigation of viremia (ie, links to more compromised clinical outcome), virus genotyping (ie, rhinovirus species and rapid evolution of the virus), and more careful analysis of the replication/transcription status of the virus (ie, separate analysis of positive- and negative-stranded virus RNA).5, 6 Our findings call attention to the need for more detailed analysis of virology, along with host response and genetics, when investigating predictors of short-term outcomes of severe rhinovirus-induced bronchiolitis.