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Viral aetiology of bronchiolitis in hospitalised children in Qatar

  • Ibrahim Janahi1Email author,
  • Anas Abdulkayoum2,
  • Fawziya Almeshwesh1,
  • Mohamed Alkuwari1,
  • Ahmed Al hammadi1 and
  • Marwah Alameri1
BMC Infectious DiseasesBMC series – open, inclusive and trusted201717:139

https://doi.org/10.1186/s12879-017-2225-z

Received: 16 October 2016

Accepted: 27 January 2017

Published: 13 February 2017

Abstract

Background

Bronchiolitis is considered one of the earliest and most common causes of hospitalisation in young children. Development of molecular technologies allowed a better understanding of bronchiolitis aetiology. Results from cohort studies evaluating the association between single, multiple viral infections and clinical outcomes are conflicting. Data on viral bronchiolitis in children were found to be limited in Qatar. This study aimed to determine frequency and seasonal trends of viral pathogens causing acute bronchiolitis, and to explore association between viral pathogens, disease severity and length of stay (LOS).

Methods

This is a retrospective descriptive study, including children admitted in 2010 and 2011 with acute bronchiolitis. Presenting history, physical examination and respiratory viral co-infections as detected by molecular assays were analysed.

Results

At least one virus was detected in 315/369 (85.4%) of included children with single and multiple viruses in 67 and 33% of cases respectively. Respiratory syncytial virus (RSV) was the most detected virus, accounting for 51.2% followed by rhinovirus (RV) in 25.5% of cases. Fall and summer admissions were associated with longer LOS. On multivariate logistic regression analysis, retraction (OR 3.96; 95% CI 1.64,9.59) and age group 1–3 months (OR 3.09; 95% CI 1.06,9.05) were associated with longer LOS. Crepitation (OR 9.15; 95% CI 1.58,53.13), retraction (OR 4.10; 95% CI 1.05,16.12) and respiratory rate (OR 1.46; 95% CI 1.28,1.66) were associated with moderate to severe bronchiolitis. Identifying the viral agent did not influence disease severity or LOS.

Conclusion

Clinical presentation is of more relevance to LOS and disease severity than the detected viruses. Future studies should investigate the interplay between climate characteristics, population’s factors and the most detectable circulating viruses.

Keywords

Length of stay Bronchiolitis severity Multivariate predictors

Background

Bronchiolitis is considered one of the earliest and most common causes of hospitalisation among young children during their first 2 years of life [1]. Although the causative agents include bacteria, fungi and viruses, this acute infection is mainly attributed to respiratory syncytial virus, accounting for 50–90% of the cases [2, 3]. With the current utilisation of reverse transcriptase real-time polymerase chain reaction (PCR), the detection of specific viral nucleic acids facilitated a better understanding of the viral aetiology of the infection. The 2014 American Academy of Paediatrics bronchiolitis guideline recommends against the routine use of radiographic or laboratory studies on the basis that knowing the infecting pathogen would rarely alter the clinical management [4]. However, a growing body of literature has identified an association between specific infecting pathogens with short and long-term outcomes [5]. Association between viral co-infection and disease severity have been assessed in several studies but with conflicting findings [57]. Although bronchiolitis is a self-limiting condition, hospitalisation rate has increased during the last two decades [3]. Assessment of bronchiolitis severity, through a combination of clinical symptoms and physical signs, remains a standard measure in daily practice though its impact on clinical outcomes, such as length of hospital stay, has yet to be confirmed. Data has been reported on seasonal variation of viral activity with conflicting evidence on its significance on disease severity and clinical outcomes [8, 9]. In Qatar, viral aetiology of bronchiolitis in children has been limited. Therefore the aims of this retrospective, descriptive study were: to determine the frequency and seasonal trends of viral pathogens causing acute bronchiolitis, and to explore the association between specific viral pathogens, disease severity and length of stay (LOS).

Methods

Study design

This retrospective descriptive study took place at the paediatric wards of Hamad General Hospital (HGH), a 603- bed, tertiary-care facility in Doha, for two consecutive years, 2010 and 2011. The institutional review board at Hamad Medical Corporation approved the study, IRB number 12054.

Study population

The study population included children aged between 2 weeks- 2 years admitted to the paediatric ward at HGH with a diagnosis of acute bronchiolitis defined according to International Classification of Disease (ICD) code 466.1 in the 9th revision of the ICD. Based on recorded clinical diagnosis, an episode of acute bronchiolitis was determined by a constellation of clinical signs and symptoms including fever, rhinitis, tachypnoea, cough, wheezing, crackles, use of accessory muscles and possible chest X ray findings of hyperinflation of the lungs, peri-bronchial thickening, collapsed segment or a lobe of the lung and increase interstitial markings. Due to the potential for an atypical natural history of bronchiolitis, children with the following diagnoses were excluded: born prematurely, defined as <37 weeks of gestation, those with low birth weight, defined as birth weight <2.5 kg, with underlying chronic lung disease or neurological disease or congenital heart disease, and those immunocompromised or with hospital-acquired bronchiolitis.

Data collection

Medical charts of the children admitted to the paediatric ward during the study period were retrieved from the medical records department at HGH, a tertiary teaching hospital located in Doha, Qatar. A trained research staff screened patients’ discharge summaries for diagnosis of bronchiolitis. A data collection form (DCF) was developed to capture the necessary information. For every child who met the inclusion criteria the following data were collected: age, gender, family history of asthma and/or atopy, clinical presentation and vital signs upon admission and length of hospital stay. Bronchiolitis severity was based on a score ranging between 1 and 5 that assessed wheezing, retraction, respiratory rate and oxygen saturation (see Additional file 1: Table S1). Patients with score of 1 or 2 were considered to have mild bronchiolitis and to have moderate to severe bronchiolitis if score was between 3 and 4, with 5 indicating respiratory failure. Wheezing on physical exam was categorised as none, mild, moderate or severe. Retraction was categorised as none, intercostal, intercostal and subcostal or intercostal and subcostal with seesaw chest motion. Viral identification laboratory results, medical therapy and need of mechanical ventilation during hospital stay were recorded. Hospital admissions due to bronchiolitis were presented on an episode base.

Nasopharyngeal sample collection and analysis

Nasopharyngeal samples were collected by inserting Dacron™ polyester tipped or FLOQSwab™ in both nostrils till the nasopharynx and rotating at 360°. The swabs were placed into 3 ml of transport medium (Copan, UTM-RT™, CA, USA). Following collection, samples were kept on wet ice and transported to central processing lab of HGH during the working hours. Specimens that were not delivered immediately to the lab were stored in a refrigerator (4 – 8 °C) for no more than 24 h. Beyond that, samples were stored at -70 °C and transported on dry ice. EZ1 virus mini kit v 2.0, was used for nucleic acid extraction (Qiagen®, Hilden, Germany). Multiplex, real-time, polymerase chain reaction (RT-PCR) using FTDResp21 kit (Fast Track Diagnostics, Silema, Malta) was used for the detection of respiratory pathogens on Applied Biosystem™ 7500 instrument (ThermoFisher Scientific Inc, MA, USA). The kit detects the following respiratory pathogens: influenza A and B; coronaviruses NL63, 229E, OC43 and HKU1; parainfluenza viruses 1, 2, 3 and 4; human metapneumovirus A/B (hMPV); rhinovirus (RV); respiratory syncytial virus A/B (RSV); adenovirus (AdV); enterovirus (EV); parechovirus (PeV); bocavirus (BoV) and Mycoplasma pneumoniae (Mpneu).

Statistical analysis

The focus of the data analysis in our study was to determine frequency of each virus that is causing acute bronchiolitis in young children in our community and link it to the clinical presentation, length of hospital stay, severity of symptoms and need for intensive care support including invasive and non invasive ventilation. Categorical and continuous values were expressed as frequency (percentage) and mean ± SD or median and interquartile range (IQR) as appropriate. Descriptive statistics were used to summarise demographic, medical history, frequency of each virus and clinical characteristics of the patients. Associations between two or more qualitative variables were assessed using chi-square test and Fisher Exact test as appropriate. Quantitative data between the two independent groups were analysed using unpaired ‘t’ and Mann Whitney U tests as appropriate.

Univariate and multivariate logistic regression methods were used to assess and compute the predictive values of each predictor or risk factors for severity of bronchiolitis and hospital length of stay. For multivariate regression models, variables were considered if statistically significant at the P <0.10 level in univariate analysis or if determined to be clinically important. The results of logistic regression analyses were reported as odds ratio (OR) with 95% confidence intervals (CIs). Pictorial presentations of the key results were made using appropriate statistical graphs. A two-sided P value <0.05 was considered to be statistically significant. All statistical analyses were done using statistical packages SPSS 22.0 (SPSS Inc. Chicago, IL) and Epi Info 2000 (Centres for Disease Control and Prevention, Atlanta, GA).

Results

Patient identification and demographics

A total of 369 children were admitted to the hospital with a clinical diagnosis of bronchiolitis documented in their medical charts during the study period with 261 (75.2%) aged 3 months or younger and 247 (67%) were male sex as illustrated in Table 1. Of the 369 cases, 145 (39.3%) had a family history of atopy or asthma. On admission, 348 (94.3%) and 270 (73.2%) presented with cough and crepitation respectively, 261 (70.7%) had fever, while 251 (68.0%) and 231 (62.6%) experienced retracted breathing and wheezing respectively. Vitals signs (mean ± SD) including temperature 38.49 ± 0.80 °C, respiratory rate 62.51 ± 13.65 breaths per minute, pulse rate 167.88 ± 19.18 bpm and O2 saturation 96.40 ± 2.46% were recorded in the majority of the children. Generally, there were no differences in the clinical presentations between the males and the females. However, pertussis like symptoms were more frequently reported in females, 14/122 (11.5%), compared to males, 15/247 (6.1%).
Table 1

Demographic characteristics, clinical presentation and symptoms, viral etiology and management of children with acute bronchiolitis

Characteristics

Frequency (%)

Gender (n = 369)

 Male

247 (66.9%)

 Female

122 (33.1%)

Age (months) (n = 347)

  < 1 months

144 (41.5%)

 1 to 3 months

117 (33.7%)

  > 3 months

86 (24.8%)

Clinical and presenting symptoms (n = 369)

 Cough

348 (94.3%)

 Wheezing

231 (62.6%)

 Rales

15 (4.1%)

 Crepitation

270 (73.2%)

 Retraction

251 (68.0%)

 Fever

261 (70.7%)

 Apnea

24 (6.5%)

 Pertussis like symptoms

29 (7.9%)

 Family history of atopy or asthma

145 (39.3%)

 Max. Temperature (°C) (n = 353)

38.49 ± 0.80

 Max. Respiratory rate (br/m) (n = 351)

62.51 ± 13.65

 Max. Pulse (beat/m) (n = 351)

167.88 ± 19.18

 O2 Saturation (%) (n = 341)

96.40 ± 2.46

Initial Clinical Severity Score (n = 349)

 1

19 (5.4%)

 2

142 (40.7%)

 3

159 (45.6%)

 4

26 (7.4%)

 5

3 (0.9%)

Nationality (n = 369)

 Qatari

234 (63.4%)

 Non-Qatari

135 (36.6%)

Seasons (n = 355)

 Winter

154 (43.4%)

 Spring

43 (12.1%)

 Summer

20 (5.6%)

 Fall

138 (38.9%)

Viral Etiology (n = 369)

 RSV

189 (51.2%)

 Influenza A

3 (0.8%)

 Influenza B

1 (0.3%)

 ParaInfluenza 1

4 (1.1%)

 ParaInfluenza 2

4 (1.1%)

 ParaInfluenza 3

19 (5.1%)

 ParaInfluenza 4

3 (0.8%)

 Corona_NL63

3 (0.8%)

 Corona_COC43

16 (4.3%)

 Corona_229E

2 (0.5%)

 Corona_HKU

2 (0.5%)

 RV

94 (25.5%)

 Enterovirus

6 (1.6%)

 hMPV

23 (6.2%)

 Boca Virus

15 (4.1%)

 Parechovirus

11 (3.0%)

 Adenovirus

23 (6.2%)

 Other viruses

20 (5.4%)

RSV Respiratory syncytial virus, RV rhinovirus, hMPV Human metapneumovirus. Quantitative data were presented in mean ± SD. For some parameters the sum is not equal to total n = 369 due to some missing observations and respective % were computed based on non-missing observations

Seasonal distribution

The seasonal pattern of RSV and RV were generally distributed all year around although incidence of RSV infection peaked during the fall season whereas RV peaked during the spring. The findings of the current study revealed more adenovirus (ADV) infections in the summer months than spring (Fig. 1). Coronavirus (CoV-OC43) circulated predominantly during the winter months while parainfluenza virus 3 (PIV3) during the fall but sporadically across the year. Dual peaks were observed for human metapneumovirus (hMPV) during the spring and winter seasons.
Fig. 1

Monthly trends of respiratory viruses

The median LOS was longer during the summer (7 days) compared to the winter (6 days) and shortest in the fall and spring (5 days), Fig. 2a. Our findings show a peak in hospital admission rates during the winter season, 154 (41.7%), followed by the fall, 138 (37.4%) with least during the summer season, 20 (5.4%) as presented in Fig. 2b.
Fig. 2

a Length of stay, in days, across different seasons. b Seasonal variations in hospital admission rates (%)

Viral aetiologies and multiple co-infections

We used polymerase chain reaction (PCR) to establish the viral aetiology of acute bronchiolitis. At least one virus was detected in 315/369 (85.4%) of children with single virus in 211/315 (67%) and multiple viruses in 104/315 (33.0%). RSV was the most common virus identified, accounting for 189 cases (51.2%) followed by RV in 94 cases (25.5%), 23 cases (6.2%) of hMPV and ADV each. Influenza A and B were the least detected viruses accounting for less than 1% of the cases, as shown in Table 1.

Out of the 315 samples analysed, 27.3% had dual infections and three viruses were detected in 5.4% of the sample with a quadruple infection found in one case. There were no marked differences in the management of single and multiple infections. β-agonists were used in the majority of cases, followed by antibiotics, hypertonic saline and adrenaline, presented in Table 2.
Table 2

Management and complications of acute bronchiolitis

Characteristics

Frequency (%)

Assisted ventilation

 Yes

32 (8.7%)

Assisted ventilation type (n = 32)

 Non-invasive

22 (6%)

 Invasive

1 (0.3%)

 Both

9 (2.4%)

Therapy/Treatment (n = 369)

 β agonist

331 (89.7%)

 Adrenaline

151 (40.9%)

 0.9% saline

42 (11.4%)

 3.0% saline

160 (43.4%)

 Steroids

85 (23%)

 Antibiotics

239 (64.8%)

 Mucomist

6 (1.6%)

 Atrovent

38 (10.3%)

Complications (n = 369)

 Collapse

76 (20.6%)

 Barotrauma

0 (0)

 Atelectasis

97 (26.3%)

 Pneumonia

63 (17.1%)

 Sepsis

20 (5.4%)

 Acute respiratory distress syndrome

0 (0)

Respiratory viruses distribution by age-group, gender, medical history and clinical presentation

Children were grouped into three age groups with different rates of single and multiple viral infections, Table 3. In children aged <1 month, the most common detected virus was RSV (47.9%); for those between 1 and 3 months of age, RV (47.2%) was the most common virus. Children aged >3 months were found to be co-infected with RSV + RV (40%). Co-infection with RSV+ non-RV (75.8%) had the highest incidence in males whereas in females, RV+ non-RSV co-infection (40.9%) dominated. Family history of atopy or asthma, P = 0.008, and high respiratory rate, P = 0.026, were more common in RV single group, whereas crepitation was more frequent in the RSV+ non-RV co-infection group, P = 0.039. More children in the RV single group (91.7%) had LOS ≥4 days compared to the RSV single group (82.4%). Similar pattern was observed in terms of bronchiolitis severity with more children in the RV single group (65.7%) with moderate to severe bronchiolitis compared to children in the RSV single group (57.6%).
Table 3

Demographic characteristics, clinical presentations and seasonality of acute bronchiolitis by RSV, RV and other co-infections

  

RSV (n = 127)

RV (n = 36)

RSV + RV

(n = 25)

RSV+ any other non- RV (n = 33)

RV+ any other non-RSV (n = 22)

Others (n = 72)

P-value*

Gender

Male

76 (59.8)

27 (75)

15 (60)

25 (75.8)

13 (59.1)

53 (73.6)

0.180

Female

51 (40.2)

9 (25)

10 (40)

8 (24.2)

9 (40.9)

19 (26.4)

 

Age Group

<1 months

57 (47.9)

14 (38.9)

4 (16)

8 (25)

8 (36.4)

28 (42.4)

0.064

1 to 3 months

33 (27.7)

17 (47.2)

11 (44)

12 (37.5)

8 (36.4)

23 (34.8)

 

>3 months

29 (24.4)

5 (13.9)

10 (40)

12 (37.5)

6 (27.3)

15 (22.7)

 

Nationality

Qatari

90 (70.9)

22 (61.1)

16 (64)

22 (66.7)

11 (50)

42 (58.3)

0.335

Clinical and presenting symptoms

Cough

124 (100)

35 (97.2)

25 (100)

32 (97)

22 (100)

66 (97.1)

0.408

Wheezing

83 (68)

26 (72.2)

20 (83.3)

22 (68.8)

13 (59.1)

42 (62.7)

0.471

Crepitation

88 (78.6)

30 (85.7)

22 (91.7)

25 (96.2)

16 (76.2)

56 (93.3)

0.039

Retraction

89 (76.7)

29 (82.9)

18 (75)

28 (90.3)

13 (59.1)

50 (82)

0.121

Fever

90 (74.4)

25 (71.4)

19 (79.2)

28 (87.5)

16 (80)

51 (79.7)

0.621

Apnea

8 (7.3)

1 (3.1)

3 (13)

1 (4.2)

1 (5.3)

8 (13.8)

0.415

Pertussis like symptoms

9 (8.3)

3 (11.5)

5 (20)

2 (8.3)

3 (15.8)

5 (10.2)

0.613

Family history of atopy or asthma

54 (61.4)

20 (69)

10 (45.5)

14 (56)

3 (16.7)

29 (59.2)

0.008

Max. temperature (degree C)

38.49 ± 0.82

38.52 ± 0.88

38.64 ± 0.77

38.49 ± 0.79

38.63 ± 0.74

38.36 ± 0.84

0.687

Max. respiratory rate (Br/min)

61.3 ± 9.5

67.5 ± 20.1

60.3 ± 9.4

62.3 ± 7.1

59.6 ± 8.0

66.8 ± 20.5

0.026

Max. Pulse (Beat/min)

167.5 ± 15.2

170 ± 34

172.2 ± 14.8

164.2 ± 16.2

169 ± 10.8

168.4 ± 23.1

0.750

O2 Saturation

96.57 ± 2.40

95.25 ± 2.73

96.55 ± 1.60

95.8 ± 3.48

96.29 ± 1.87

96.42 ± 2.24

0.087

ICS score

3 to 4

72 (57.6)

23 (65.7)

14 (58.3)

17 (56.7)

10 (45.5)

34 (51.5)

0.692

Seasons

Winter

44 (34.9)

17 (47.2)

14 (56)

13 (39.4)

11 (50)

27 (40.9)

0.483

Spring

14 (11.1)

6 (16.7)

4 (16)

3 (9.1)

0 (0)

9 (13.6)

 

Summer

12 (9.5)

1 (2.8)

1 (4)

2 (6.1)

2 (9.1)

2 (3)

 

Fall

56 (44.4)

12 (33.3)

6 (24)

15 (45.5)

9 (40.9)

28 (42.4)

 

Assisted ventilation

Yes

12 (10)

6 (16.7)

1 (4.3)

2 (6.1)

2 (9.5)

8 (12.3)

0.642

LOS (days)

≥4 days

103 (82.4)

33 (91.7)

21 (87.5)

30 (90.9)

19 (86.4)

56 (84.8)

0.703

LOS Length of stay in hospital, ICS Initial clinical severity score. *P-values computed using one-way analysis of variance (ANOVA). Chi-square and Yates corrected Chi-square statistical tests methods

Analysis of risk factors of length of hospital stay and bronchiolitis severity

A total of 291 (82.4) had a LOS ≥4 days. On univariate logistic regression analysis, admission during the fall season (unadjusted OR 1.89; 95% CI 1.01,3.53; P = 0.046), cough (unadjusted OR 7.27; 95% CI 1.2,44.5; P = 0.032), retraction (unadjusted OR 2.70; 95% CI 1.5,5.1; P = 0.002), pulse rate (unadjusted OR 1.01; 95% CI 1.0,1.03; P = 0.011) were significantly associated with longer LOS as shown in Table 4. Oxygen saturation level (unadjusted OR 0.78; 95% CI 0.66,0.89; P = 0.001) was associated with shorter LOS. Detection of RV, RSV+ non-RV, age group 1–3 months and admission during the summer season increased LOS but these differences did not reach statistical significance (P >0.05). On multivariate logistic regression analysis, the only factors that remained statistically significant were retraction (adjusted OR 3.96; 95% CI 1.64,9.59; P = 0.002), age group 1–3 months (adjusted OR 3.09; 95% CI 1.06,9.05; P = 0.039) and high respiratory rate (adjusted OR 1.07; 95% CI 1.0,1.14; P = 0.05), provided in Additional file 1: Table S2.
Table 4

Predictors of length-of-stay ≥4 days among children with mild to severe bronchiolitis: logistic regression analysis

 

LOS <4 days

LOS ≥ 4 days

Odds Ratio (OR) (95% CI)

P-Value

Demographic characteristics

 Age group

   ≤ 1 month

25 (42.4%)

118 (41.5%)

1.36 (0.70, 2.7)

0.369

  1 to 3 months

15 (25.4%)

100 (35.2%)

1.92 (0.91, 4.0)

0.086

   > 3 months

19 (32.2%)

66 (23.2%)

1.0 (Reference)

 

  Male

39 (62.9%)

196 (67.4%)

1.22 (0.69, 2.15)

0.500

  Female

23 (37.1%)

95 (32.6%)

1.0 (Reference)

 

  Qatari

38 (61.3%)

185 (63.6%)

1.1 (0.63, 1.9)

0.735

  Non-Qatari

24 (38.7%)

106 (36.4%)

1.0 (Reference)

 

Types of viruses, seasonal trend and severity

 RSV

22 (50%)

103 (39.3%)

1.0 (Reference)

 

 RV

3 (6.8%)

33 (12.6%)

2.35 (0.66, 8.35)

0.187

 RSV + RV

3 (6.8%)

21 (8%)

1.50 (0.41, 5.46)

0.542

 RSV+ any other non-RV

3 (6.8%)

30 (11.5%)

2.14 (0.60, 7.63)

0.243

 RV+ any other non-RSV

3 (6.8%)

19 (7.3%)

1.35 (0.37, 4.97)

0.649

 Others

10 (22.7%)

56 (21.4%)

1.20 (0.53, 2.70)

0.667

Seasons

 Spring

8 (12.9%)

35 (12%)

1.25 (0.53, 2.90)

0.610

 Summer

2 (3.2%)

18 (6.2%)

2.57 (0.57, 11.6)

0.220

 Fall

18 (29%)

119 (41%)

1.89 (1.01, 3.53)

0.046

 Winter

34 (54.8)

119 (40.9)

1.0 (Reference)

 

 ICS score: 3 to 4

27 (43.5%)

156 (55.5%)

1.62 (0.93, 2.82)

0.089

 ICS score: 1 to 2

35 (56.5%)

125 (44.5%)

1.0 (Reference)

 

Medical history and physical exam findings

 Cough

59 (95.2%)

286 (99.3%)

7.27 (1.2, 44.5)

0.032

 Wheezing

40 (66.7%)

189 (66.5%)

0.99 (0.55, 1.8)

0.986

 Crepitation

42 (76.4%)

226 (85.6%)

1.84 (0.90, 3.7)

0.092

 Retraction

33 (60%)

215 (80.2%)

2.70 (1.5, 5.1)

0.002

 Fever

47 (78.3%)

212 (76.3%)

0.89 (0.45, 1.74)

0.731

 Apnea

3 (5.6%)

21 (8.4%)

1.56 (0.45, 5.4)

0.485

 Pertussis like symptoms

3 (5.5%)

26 (11%)

2.15 (0.63, 7.4)

0.225

 Family history of asthma

22 (55%)

121 (56.3%)

1.1 (0.53, 2.1)

0.881

 Maximum temperature (°C)

38.39 ± 0.87

38.52 ± 0.78

1.22 (0.86, 1.73)

0.255

 Maximum respiratory rate (br/m)

60.34 ± 15.13

62.99 ± 13.32

1.02 (0.99, 1.1)

0.160

 Maximum pulse rate (beat/m)

161.8 ± 22.1

169.1 ± 18.1

1.01 (1.0, 1.03)

0.011

 O2 saturation (%)

97.37 ± 1.84

96.18 ± 2.53

0.78 (0.66, 0.89)

0.001

LOS Length of stay in hospital, ICS Initial clinical severity score, OR odds ratio, CI confidence interval. Dichotomous outcome LOS <4 days considered as reference group

A total of 185 (53.4%) of the hospitalised children experienced moderate to severe bronchiolitis. On univariate logistic regression analysis, children in this group required greater need for respiratory support (OR 5.85; 95% CI 1.98,17.3; P = 0.001), experienced more wheezing (OR 1.82; 95% CI 1.15,2.89; P = 0.010), crepitation (OR 3.11; 95% CI 1.64,5.90; P = 0.001), and retraction (OR 5.65; 95% CI 3.13,10.2; P <0.001), increased respiratory rate (OR 1.09; 95% CI 1.07,1.12; P <0.001), increased pulse rate (OR 1.03; 95% CI 1.02,1.04; P < 0.001), but higher oxygen saturation levels reduced the odds of moderate to severe bronchiolitis (OR 0.85; 95% CI 0.77,0.93; P = 0.001) as presented in Table 5. On multivariate logistic regression analysis, crepitation (adjusted OR 9.15; 95% CI 1.58,53.13; P = 0.014), retraction (OR 4.10; 95% CI 1.05,16.12; P = 0.043), and increased respiratory rate (adjusted OR 1.46; 95% CI 1.28,1.66; P < 0.001) were significant predictors associated with bronchiolitis severity, provided in Additional file 1: Table S3. Complications including atelectasis, collapse, pneumonia and sepsis were reported in 97 (26.3%), 76(20.6%), 63(17.1%) and 20(5.4%) of hospitalised children respectively.
Table 5

Predictors of mild to severe ICS score among children with viral bronchiolitis: logistic regression analysis

 

ICS score: 1 to 2 (mild)

ICS score: 3 to 4 (moderate to severe)

Odds Ratio (OR) (95% CI)

P-Value

Demographic characteristics

 Age group

   ≤ 1 month

70 (44.0%)

68 (38.4%)

0.84 (0.49, 1.45)

0.535

  1 to 3 months

50 (31.4%)

64 (36.2%)

1.11 (0.63, 1.95)

0.720

   > 3 months

39 (24.5%)

45 (25.4%)

1.0 (Reference)

 

  Male

101 (62.7%)

131 (70.8%)

1.44 (0.92, 2.26)

0.111

  Female

60 (37.3%)

54 (29.2%)

1.0 (Reference)

 

  Qatari

97 (60.2%)

123 (66.5%)

1.31 (0.84, 2.03)

0.229

  Non-Qatari

64 (39.8%)

62 (33.5%)

1.0 (Reference)

 

Types of viruses, seasonal trend and severity

 RSV

53 (40.2%)

72 (42.4%)

1.0 (Reference)

 

 RV

12 (9.1%)

23 (13.5%)

1.41 (0.65, 3.09)

0.389

 RSV + RV

10 (7.6%)

14 (8.2%)

1.03 (0.42, 2.50)

0.947

 RSV+ any other non-RV

13 (9.8%)

17 (10%)

0.96 (0.43, 2.15)

0.926

 RV+ any other non-RSV

12 (9.1%)

10 (5.9%)

0.61 (0.25, 1.53)

0.293

 Others

32 (24.2%)

34 (20%)

0.78 (0.43, 1.42)

0.421

Seasons

 Winter

62 (38.5%)

88 (47.8%)

1.0 (Reference)

 

 Spring

23 (14.3%)

19 (10.3%)

0.58 (0.29, 1.16)

0.124

 Summer

6 (3.7%)

13 (7.1%)

1.53 (0.55, 4.24)

0.417

 Fall

70 (43.5%)

64 (34.8%)

0.64 (0.40, 1.03)

0.066

 LOS ≥ 4 daysa

125 (78.1%)

156 (85.2%)

1.62 (0.93, 2.82)

0.089

 Assisted Ventilationa

4 (2.6%)

24 (13.4%)

5.85 (1.98, 17.3)

0.001

Medical history and physical exam findings

 Cough

158 (98.8%)

181 (98.4%)

0.76 (0.13, 4.63)

0.769

 Wheezing

95 (60.1%)

132 (73.3%)

1.82 (1.15, 2.89)

0.010

 Crepitation

109 (75.7%)

155 (90.6%)

3.11 (1.64, 5.90)

0.001

 Retraction

87 (60.8%)

158 (89.8%)

5.65 (3.13, 10.2)

<0.001

 Fever

118 (75.6%)

135 (76.3%)

1.03 (0.63, 1.71)

0.893

 Apnea

13 (9.3%)

9 (5.6%)

0.58 (0.24, 1.40)

0.224

 Pertussis like symptoms

12 (9.2%)

16 (10.1%)

1.12 (0.51, 2.46)

0.782

 Family history of asthma

59 (52.7%)

81 (58.3%)

1.26 (0.76, 2.07)

0.375

 Maximum temperature (°C)

38.44 ± 0.82

38.56 ± 0.79

1.20 (0.92, 1.56)

0.156

 Maximum respiratory rate (br/m)

57.98 ± 17.17

66.37 ± 7.83

1.09 (1.07, 1.12)

<0.001

 Maximum pulse rate (beat/m)

163.2 ± 19.9

171.9 ± 17.7

1.03 (1.02, 1.04)

<0.001

 O2 saturation (%)

96.91 ± 2.01

96.02 ± 2.64

0.85 (0.77, 0.93)

0.001

LOS Length of stay in hospital, OR odds ratio, CI confidence interval, ICS Initial clinical severity score. aReference category: LOS <4 days; not assisted ventilation. Dichotomous outcome ICS score value 1 to 2 was taken as reference group

Discussion

To our knowledge this is the first comprehensive report on viral aetiology in hospitalised children with bronchiolitis in the State of Qatar. Our study revealed that RSV and RV were the most commonly detected causative agents. This finding is in contrast to a previous report with a small sample size of 56 children with respiratory tract infection (RTI) in Qatar in which hMPV was the most frequently isolated virus [10]. Our findings are, however, in line with a number of large studies conducted in the Middle East and elsewhere [1114]. In Jordanian children of less than 2 years of age, RSV was a major cause of hospitalisation [11]. Other studies conducted in Saudi Arabia and Turkey reported the same [15, 16].

Geographic variations in seasonal activity of the most commonly detected respiratory viruses have been reported in the literature. In temperate countries, RSV peaks during the winter season, but with variation in the tropics. This diversity is mainly attributed to the region’s climate characteristics, i.e. relative humidity, average monthly temperature and rainfall [1719]. In their study, Haynes et al. assessed RSV seasonality in seven countries with diverse climate characteristics and found that RSV onset and peak timings were inconsistent with climate characteristics in all assessed countries apart from Thailand. RSV offset was found to be consistent in Guatemala [20]. Rhinovirus A was detected all year around with high proportion by the onset of summer in Japan but during the fall and spring in Cyprus while Rhinovirus C was mainly detected in the winter but during the fall and spring in Japan and Cyprus, respectively [18, 21].

In this study, RSV exhibited a strong seasonal pattern with peak activity during the fall and summer months, in contrast to RV, which showed minimal circulation during the fall.

In comparison to children with RSV only infections, children infected with RSV in combination with non-RV or RV alone were more likely to have longer LOS. However, we found no significant association between single or multiple infections and disease severity or LOS. The findings are consistent with two large studies conducted in North America and Europe [13, 14], but in contrast with previous reports where RV was associated with shorter LOS [12, 22]. These discrepancies might be related to sample size, study design and variation in host risk factors.

In this study, we noted an association between individual components of the clinical severity score and bronchiolitis outcome after adjusting for clinical and demographic factors. Similar to Ricart et al., McCallum et al. and Weisgerber et al., the data indicate that, in the Qatari community, children’s clinical characteristics are more relevant than the specific infecting viruses in determining the duration of LOS and disease severity [2325].

Detection of the presence of multiple infections has become common in practice although its clinical impact on disease management and predicting outcomes remains unclear [26]. By using RT-PCR to quantify viral load, a number of studies have concluded that RSV genomic load is correlated with disease severity [13, 14]. Similarly, two investigational anti-RSV drugs showed promising results in reducing viral load and clinical disease severity [27, 28].

Some studies have determined severity based on a modified Wood-Downes score or the need for paediatric intensive care unit (PICU) admission [7, 23]. In this study we analysed severity based on a clinical score that allows children’s classification according to respiratory rate, oxygen saturation and physical examination, mirroring the severity of the respiratory burden.

Previous studies have reported males to be more susceptible than females to lower RTIs across different age groups [29]. In this study the percent of males with severe bronchiolitis was as twice as that to females, 70.8 vs. 29.2%. An explanation was suggested two decades ago by Gupta et al. in which the disproportionally narrower peripheral airways in the younger males could be a possible mechanism of the observed difference [30].

Childhood respiratory infection may influence the development of chronic respiratory diseases. In a cohort of 47 Swedish hospitalised infants with RSV-bronchiolitis, asthma was prevalent in 30% of the group when aged 7 years increasing to 37% at the age of 13 [31]. While Jackson et al. noted an increase in asthma risk in children with RSV associated wheezing; RV was associated with a 10-fold increase of asthma [32]. An earlier retrospective study from Qatar noted an increase in recurrent wheezing by 44% in hospitalised infants due to RSV bronchiolitis 2 years after admission compared to 12% in the control group [33]. In the current study, 63% of the admitted children had wheezing of which 51.2% had RSV associated bronchiolitis. Compared to RSV, RV associated bronchiolitis is suggested to occur in older infants, 13 versus 5 months, who present more often with atopic dermatitis and blood eosinophilia [34].

This study has potential limitations. First, it is a retrospective study at a single hospital. Another limitation is that data on concomitant bacterial infection, viral genomic load and palivizumab prophylaxis were not collected.

Conclusions

In summary, RSV was the most common virus identified, followed by RV with peaks during the fall and spring seasons respectively. Our data show that the clinical presentation is more related to the duration of hospital stay and disease severity than the detected viruses.

Conducting a prospective, multi site surveillance of viral bronchiolitis in the warm, desert climate of the Gulf Cooperation Council (GCC) countries will allow for proper timing of preventable measures. Future studies within the GCC countries should investigate the interplay between climate characteristics, population’s factors and the most detectable circulating viruses.

Abbreviations

ADV: 

Adenovirus

CI: 

Confidence interval

CoV-OC43: 

Coronavirus

DCF: 

Data collection form

GCC: 

Gulf cooperation council

HGH: 

Hamad general hospital

hMPV: 

Human metapneumovirus

ICD: 

International classification of disease

IQR: 

Interquartile range

IRB: 

Institutional review board

LOS: 

Length of stay

OR: 

Odds ratio

PCR: 

Polymerase chain reaction

PICU: 

Paediatric intensive care unit

PIV3: 

Parainfluenza virus 3

RSV: 

Respiratory syncytial virus

RTI: 

Respiratory tract infection

RV: 

Rhinovirus

Declarations

Acknowledgements

The authors would like to thank Prem Chandra for his contribution to data analysis. The study was financially supported by Medical Research Centre, Hamad Medical Corporation, Qatar.

Funding

Hamad Medical Corporation-Medical Research Centre, Institutional Review Board (IRB) Number: 12054.

Availability of data and materials

The dataset generated and/or analysed during the current study available from the corresponding author on reasonable request.

Authors’ contributions

IJ conceptualized and supervised study conduction, assisted in quality assurance and guided critical revisions in response to reviewers’ feedback. AAH, FA, MAH and AA performed literature review and data collection. MA interpreted the data and wrote the manuscript. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval and consent to participate

The institutional review board (IRB) at Hamad Medical Corporation (HMC) approved the study. Waiver of the requirement of participants’ informed consent was obtained from the IRB of HMC due to the retrospective nature of the study.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Paediatric Pulmonology Unit, Hamad Medical Corporation
(2)
Icahn School of Medicine at Mount Sinai

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Copyright

© The Author(s). 2017

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