Risk factors for disease severity and increased medical resource utilization in respiratory syncytial virus (+) hospitalized children: A descriptive study conducted in four Belgian hospitals.

BACKGROUND: We aimed to provide regional data on clinical symptoms, medical resource utilization (MRU), and risk factors for increased MRU in hospitalized respiratory syncytial virus (RSV)-infected Belgian pediatric population.
METHODS: This prospective, multicenter study enrolled RSV (+) hospitalized children (aged ≤5y) during the 2013-2015 RSV seasons. RSV was diagnosed within 24h of hospitalization. Disease severity of RSV (+) patients was assessed until discharge or up to maximum six days using a Physical Examination Score (PES) and a derived score based on ability to feed, dyspnea and respiratory effort (PES3). MRU (concomitant medications, length of hospitalization [LOH], and oxygen supplementation) was evaluated. Kaplan-Meier survival analysis was performed to compare MRU by age and presence of risk factors for severe disease. Association between baseline covariates and MRU was analyzed using Cox regression models.
RESULTS: In total, 75 children were included, Median (range) age was 4 (0-41) months, risk factors were present in 18.7%, and early hospitalization (≤3 days of symptom onset) was observed in 57.3% of patients. Cough (100%), feeding problems (82.2%), nasal discharge (87.8%), and rales and rhonchi (82.2%) were frequently observed. Median (range) LOH and oxygen supplementation was 5 (2-7) and 3 (1-7) days. Oxygen supplementation, bronchodilators, and antibiotics were administered to 58.7%, 64.0%, and 41.3% of the patients, respectively. Age <3 months and baseline total PES3 score were associated with probability and the duration of receiving oxygen supplementation. LOH was not associated with any covariate.
CONCLUSION: RSV is associated with high disease burden and MRU in hospitalized children. Oxygen supplementation but not length of hospitalization was associated with very young age and the PES3 score. These results warrant further assessment of the PES3 score as a predictor for the probability of receiving and length of oxygen supplementation in RSV hospitalized children. REGISTRATION: NCT02133092.

Introduction

RSV is a common cause of respiratory tract infection in infants and young children [1], and was estimated to be responsible yearly for at least 33.1 million episodes of acute lower respiratory tract infection worldwide in 2015, resulting in the death of 94,600 to 149,400 children aged <5 years [2]. It has been documented that the clinical presentation of RSV infection in children differs according to age and may be influenced by the differences in their immune reaction to RSV [3]. In a metareview, it was shown that the annual RSV hospitalization rates decreased with increasing age and varied by a factor of 2–3. Risks factors associated with RSV related medical resources utilization included, male sex; age <6 months; birth during the first half of the RSV season; crowding/siblings; and day-care exposure (high strength of evidence) [4].

RSV activity is influenced by meteorological variables such as temperature, humidity, air pressure [5], and geographical latitude [6]. The European Influenza Surveillance Network reported the median RSV peak to be in late January and early February in the Northern hemisphere [6]. However, the pattern is different in Belgium, as RSV infection peaks in young children usually in November or December [1] and around six weeks later in the elderly [7].

Similar to findings from other countries, Cattoir et al. [1] reported the proportion of reverse transcription polymerase chain reaction (RT-PCR) positive samples for RSV to be greater in younger children aged <4 years than those aged >4 years (23% vs. 4%) in Belgium, with infants aged <6 months being affected more than other age groups. A recent systematic review also reported the highest number of RSV-related hospitalizations (>1.4 million) globally among infants aged <6 months [2], and the average annual hospitalization rate for RSV infection in Danish infants aged <6 months was 45.9/1000 [8]. Similar studies in the United Kingdom have shown that infants aged <6 months account for >40% of all RSV-related hospitalizations [9, 10].

Although Belgium is affected by RSV every year [1, 7], local data regarding hospitalization, medical resource utilization (MRU), as well as RSV disease progression for children aged ≤5 years are unavailable. This study aimed to provide evidence on factors associated with length of hospitalization and request for oxygen supplementation in RSV (+) hospitalized Belgian children. Both demographic characteristics (age, presence of underlying risks) and disease severity were considered as potential drivers for MRU.

Methods

Study design

This exploratory, prospective, multicenter study (NCT02133092) enrolled patients from clinical pediatric wards of four Belgian hospitals (one tertiary academic center and three regional hospitals: UZ Leuven, AZ Sint-Jan Brugge–Oostende campus Brugge, AZ Sint-Jan Brugge—Oostende campus Henri Serruys, and Heilig Hart Ziekenhuis Lier) during the 2013–2014 and 2014–2015 RSV epidemic seasons (Study initiated: 17 December 2013 and Study completed: 21 January 2015). Patients were diagnosed as RSV (+) based on a quantitative RT-PCR (qRT-PCR) homemade/in-house test, or a Sofia RSV fluorescent immunoassay (SOFIA® RSV tests, Quidel), whichever was available first, within 24h after hospitalization. Children with a positive RSV test were monitored daily until discharge or for a maximum of six days (Day 2 to Day 7 of hospitalization).

RSV disease severity, peripheral oxygen saturation (SpO2), respiratory rate and heart rate were monitored.

Approval for the study was obtained from the Commissie Medische Ethiek of the Universitaire Ziekenhuizen Leuven (study reference number—S55858).

Study population

Pediatric patients aged ≤5 years with a diagnosis of lower respiratory tract infection (LRTI) as per the hospital’s standard-of-care (SOC) were enrolled if: (a) they were hospitalized for ≤24 hours duration, (b) the legal representative had provided an ethics committee-approved written informed consent and (c) the patient had a confirmed RSV infection.

Assessments

Demographics and clinical characteristics

Age, weight, gender, current breastfeeding status, day care attendance, duration of symptoms, and underlying risk factors were assessed at enrolment. Duration of symptoms prior to enrolment was collected by asking the caregiver the following question “When did the first acute respiratory symptoms appear?”. The following signs and symptoms were considered as first manifestations of the disease: apnea and feeding problems/ reduction of food intake (for neonates) or being irritable, rhinorrhea, nasal congestion, pharyngitis, cough, ear pain (for older children). Underlying conditions i.e., risk factors reported by the parent/guardian were documented, such as asthma/atopy, previous or recurrent wheezing episode, congenital lung disease, congenital heart disease, immunodeficiency, and bronchopulmonary dysplasia and other risks. Prematurity was documented and defined as ≤37 weeks of gestation, however, no information was available regarding the prematurity sub-category.

Disease severity monitoring

RSV disease severity was monitored by recording clinical signs and symptoms every morning. The signs and symptoms were recorded prior to nasal specimen collection. SpO2 was assessed on room air.

The Physical Examination Score (PES) was used to assess the disease progression over time, as reported by clinician. The PES was developed based on the Emboriadou-Garofalo Bronchiolitis Score [11, 12], Pedianet Bronchiolitis Score [13], and DeVincenzo et al.’s method [14]. Items included in the PES were: ability to feed; otitis; cough; nasal discharge; dyspnea; respiratory efforts; and lung sounds (rales, rhonchi, and wheezing). Each parameter was scored on a four-point severity scale (0 = no symptoms to 3 = severe symptoms) for a total score ranging from 0 to 24 (S1 Table in S1 File). A secondary score termed the PES3 score, was also used. The PES3 score was based on main signs/symptoms with major clinical relevance, such as ability to feed, dyspnea and respiratory effort. The sum score of ability to feed, dyspnea and respiratory effort was used for further assessments.

Medical resource utilization

Medical supportive care (mechanical ventilation and supplementary oxygen), concomitant medication, length of hospitalization (LOH, in days), and physician visits for acute respiratory infection (ARI) before hospitalization were documented.

Statistical analysis

Demographic and clinical characteristics were tabulated and analyzed descriptively and graphically. Data were descriptively analyzed per age groups (0–<3 months, 3–<6 months, 6–<12 months, and 12–48 months), duration of symptoms before hospitalization (early presentation: ≤3d and late presentation: >3d–≤5d), and presence of underlying risk factors.

Several analyses were conducted to examine the risk factors associated with LOH, need for and duration of oxygen supplementation. Kaplan-Meier survival analysis was performed to compare LOH and length of oxygen supplementation across age groups and underlying risk factors (log-rank test). Univariate and multivariate logistic regression models were applied to investigate whether covariates impact the dependent variables LOH (categorized as LOH ≤4 days and LOH >4 days) and the need for supplemental oxygen (subject received supplemental oxygen during hospitalization: Yes/No). Univariate and multivariate Cox proportional hazard regression models [15] were implemented on the LOH (in days) and length of oxygen supplementation (in days).

The following, at baseline available, independent variables (covariates) were considered: demographic variables [age, sex], comorbidities [underlying risk], duration of symptoms before hospitalization, signs and symptoms severity [individual PES3 items and total-PES3 score on day 1]. In addition, reception of oxygen supplementation on day 1 (Yes/No) was included as a covariate for the modeling of LOH. Three options were explored to incorporate the PES score on day 1: (1) the total PES score by summing the 8 individual components; (2) scores on the individual components of ability to feed, dyspnea and respiratory effort; and (3) the PES3 score. The results of options (2) and (3) are presented here.

Statistical analyses were performed using SAS software package (version 9.2 for Windows, SAS Institute Inc., Cary, NC, USA) and R software package (R version 3.6.0 for Windows) [16, 17] Baseline characteristics were compared using Wilcoxon rank sum test or chi-square test where applicable. P-values without multiple comparison corrections were reported. All significance tests were 2-sided with a 5% significance level, where applicable.

Results

Baseline characteristics

Seventy-five patients were included in the study. Baseline characteristics were reported for all patients (Table 1) as well as after classifying based on age, symptom duration, and underlying risk (S3 Table in S1 File). Overall, the median (range) age was 4 (0–41) months with more males than females (n = 41/75 [54.7%] vs. n = 34/75 [45.3%]). Majority of patients were infected by RSV-A (n = 68/75 [90.7%]). Underlying risk factors were present in 18.7% of the patients (n = 14/75), with previous or recurrent wheezing (n = 5/75) and congenital heart disease (CHD; n = 4/75) being the most common underlying risk factors. Premature birth (≤37 weeks of gestation) was reported in 20.0% (n = 15/75) of the patients, with a median (range) age of 7 (0–28) months at enrolment. The premature group was elder at the time of hospital admission than the patients without reported prematurity (median [range] age of 3 [0-41] months). Median (range) symptom duration at enrolment was 3.0 (1–5) days, with symptoms being reported for ≤3 days for most patients (n = 43/75 [57.3%]) before being hospitalized.

Table 1

Baseline characteristics and medical resource utilization.

Parameter	All (n = 75)
Age (months, median [range]) a	4.0 (0–41)
Age (months, n [%]) a
0 - <3	28 (37.8)
3 - <6	15 (20.3)
6 - <12	13 (17.6)
12–48	18 (24.3)
Gender (n [%])
Female	34 (45.3)
Male	41 (54.7)
RSV subtype (n [%])
A	68 (90.7)
B	7 (9.3)
Weight at birth (kg, median [range])	3.34 (1.00–4.37)
Baseline weight (kg, median [range])	6.91 (2.68–17.70)
Day care attendance (n [%]) a
Yes	36 (48.6)
No	38 (51.4)
Currently breastfed (n [%])
Yes	27 (36.0)
No	48 (64.0)
Underlying riskb (n [%])
Yes	14 (18.7)
No	61 (81.3)
Premature birth (n [%]) f
Yes	15 (20.0)
No	60 (80.0)
Symptom length (days, median [range])	3.0 (1–5)
Symptom length (days, n [%])
≤3	43 (57.3)
>3	32 (42.7)
Co-medication during study (n [%])
Antibiotics	31 (41.3)
Bronchodilators	48 (64.0)
Corticosteroids	6 (8.0)
Othersc	4 (5.3)
Length of hospital stay (days, median [range]) d	5.0 (2–7)
Oxygen supplementation (n [%])
Yes	44 (58.7)
No	31 (41.3)
Length of oxygen supplementation (days, median [range]) e	3.0 (1–7)
Visited family doctor for ARI before hospitalization (n [%])
Yes	39 (52.0)
No	36 (48.0)

a The sample size for the evaluation was 74 since data was missing for 1 patient.

b Underlying risk includes atopy (n = 2), previous or recurrent wheezing (n = 5), CHD (n = 4), immunodeficiency (n = 1) and others (n = 4).

c One patient received Synagis (older age group, likely immunocompromised and presented early [≤3d]).

d The sample size for this evaluation was 61.

e The sample size for this evaluation was 44.

Prematurity defined as (≤37 weeks of gestation)

Abbreviations: ARI–Acute Respiratory Infection, CHD–Congenital Heart Disease, RSV–Respiratory Syncytial Virus, SD–Standard Deviation

Compared with the patients with early presentation (≤3 days from symptom onset), patients with later presentation (>3 days from symptoms onset) showed a trend for older age (median age 5.5 vs. 2.5 months), less current breastfeeding (28.1% vs 41.9%), and had more premature births (25% vs 16.3%). However, none of these differences were statistically significant. Fewer patients had underlying risk factors in the late intercept group (n = 3/32 [9.4%]) than the early intercept group (n = 11/43 [25.6%], p = 0.138) (S2 Table in S1 File).

Patients with underlying risk factors (n = 14) were older (median [range] age 8.0 [1-32] vs. 3.0 [0-41] months, p = 0.056), were breastfed less (n = 4/14 [28.6%] vs. n = 23/61 [37.7%], p = 0.739), and had a shorter symptom duration at hospitalization (median [range] 2.5 [1-5] vs. 3.0 [1-5] days, p = 0.078) than patients without underlying risk factors (n = 61) (S3 Table in S1 File).

Medical resource utilization

Concomitant medications

Bronchodilators (n = 48/75 [64.0%]) and antibiotics (n = 31/75 [41.3%]) were the most common medications prescribed overall (Table 1) and in all the subgroups (see S3 Table in S1 File). Patients with underlying risk factors received more antibiotics than patients without underlying risk factors (n = 10/14 [71.4%] vs. n = 21/61 [34.4%], p = 0.025; S4 Table in S1 File).

Hospitalization

Overall, the median (range) LOH was 5.0 (2–7) days (Table 1), with small variations between a minimum of 4.0 (2–6) days and a maximum of 6.0 (2–7) days between different groups (S3 Table in S1 File). Overall, 8 patients (10.8%) were hospitalized for >7 days; 5 of these 8 patients were from the youngest age group (<3 months).

Oxygen supplementation

Overall, oxygen supplementation was given to 44/75 (58.7%) of the patients for a median (range) duration of 3.0 (1–7) days (Table 1). The need for oxygen supplementation was highest in the 0–<3 months group (n = 23/28 [82.1%]) for a median (range) duration of 4.0 (1–7) days. Proportion of patients who received oxygen supplementation and the duration of supplementation was similar in patients with symptoms for ≤3 days and >3 days. Underlying risk factors did not result in greater usage of oxygen supplementation (S3 Table in S1 File).

Prior physician visit

Half of the patients (n = 39/75 [52.0%]) visited their family doctor prior to hospitalization (Table 1). Patients aged 3–<6 months (n = 11/18 [61.1%], p = 0.046) and those with symptoms for >3 days (n = 22/32 [68.8%], p = 0.023), visited their physicians the most prior to being hospitalized (S3 Table in S1 File).

Clinical disease kinetics

Patients were mostly afflicted with cough (100%–93. 7%), feeding problems (82.2%–37.5%), nasal discharge (93.2%–81.2%), and rales or rhonchi (84.9%–40.0%) throughout the assessment period (Fig 1). The mean (SE) PES item score on each assessment day as per underlying risk, age, and symptom onset, respectively are illustrated in Fig 2 and S4 and S5 Figs in S1 File. Higher scores (i.e., worse condition) in the ability to feed item were noted for the 3–6 months group (S5 Fig in S1 File). Scores for wheezing, rales and ronchi, dyspnea, respiratory effort, and otitis were higher for patients with underlying risk factors (Fig 2).

Fig 1

PES item frequency over time as per item severity.

Relative frequency of each PES item is expressed as per item severity in all the patients. Item severity is scored from 0 to 3. Patients who were discharged were not considered in the following days’ calculation which could bias the improvement observed over time. Abbreviations: PES–Physical Examination Scoring.

Fig 2

PES item score over time as per underlying risk.

Mean ± SE PES item score is represented at each day of assessment for patients classified based on presence of absence of underlying risk. Patients who were discharged were not considered in the following days’ calculation which could bias the improvement observed over time. Abbreviations: PES–Physical Examination Scoring, SE–Standard Error.

Factors affecting length of hospitalization

The LOH was not statistically different between the age groups (log-rank test, p = 0.320) and by presence of underlying risks (log-rank test, p = 0.884; S6 Fig in S1 File). For the logistic regression assessment, LOH was categorized into: (1) patients with a LOH ≤4d (n = 27), and (2) LOH >4d (n = 45). When baseline covariates were assessed, none of the covariates were observed to significantly influence LOH in both the univariate and multivariate regression models (S7 Table in S1 File). Cox regression analysis showed similar results (S8 Table in S1 File).

Factors affecting oxygen supplementation

Patients aged 0–<3 months received oxygen supplementation for a longer duration than other age groups (log-rank test, p = 0.0016). Duration of oxygen supplementation was not statistically different between patients with and without underlying risk factors (log-rank test, p = 0.084; Fig 3).

Fig 3

Length of oxygen supplementation by age and underlying risk.

Kaplan-Meier curves represent the length of oxygen supplementation for (A) overall patients, (B) patients classified based on age, and (C) patients classified based on underlying risk.

Patients were categorized based on whether they received supplemental oxygen (n = 29) or not (n = 43) during hospitalization. Age significantly affected the probability of receiving supplemental oxygen (p = 0.005; S9 Table in S1 File). Patients in the youngest age category had a higher probability of receiving supplemental oxygen. Furthermore, there was a significant effect of the PES3 score at Day 1 on the probability of receiving supplemental oxygen, with an estimated odds ratio for a 1-unit increase in PES3 score of 1.63 (95% CI 1.19–2.37).

Cox regression analysis showed similar results with a significant effect of age (p = 0.001) and Day 1 PES3 score (p = 0.029) on the length of receiving oxygen supplementation. Patients aged 3–6 months were at a lower risk of receiving oxygen supplementation during hospitalization when compared with patients aged 0–<3 months (hazard ratio [HR] 3.76 (95% CI 1.75–8.11) (Table 2). This corresponds to a 79% chance (HR/[1-HR]) [18] that patients aged 3–6 months have a shorter oxygen supplementation period compared to patients aged 0–<3 months. The HR of the PES3 score was significantly lower than 1 (0.86 [95% CI 0.75–0.99]; p = 0.029), indicating that a higher PES3 score on day 1 was associated with a longer duration of oxygen supplementation.

Table 2

Cox proportional hazard regression analysis for number of days a patient received oxygen supplementation.

Parameter	Multivariate analysis
	HR (95% CI)	p valuea
Age
0–<3 months	-	0.001
3–6 months	3.76 (1.75–8.11)
6–<12 months	2.94 (1.37–6.29)
12–<48 months	3.81 (1.78–8.13)
Gender
Female	-	0.976
Male	1.01 (0.62–1.65)
Underlying risk
No	-	0.202
Yes	1.61 (0.79–3.31)
Length of symptoms at intercept
≤3 days	-	0.389
>3 days	0.78 (0.44–1.37)
PES3-total score (3 items; 1-unit increase)	0.86 (0.75–0.99)	0.029

N = 72, 2 patients were excluded as they did not have PES score on day 1 available. 1 patient was excluded due to missing age.

ap value was calculated by a likelihood ratio test.

A global chi-square test for the proportional hazard assumption showed no deviation (p = 0.447). A graphical review of possible time-dependent coefficients over time (plots of residuals for individual predictors) showed no deviation from the proportional hazard assumption.

Abbreviations: CI–Confidence Interval, HR–Hazard Ratio, PES–Physical Examination Scoring

Discussion

This study describes the disease progression, medical resources utilization and predictors for oxygen supplementation and duration of hospitalization. in RSV (+) children hospitalized with a LRTI. There were no transfers to ICU or mechanical ventilation (although one of the four sites was a tertiary hospital), indicating that the population studied is representative for moderate severity bronchiolitis hospitalizations.

Disease severity was characterized based on clinical evaluation of signs and symptoms covering the full spectrum of LRTIs, as suggested by Karron and Zar [19]. A greater severity of otitis and nasal discharge was observed among older children (>6 months), and greater respiratory effort among younger children (<6 months) over time. We observed a greater severity of dyspnea and greater respiratory effort in neonates (<3 months), whereas Ogra [20] reported that reduction in food intake and apnea were the most severe findings in this age group. The median (range) LOH for the overall patient population was 5.0 (2–7) days. This duration was similar compared with studies in children in France [21], Spain [22], and Japan [23] and longer compared with studies from England [24], the United States [25], and New Zealand [26].

Overall, 41.3% of the patients in the current study were prescribed antibiotics, which is similar to values reported by studies in Israel and the Netherlands (49%) [27]. Canada (60.5%) [28], and Germany (41.7%) [29]. Although patients with severe RSV infection receive antibiotics to treat a possible bacterial superinfection [30], doing so regardless of RSV severity may lead to adverse events and unnecessary financial burden [28] or antibiotic resistance. This finding highlights the overuse of antibiotics for treatment of viral related ARIs and the requirement for appropriate antibiotic stewardship programs [31-33]. We did not collect data on bacterial co-infection; however, we suspect overuse of antibiotics based on the facts that numerous studies have shown that the occurrence of a secondary or concurrent bacterial infection in hospitalized children with RSV lower respiratory tract disease. Nevertheless, frequency of RSV and bacterial co-infection in children is very low [34, 35]. The overuse of antibiotics for treatment of RSV disease has been documented before [27, 33].

The LOH is subjected to various factors (regional and site hospitalizations and discharge guideline, socio-economic reasons, etc.), partially independent of disease severity and therefore hampering the use of LOH as an endpoint for development of pharmaceutical interventions for ARI treatment [36, 37]. The current study did not find any demographic or clinical risk factor to significantly predict LOH. In contrast, in other studies, baseline characteristics such as male sex, lower weight, presence of congenital anomalies, etc. were associated with prolonged hospitalization [38-40]. Differences in study design, sample size, analysis methods and demographics could account for the conflicting data, i.e. younger children and ICU hospitalization were included in the El Saleeby et al. study [41]. Compared with the current study (mean age 3 vs. 8 months and 25% ICU admission vs. no ICU admission).

We did not observe a relationship between the start of oxygen supplementation and LOH, whereas published evidence is conflicting. While Unger et al. [42] and Schroeder et al. [43] reported longer LOH in the presence of oxygen supplementation, a recent study reported that oxygen supplementation could have a variable influence on LOH depending on disease severity [44]. In the current study, young age (<3 months) but not disease severity were associated with greater probability of receiving oxygen as well as with length of oxygen supplementation, consistent with Stollar et al.’s results [45]. However, evidence regarding the association between severity assessment and oxygen supplementation is conflicting [46, 47] possibly due to use of different scoring systems. Our study shows an association between the PES3 score and probability of receiving oxygen and the length of oxygen supplementation. At our knowledge, this is the first time when the ability to feed, dyspnea and respiratory effort are combined in a composite score and predict the use of oxygen supplementation during hospitalization. Such a score, based on critical major signs/symptoms, would be easy to implement in clinical practice.

This study has limitations. Due to practical reasons, only a subset of patients admitted for RSV infections were enrolled in the study, therefore we cannot comment on the generalizability of the results. Most of the children are discharged with ongoing signs/symptoms that may drive additional medical resources utilization after hospital discharge. In this study, the MRUs were not captured after discharge, even though we consider that 7 days is sufficient time for capturing the utilization of medical resources [22, 48]. Since, only the current breastfeeding status was collected, the study was not able to evaluate the potential impact of prior breastfeeding on clinical burden and medical resources utilization during the hospitalization, In addition, the way different sites recruited participants could be different (some sites could have included mainly sicker patients that have a higher probability of receiving supplemental oxygen). We realized that the patients included may not be representative for all RSV related hospitalizations in the participating sites. Since a strict protocol on initiation and discontinuation of oxygen supplementation was not implemented, all participating hospitals followed their in-house protocol, which may vary from each other. The participating hospitals also did not have documented discharge criteria. This difference is a potential factor for bias introduced by site effects. Although not excluded in the protocol, no intensive care cases were included, hence most severe cases were not captured. No information was available on concomitant or secondary bacterial respiratory tract infections. However, the high use of antibiotics (41.3%) in our study may reflect lack of antibiotic stewardship and high suspicion of a concomitant bacterial infection, although bacterial infections are expected to occur with low frequency in RSV (+) hospitalized children. The RSV subtype was determined by first testing the sample for the predominant RSV subtype during the season. Further testing for the non-predominant RSV subtype was performed only when the samples were negative for the predominant subtype. Hence, patients with subtype A/B coinfections were not identified. Finally, the study results reflect MRUs related with the pediatric RSV hospitalization prior to the COVID19 pandemic, whereas the patient management pathway and associated burden during and post-pandemic may be different [49-53].

Conclusion

This exploratory, prospective study provides evidence on disease burden and predictors for increased use of medical resources in hospitalized children. Very young age (<3 months old) and baseline PES3 total score were associated with the probability of receiving and the length of oxygen supplementation, however, none of the factors analyzed were associated with the length of hospitalization. This study emphasizes that the probability and length of oxygen supplementation but not the length of hospitalization could be predicted in hospitalized children.

(ZIP)

Click here for additional data file.

28 Sep 2021

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Brenda M. Morrow, PhD

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Please note that PLOS does not permit references to 'results/data not shown.' Authors should provide the relevant data within the manuscript, the Supporting Information files, or in a public repository. If the data are not a core part of the research study being presented, we ask that authors remove any references to these data

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Comments to the Author

Proesmans et al., report relevant data on risk factors for hospitalization and use of medical resources in children <5 years old in Belgium. The study nevertheless requires reorganization, better consistency and faithful presentation of the dependent and independent variables in the methodology and results sections.

Methodology

L97: In general, it is preferred to describe the following information: (company name, City, State. Country) for company information of the experimental kit used.

L105-106: what was your definition of LRTI?

L99: Is a 2–7-day follow-up long enough to expect to observe factors associated with the length of hospital stay and the use of medical resources?

Authors should clearly group together the potential risk factors for hospitalization and use of medical resources due to HRSV. That is to say socio-demographic factors, signs and symptoms, comorbidities, duration of symptoms before hospitalization, severity (PES, PES3).

The authors must clarify the dependent variables, i.e. hospitalization (length of hospitalization) and use of medical resources (mechanical ventilation, oxygen supplementation, duration of oxygen supplementation, reception of supplementation oxygen on day 1, concomitant medication, doctor's visit for ARI before hospitalization).

L140-143: this part should be presented in data analysis or socio-demographic data.

The authors should explain the orientation of the choice of the Wilcoxon test, chi square test, log rank and logistic regression.

Reviewer #2: Comments to Authors:

The study demonstrates the issue well in disease severity and medical resource utilization of hospitalized RSV-positive children. Overall, this is a well-written manuscript and contributes valuable respiratory data in pediatric clinical practice. The methods are generally appropriate, although authors should clarify a few details and provide a rationale for using analytical methods to measure medical resource utilization parameters.

Introduction

p.9, paragraph 3: Since the authors chose the age as a parameter for medical resource utilization categorized into 0-<3 months, 3-6 months, 6-<12 months, 12-<48 months, readers would want to see background epidemiological data of RSV in these age groups of children.

Methods

Study design

p.11, lines 93-95: Please explain on what grounds these hospitals were selected. Are these hospitals located in RSV endemic areas in the country?

p.11, line 96: Since authors addressed epidemic seasons in the Introduction of the study, the S1 figure is unnecessary. Instead, please add study start and end dates for each respective year.

Study population

p.12, line 105: Please give more specifics of study subjects. Are all pediatric patients included who met inclusion criteria? Readers would want to know why the recruited subjects are only 75 when the RSV detection rate is almost 80% of children under five with severe acute respiratory infection in Belgium generally. (Subissi, L., Bossuyt, N., Reynders, M., Gérard, M., Dauby, N., Bourgeois, M., ... & Barbezange, C. (2020). Capturing respiratory syncytial virus season in Belgium using the influenza severe acute respiratory infection surveillance network, season 2018/19. Eurosurveillance, 25(39), 1900627.)

Demographics and clinical characteristics

p.12, line 118: Did authors consider including re-infection of RSV in underlying conditions?

Medical resource utilization

p.13, line 138: As indications of medical resource utilization might differ depending on the country or context, please specify indications for supplementary oxygen provided for patients involved in the study. Also, authors might need to consider this indication as one of the covariates in the analysis if the practice differs across hospitals. Supplementary oxygen is a highly vulnerable treatment depending on the capacity of the hospitals, especially in developing countries.

Statistical analysis

p.13, line 147 and line 152: Please briefly explain why Kaplan-Meier survival analysis and Cox proportional hazard regression models were performed with distinction. Please indicate all the variables included in each analysis respectively.

p. 14, line 163: Please explain why p-values without multiple comparison corrections were reported.

Results

p. 15, line 170: Readers would want to know why children above 41 months did not take part in the study as inclusion criteria were pediatric patients up to 5 years old.

Table 1

Please clarify breastfeeding? Does it indicate breastfeeding at the point of the data collection?

Clinical disease kinetics

p.19, line 231-233: As shown in Fig 2, the ability to feed and wheezing were mentioned, but how about rales, rhonchi, or others as it appears to be presented more in patients with underlying risk factors too?

Discussion

p.23, paragraph 4: In case authors do not have data on bacterial co-infection, it might look misguiding to state that 41.3% of the patients prescribed with antibiotics highlight overuse of antibiotics. If the authors have more explanation in this regard, please do so. Otherwise, please revise.

p.24, line 330: Please discuss more on the limitation of the study, including potential sources of bias.

Minor comments:

Please correct typos such as:

p. 7, line 45: “PSE3” to “PES3”

p.8, line 59: “score” to “score.”

p.26, line 362: “children” to “children.”

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Amarjargal Dagvadorj

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Submitted filename: Comments to Authors.docx

Click here for additional data file.

11 Jan 2022

Reviewer 1:

We appreciate your thoughtful review of the manuscript and the responses to your comments are provided below

Comment 1: Proesmans et al., report relevant data on risk factors for hospitalization and use of medical resources in children <5 years old in Belgium. The study nevertheless requires reorganization, better consistency, and faithful presentation of the dependent and independent variables in the methodology and results sections.

Response: Based on your comments, we have made the necessary changes and hope the manuscript meets your expectations

Comment 2: Methodology - L97: In general, it is preferred to describe the following information: (company name, City, State. Country) for company information of the experimental kit used.

Response: Either the standard of care quantitative RT-PCR (qRT-PCR) test which concerns a semi-quantitative ISO-accredited LDT (laboratory-developed test)., or a study specific Sofia RSV fluorescent immunoassay (SOFIA®RSV tests, Quidel) were used. The data in the manuscript has been modified to include the details

Comment 3: L105-106: what was your definition of LRTI?

Response: No protocol specific definition of LRTI was provided, the diagnosis of LRTI was done based on clinical decision. In general practice, LRTI clinical diagnosis is based on the presence of symptoms such as: respiratory distress (tachypnea or retraction and/or abnormalities on auscultation).

Comment 4: L99: Is a 2–7-day follow-up long enough to expect to observe factors associated with the length of hospital stay and the use of medical resources?

Response: Yes, we are convinced that in this study the follow-up period of 7 days is sufficient.

(1) All independent variables used in the modelling, on both length of hospital stay and the use of supplemental oxygen, use factors observed at baseline (day 1 in the hospital) namely demographic variables [age, sex], comorbidities [underlying risk], duration of symptoms before hospitalization, signs, and symptoms severity [individual and total PES3] and are thus not influenced by the length of study.

(2) We agree that stopping the follow-up period at day 7 could imply that the actual length of stay is not observed for patients who would be longer hospitalized. In this study, only 8/74 (10.8 %) subjects had a length of stay of longer than 7 days, and thus had a censored length of stay. The applied Cox proportional hazards model accounts for these censored observations.

For modelling of the length of hospital stay, results of the Cox proportional hazards model are now included in the Supplementary Materials Table S8. Results are qualitative similar as results of the logistic regression. This table has been mentioned in the section on ‘Factors affecting length of hospitalization’ in the manuscript.

Comment 5: Authors should clearly group together the potential risk factors for hospitalization and use of medical resources due to HRSV. That is to say socio-demographic factors, signs and symptoms, comorbidities, duration of symptoms before hospitalization, severity (PES, PES3).

Response: We agree with the reviewer. The text in the Statistical Analysis section (Page no 14/ line no 161) has changed to: “The following, at baseline available, independent variables (covariates) were considered: demographic variables [age, sex], comorbidities [underlying risk], duration of symptoms before hospitalization, signs and symptoms severity [individual PES3 items and total-PES3 score on day 1]. In addition, reception of oxygen supplementation on day 1 (Yes/No) was included as a covariate for the modelling of LOH. Three options were explored to incorporate the PES score on day 1: (1) the total PES score by summing the 8 individual components; (2) scores on the individual components of ability to feed, dyspnea and respiratory effort; and (3) the PES3 score. The results of options (2) and (3) are presented here.”

Comment 6: The authors must clarify the dependent variables, i.e. hospitalization (length of hospitalization) and use of medical resources (mechanical ventilation, oxygen supplementation, duration of oxygen supplementation, reception of supplementation oxygen on day 1, concomitant medication, doctor's visit for ARI before hospitalization).

Response: We agree with the reviewer. The text in the Statistical Analysis section (Page 14, line no 155) has been changed to: “Univariate and multivariate logistic regression models were applied to investigate whether covariates impact the dependent variables LOH (categorized as LOH ≤4 days and LOH >4 days) and the need for supplemental oxygen (subject received supplemental oxygen during hospitalization: Yes/No). Univariate and multivariate Cox proportional hazard regression models were implemented on the LOH (in days) and length of oxygen supplementation (in days).”

Comment 7: L140-143: this part should be presented in data analysis or socio-demographic data.

Response: Thanks for the suggestion, the text has now been moved to the Statistical analysis section

Comment 8: The authors should explain the orientation of the choice of the Wilcoxon test, chi square test, log rank and logistic regression.

Response: As mentioned in Statistical analysis section, all significance tests were 2-sided with a 5% significance level, where applicable. The ‘where applicable’ refers to the fact that chi-square test for independence of two categorical variables is always one-sided.

Reviewer 2:

The study demonstrates the issue well in disease severity and medical resource utilization of hospitalized RSV-positive children. Overall, this is a well-written manuscript and contributes valuable respiratory data in pediatric clinical practice. The methods are generally appropriate, although authors should clarify a few details and provide a rationale for using analytical methods to measure medical resource utilization parameters.

Comment 1:

Introduction

p.9, paragraph 3: Since the authors chose the age as a parameter for medical resource utilization categorized into 0-<3 months, 3-6 months, 6-<12 months, 12-<48 months, readers would want to see background epidemiological data of RSV in these age groups of children.

Response: The following text along with the corresponding references has been added in the introduction (Page 9, line no 69):

It has been documented that the clinical presentation of RSV infection in children differs according to age and may be influenced by the differences in their immune reaction to RSV. In a metareview, (Bont L et al., Defining the Epidemiology and Burden of Severe Respiratory Syncytial Virus Infection Among Infants and Children in Western Countries. Infect Dis Ther. 2016 Sep;5(3):271-98.) it was shown that the annual RSV hospitalization rates decreased with increasing age and varied by a factor of 2-3. Risks factors associated with RSV related medical resources utilization included: male sex; age <6 months; birth during the first half of the RSV season; crowding/siblings; and day-care exposure (high strength of evidence).

Comment 2: Methods

Study design

p.11, lines 93-95: Please explain on what grounds these hospitals were selected. Are these hospitals located in RSV endemic areas in the country?

Response: The study had a central site that coordinated the additional sites included. The hospitals were in Flanders, and through their locations allowed a good geographical coverage of the seasonal RSV circulation in that region. The study sites included tertiary academic center/university, large regional and small regional hospitals.

Comment 3: p.11, line 96: Since authors addressed epidemic seasons in the Introduction of the study, the S1 figure is unnecessary. Instead, please add study start and end dates for each respective year.

Response: We have added the study start and end date. The text now reads as:

This exploratory, prospective, multicenter study (NCT02133092) enrolled patients from clinical pediatric wards of four Belgian hospitals (one tertiary academic center and three regional hospitals: UZ Leuven, AZ Sint-Jan Brugge – Oostende campus Brugge, AZ Sint-Jan Brugge - Oostende campus Henri Serruys, and Heilig Hart Ziekenhuis Lier) during the 2013–2014 and 2014–2015 RSV epidemic seasons (Study initiated: 17 December 2013 and Study completed: 21 January 2015)

Comment 4: Study population

p.12, line 105: Please give more specifics of study subjects. Are all pediatric patients included who met inclusion criteria? Readers would want to know why the recruited subjects are only 75 when the RSV detection rate is almost 80% of children under five with severe acute respiratory infection in Belgium generally. (Subissi L, et al. Capturing respiratory syncytial virus season in Belgium using the influenza severe acute respiratory infection surveillance network, season 2018/19. Euro Surveill. 2020 Oct; 25(39): 1900627.)

Response: All pediatric patients included in the study met the inclusion criteria, however, not all patients that met the inclusion criteria were enrolled in the study. Furthermore, the study was not designed to measure RSV positivity rate in all patients hospitalized. The patients were not enrolled during the Weekends and public holidays.

One possible explanation for the difference between the positivity rate found in our research and the Subissi et al 2020 reference, could be different case definitions used for eligibility across the two studies, with any ARI for our study and SARI case definition for the referenced study.

We would like to highlight that in Belgium, similar to other countries, the positivity rate in surveillance data, are between 20-50%, depending on the intensity of RSV circulation, and aligned with our findings. (https://www.tandfonline.com/doi/epub/10.1080/17843286.2018.1492509?needAccess=true)

Comment 5: Demographics and clinical characteristics

p.12, line 118: Did authors consider including re-infection of RSV in underlying conditions?

Response: We have no information on whether the RSV event for which the child was included in the study is a possible re-infection of RSV. Indeed, this would have been valuable information, however, re-infections or prior hospitalization due to RSV were not captured.

Comment 6: Medical resource utilization

p.13, line 138: As indications of medical resource utilization might differ depending on the country or context, please specify indications for supplementary oxygen provided for patients involved in the study. Also, authors might need to consider this indication as one of the covariates in the analysis if the practice differs across hospitals. Supplementary oxygen is a highly vulnerable treatment depending on the capacity of the hospitals, especially in developing countries.

Response: The decision to provide O2 supplementation was done according to the Standard of care. Whereas there was no harmonization on O2 supplementation start and stop decisions, in general, considering that the participating sites were located in the same region /country, they likely had similar local guidelines for O2 supplementation, with 92% SpO2 used as a cut-off to guide hospitalization and request for O2 supplementation.

In this study we had 4 sites with, respectively, 14, 10, 24 and 27 subjects. Proportions of subjects receiving oxygen supplementation differs, markedly, by site with respectively 92.9% (13/14), 20.0% (2/10), 41.7% (10/24) and 70.4% (19/27). Further, it was observed that the site with highest proportions of oxygen supplementation also had the highest proportion of youngest subjects. However, as can be observed from the table below, overall, there is a trend in all sites that mainly the younger patients received supplemental oxygen.

Received oxygen supplementation

All Age,

0 - <3 months Age,

3 - <6 months Age,

6 - <12 months Age,

12 - <48 months

Site 1 (n=14) 13 (92.9 %) 9 / 9 (100 %) 1 / 2 (50.0 %) - 3 / 3 (100 %)

Site 2 (n=10) 2 (20.0 %) 1 / 2 (50.0 %) 0 / 1 (0.0 %) 0 / 2 (0.0 %) 1 / 5 (20.0 %)

Site 3 (n=24) 10 (41.7 %) 4 / 6 (66.7 %) 3 / 6 (50.0 %) 1 / 4 (25.0 %) 2 / 8 (25.0 %)

Site 4 (n=27) 19 (70.4 %) 9 / 11 (81.2 %) 3 / 6 (50.0 %) 6 / 7 (85.7 %) 1 / 2 (50.0 %)

Based on clinical input that an association exists between age and receiving supplemental oxygen and the results in the table above, it was decided not to include site as a covariate in the statistical models. Including site as a covariate could possibly dilute the effect of age. In addition, the manner the different sites recruited participants could be different (some sites could have included mainly sicker patients that have a higher probability of receiving supplemental oxygen). This difference is a potential factor for bias when site would be included as a covariate in the modelling.

This was also added to the Discussion section of the manuscript (see also below on the comment on potential sources of bias raised by the reviewer).

Comment 7: Statistical analysis

p.13, line 147 and line 152: Please briefly explain why Kaplan-Meier survival analysis and Cox proportional hazard regression models were performed with distinction. Please indicate all the variables included in each analysis respectively.

Response: Kaplan-Meier analysis can only be used for univariate analysis (thus one covariate at a time). Whereas the Cox proportional hazard regression model can incorporate multiple variables at the same moment.

We adjusted the Statistical Analysis section such that it is more clearly presented which variables are included in each analysis: “Univariate and multivariate logistic regression models were applied to investigate whether covariates impact the dependent variables LOH (categorized as LOH ≤4 days and LOH >4 days) and the need for supplemental oxygen (subject received supplemental oxygen during hospitalization: Yes/No). Univariate and multivariate Cox proportional hazard regression models were implemented on the LOH (in days) and length of oxygen supplementation (in days).

The following, at baseline available, independent variables (covariates) were considered: demographic variables [age, sex], comorbidities [underlying risk], duration of symptoms before hospitalization, signs and symptoms severity [individual PES3 items and total-PES3 score on day 1]. In addition, reception of oxygen supplementation on day 1 (Yes/No) was included as a covariate for the modelling of LOH. Three options were explored to incorporate the PES score on day 1: (1) the total PES score by summing the 8 individual components; (2) scores on the individual components of ability to feed, dyspnea and respiratory effort; and (3) the PES3 score. The results of options (2) and (3) are presented here.”

Comment 8: p. 14, line 163: Please explain why p-values without multiple comparison corrections were reported.

Response: It is common practice that multiple testing correction is not applied to multiple linear regression. We want to point to the following publication on multiple comparison [‘Adjust for Multiple Comparisons? It’s Not That Simple’ by A. Althouse, doi: https://doi.org/10. 1016/j.athoracsur.2015.11.024]. In our and the author’s opinion, the best approach is simply to (1) describe what was done in a study; (2) report point estimates, confidence intervals, and p-values; and (3) let readers use their own judgment about the relative weight of the conclusions. The author and others argue that because adjustment for multiple comparisons has several practical considerations that make the concept unreasonable to apply to every research paper, and particularly not to exploratory studies.

In confirmatory studies, which may lead to a change in clinical practice or approval of a new treatment, it is more important to guard against the possibility of false-positive results. When it comes to exploratory studies or post-hoc analysis of existing data, though, a strict adjustment for multiple comparisons is less critical, as long as the manuscript contains a clear statement acknowledging that.

Comment 9: Results: p. 15, line 170: Readers would want to know why children above 41 months did not take part in the study as inclusion criteria were pediatric patients up to 5 years old.

Response: Although the inclusion criteria were open to 5-year-old, most of the patients hospitalized were <1 year old; 41 months was the maximum observed age in the study. This is in alignment with what has been published in the field, with RSV burden of hospitalization been reported mainly in the very young children.

Comment 11: Table 1: Please clarify breastfeeding. Does it indicate breastfeeding at the point of the data collection?

Response: Yes, this was breastfeeding status at enrollment

Comment 12: Clinical disease kinetics

p.19, line 231-233: As shown in Fig 2, the ability to feed and wheezing were mentioned, but how about rales, rhonchi, or others as it appears to be presented more in patients with underlying risk factors too?

Response: Thank you for the suggestion, changes in rales and rochis and others have now been highlighted as well. Corresponding change in the text is as below

Higher scores i.e., worse condition in the ability to feed item for the 3–6 months group, wheezing; changes in rales and rochi, dyspnea, respiratory effort, and otitis for patients with underlying risk factors show that certain functions were affected more in certain groups.

Comment 13: Discussion

p.23, paragraph 4: In case authors do not have data on bacterial co-infection, it might look misguiding to state that 41.3% of the patients prescribed with antibiotics highlight overuse of antibiotics. If the authors have more explanation in this regard, please do so. Otherwise, please revise.

Response: - No data on bacterial co-infection was available. However, we based our statement on the following considerations:

• The frequency of RSV and bacterial co-infection in children is relatively low. Numerous studies have shown that the occurrence of a secondary or concurrent bacterial infection in hospitalized children with RSV lower respiratory tract disease is <1% (https://adc.bmj.com/content/89/4/363?ijkey=04c663ca8ef80c49237de729d2677f9842cca96f&keytype2=tf_ipsecsha)

• The over-use of antibiotics for treatment of RSV disease was highly documented in the field.

- Reducing Antibiotic Use in Respiratory Syncytial Virus-A Quality Improvement Approach to Antimicrobial Stewardship - PubMed (nih.gov)

- Antibiotic Overuse in Children with Respiratory Syncytial Virus Lower Respiratory Tract Infection - PubMed (nih.gov)

However, the following change in text (Page 23, line no 320) is made, to acknowledge the absence of bacterial co-infection data:

We did not collect data on bacterial co-infection; however, we suspect overuse of antibiotics based on the facts that numerous studies have shown that the occurrence of a secondary or concurrent bacterial infection in hospitalized children with RSV lower respiratory tract disease Nevertheless, frequency of RSV and bacterial co-infection in children is very low. The overuse of antibiotics for treatment of RSV disease has been documented before.

Comment 14: p.24, line 330: Please discuss more on the limitation of the study, including potential sources of bias.

Response: We have modified the limitations to identify the potential sources of bias. The limitations paragraph now reads as below:

Due to practical reasons, only a subset of patients admitted for RSV infections were enrolled in the study, therefore we cannot comment on the generalizability of the results. In addition, the way different sites recruited participants could be different (some sites could have included mainly sicker patients that have a higher probability of receiving supplemental oxygen). We realized that the patients included may not be representative for all RSV related hospitalizations in the participating sites. Since a strict protocol on initiation and discontinuation of oxygen supplementation was not implemented, all participating hospitals followed their in-house protocol, which may vary from each other. The participating hospitals also did not have documented discharge criteria. This difference is a potential factor for bias introduced by site effects. Although not excluded in the protocol, no intensive care cases were included, hence most severe cases were not captured.

Comment 15: Minor comments:

Please correct typos such as:

p. 7, line 45: “PSE3” to “PES3”

p.8, line 59: “score” to “score.”

p.26, line 362: “children” to “children.”

Response: Thanks for noting. We have now corrected the typos.

Submitted filename: Response to Reviewers_PONE-D-21-25349.docx

Click here for additional data file.

25 Feb 2022

31 Mar 2022

Reviewer #1: Comments to the Author

Thanks to the authors for responding to the questions raised. There are, however, the questions below that I would like further clarification.

Methodology

L97: In general, it is preferred to describe the following information: (company name, City, State. Country) for company information of the experimental kit used.

Thank you for modifying the document in accordance with the comment above. However, it will be better to also specify in the main manuscript that the qRT-PCR assay was homemade.

Response: Thank you for your suggestion, we have specified that qRT-PCR assay was homemade in the manuscript.

L99: Is a 2–7-day follow-up long enough to expect to observe factors associated with the length of hospital stay and the use of medical resources?

Thank you for providing the explanations in the letter in relation to the comment above. You affirm that you are convinced that 7 days is long enough to observe all the outcomes of the use of health resources. It would be greatly appreciated if you provide a reference that supports your statement. Also, the explanation that 8/74 participants had more than 7 days in hospital would be important to mention in the main manuscript.

Response: Thank you for your suggestion, we already have this statement in the result section of the manuscript (L225, hospitalization paragraph of result section). We have now added the additional explanation along with the references that would support the length of hospital stay we used in this study.

1) The objective of the study was to describe clinical and medical burden during the hospitalization. However, most of the children are discharged with ongoing signs/symptoms that may drive additional medical resources utilization after hospital discharge. Due to the study design, we could not capture the MRUs after discharge, this being another limitation of the study. We have included this in the discussion section

2) We consider that 7 days follow-up is sufficient to monitor the use of hospital health resources in the enrolled population, besides only 8/74 participants enrolled were hospitalized for more than 7 days. We have also included some literature in the discussion section to support the length of the hospital stay observed in our study,[median of 5.0 days (2–7) d CI], which is similar to the length of hospitalization observed in a Belgium study (LOH: median 5 days, 3-11 CI) (Subissi et al., Euro Surveill. 2020 Oct 1; 25(39): 1900627) and in Spain (LOH: mean 4.8 +/- 11d) (Viguria et al., PLoS One. 2018 Nov 15;13(11):e0206474)

3) The logistic regression analysis on the probability of hospitalization length (LOH ≤ 4 days, LOH > 4 days) and probability of requiring oxygen supplementation, as well as the Cox regression models on the length of hospitalization and length of oxygen supplementation only have baseline covariates included. Thus, the included covariates are independent on the length of follow-up of the patients. The applied Cox proportional hazards model account for censored observations, and thus all available information of the 8 patients with more than 7 days of hospitalizations is included.

Reviewer #2: The authors have clarified all of the questions I raised in my previous review except one problem.

Also, the two copies of the manuscript provided were somewhat different. I would suggest using a file named “Observe001_MSS_Resubmission version_clean copy” instead of a file named “Observe001_MSS_PLOS ONE” as the latter does not seem to reflect all the revisions made.

In general, the paper appears to be worthwhile, and I would accept after addressing the following issue:

Response: Thank you for your suggestion and accepting the paper, we have renamed the file to, ‘Observe001_MSS_Resubmission version_clean copy’ as suggested. We have also verified and checked if the current version reflects all the revisions, and we are able to see the revisions.

Table 1: Please add and revise the appropriate term for the “breastfeeding” variable. Although the authors stated that the variable shows breastfeeding status at enrolment, how about older children who had stopped breastfeeding as your study subjects are up to 41 months old? If you marked them as “no” in the breastfeeding variable, that would be a major concern. Showing the breastfeeding duration is vital as a sufficient breastfeeding period can provide a long-term protective effect against respiratory tract infections. Authors might also need to include breastfeeding as one of the independent variables in multivariate analysis. Because it is well reported that breastfeeding is significant in reducing the rate of severe RSV infection cases. (Please refer to https://www.thelancet.com/series/breastfeeding)

Response: Thank you for suggestion and valuable input regarding the breastfeeding being significant in reducing the rate of severe RSV infection cases.

We have changed the term to ‘currently breastfed’ in the manuscript. Unfortunately, we don’t have information on breastfeeding status or length in the past. We added in the discussion that it is a limitation that we cannot study the possible long-term protective effect of breastfeeding on hospitalization characteristics.

The relevant literature published in this field assessed breastfeeding as a risk factor for progression to hospitalization. However, studies that assessed breastfeeding as a risk factor for severity of disease and length of hospitalization and MRU during hospitalization are limited. Below are some relevant references

1) This study suggests that there was not a significant association between breastfeeding and bronchiolitis severity score or length of hospital stay (Vereen S, Gebretsadik T, Hartert TV et al., Pediatr Infect Dis J. 2014 Sep;33(9):986-8).

2) This article states breastfeeding (<2months or not) was a predictor of progression to hospitalization (Blanken MO, Koffijberg H, Nibbelke EE et al., PLoS One. 2013;8(3):e59161)

3) In a meta-analysis, breastfeeding was observed to be associated with RSV ALRI. However, the definition used for breastfeeding in the reviewed articles was different - No breastfeeding = [no breastfeeding for first 14 days, <3 months breastfeeding or lack of exclusive breastfeeding] (Shi T, Balsells E, Wastnedge E, Singleton R et al., J Glob Health. 2015 Dec;5(2):020416)

Current breastfeeding status (yes/no) is associated with age (see Table S3) with higher proportions of currently being breastfed in the youngest age group.

A Kaplan-Meier analysis showed no differences between current breastfeeding status and length of hospital stay (p=0.55). We also included current breastfeeding status as one of the independent variables in both a univariate and the multivariate regression analyses for length of hospital stay. Current breastfeeding status showed no differences in these regression models.

In our study, patients with current breastfeeding have a longer length of oxygen supplementation (Kaplan-Meier analysis, p=0.046). This result, however, is confounded with age. A univariate logistic regression analysis for the probability of receiving oxygen supplementation shows a significant effect of breastfeeding status. Patients receiving currently breastfeeding have a higher probability of receiving oxygen with OR=3.33 [1.18 – 10.51]. However, in a multivariate logistic regression (and thus corrected for age) no effect is observed anymore of current breastfeeding status (OR = 0.73 [0.15 – 3.40]). Similarly, in the multivariate Cox regression model no significant effect of breastfeeding status is observed (HR = 1.19 [0.64 – 2.22]).

Submitted filename: Response to Reviewers v2._PONE-D-21-25349_24Mar22.docx

Click here for additional data file.

3 May 2022

Risk factors for disease severity and increased medical resource utilization in respiratory syncytial virus (+) hospitalized children: a descriptive study conducted in four Belgian hospitals

PONE-D-21-25349R2

Dear Dr. Ispas,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Brenda M. Morrow, PhD

Academic Editor

PLOS ONE

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I enjoyed reviewing this relevant manuscript on risk factors for hospitalization and use of medical resources in children. Thank you for the invitation to review. Regards.

Reviewer #2: The authors revised the article well as per my suggestions. This work contributes towards further improvement of treatment for young children with RSV infection.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Amarjargal Dagvadorj

26 May 2022

PONE-D-21-25349R2

Risk factors for disease severity and increased medical resource utilization in respiratory syncytial virus (+) hospitalized children: a descriptive study conducted in four Belgian hospitals

Dear Dr. Ispas:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Professor Brenda M. Morrow

Academic Editor

PLOS ONE