Value of a risk scoring tool to predict respiratory syncytial virus disease severity and need for hospitalization in term infants

RSV-CLASS -Clinical Assessment Severity Score: An easy-to-use clinical disease severity score for respiratory syncytial virus infection in hospitalized children

Respiratory syncytial virus (RSV) is the most common cause of acute respiratory tract infection in infants and young children often leading to severe disease requiring hospitalization. However, validated tools for systematic assessment of disease severity are lacking. This study aimed at creating and validating a standardized, simple-to-use disease severity score for RSV infection in children-the RSV-CLASS (Clinical Assessment Severity Score). Therefore, data from over 700 RSV-infected children over six winter seasons (2014-2020) was analyzed using univariate and multiple regression analyses for the prediction of lower respiratory tract infection (LRTI) as a proxy for a severe course of the disease. Testing a broad range of respiratory symptoms, they eventually yielded seven items. Performing stepwise selection, these were reduced to the final four items: cough, tachypnea, rales, and wheezing, each receiving one point in the proposed score named RSV-CLASS. The score was calculated for children in two cohorts A and B, one for development and one for validation, with an area under the curve of 0.90 and 0.87, respectively. With a score value of 3 or 4, 97.8% and 100% of the children, respectively, were admitted with LRTI and classified correctly. The RSV-CLASS is a disease severity score based on a neutral, analytical approach using prospective data from a large study cohort. It will contribute to systematically assessing the disease severity of RSV infection and can be used for evidence-based clinical decision-making as well as for research settings.

Machine learning early prediction of respiratory syncytial virus in pediatric hospitalized patients

Respiratory syncytial virus (RSV) causes millions of infections among children in the US each year and can cause severe disease or death. Infections that are not promptly detected can cause outbreaks that put other hospitalized patients at risk. No tools besides diagnostic testing are available to rapidly and reliably predict RSV infections among hospitalized patients. We conducted a retrospective study from pediatric electronic health record (EHR) data and built a machine learning model to predict whether a patient will test positive to RSV by nucleic acid amplification test during their stay. Our model demonstrated excellent discrimination with an area under the receiver-operating curve of 0.919, a sensitivity of 0.802, and specificity of 0.876. Our model can help clinicians identify patients who may have RSV infections rapidly and cost-effectively. Successfully integrating this model into routine pediatric inpatient care may assist efforts in patient care and infection control.

Field testing two existing, standardized respiratory severity scores (LIBSS and ReSViNET) in infants presenting with acute respiratory illness to tertiary hospitals in Rwanda - a validation and inter-rater reliability study

INTRODUCTION

There is a substantial burden of respiratory disease in infants in the sub-Saharan Africa region. Many health care providers (HCPs) that initially receive infants with respiratory distress may not be adequately skilled to differentiate between mild, moderate and severe respiratory symptoms, which may contribute to poor management and outcome. Therefore, respiratory severity scores have the potential to contributing to address this gap.

OBJECTIVES

to field-test the use of two existing standardized bronchiolitis severity scores (LIBSS and ReSViNET) in a population of Rwandan infants (1-12 months) presenting with respiratory illnesses to urban, tertiary, pediatric hospitals and to assess the severity of respiratory distress in these infants and the treatments used.

METHODS

A cross-sectional, validation study, was conducted in four tertiary hospitals in Rwanda. Infants presenting with difficulty in breathing were included. The LIBSS and ReSViNET scores were independently employed by nurses and residents to assess the severity of disease in each infant.

RESULTS

100 infants were recruited with a mean age of seven months. Infants presented with pneumonia (n = 51), bronchiolitis (n = 36) and other infectious respiratory illnesses (n = 13). Thirty-three infants had severe disease and survival was 94% using nurse applied LIBSS. Regarding inter-rater reliability, the intra-class correlation coefficient (ICC) for LIBSS and ReSViNET between nurses and residents was 0.985 (95% CI: 0.98-0.99) and 0.980 (0.97-0.99). The convergent validity (Pearson's correlation) between LIBSS and ReSViNET for nurses and residents was R = 0.836 (p<0.001) and R = 0.815 (p<0.001). The area under the Receiver Operator Curve (aROC) for admission to PICU or HDU was 0.956 (CI: 0.92-0.99, p<0.001) and 0.880 (CI: 0.80-0.96, p<0.001) for nurse completed LIBSS and ReSViNET respectively.

CONCLUSION

LIBSS and ReSViNET were designed for infants with bronchiolitis in resource-rich settings. Both LIBSS and ReSViNET demonstrated good reliability and validity results, in this cohort of patients presenting to tertiary level hospitals. This early data demonstrate that these two scores have the potential to be used in conjunction with clinical reasoning to identify infants at increased risk of clinical deterioration and allow timely admission, treatment escalation and therefore support resource allocation in Rwanda.

Airway gene-expression classifiers for respiratory syncytial virus (RSV) disease severity in infants

Background

A substantial number of infants infected with RSV develop severe symptoms requiring hospitalization. We currently lack accurate biomarkers that are associated with severe illness.

Method

We defined airway gene expression profiles based on RNA sequencing from nasal brush samples from 106 full-tem previously healthy RSV infected subjects during acute infection (day 1–10 of illness) and convalescence stage (day 28 of illness). All subjects were assigned a clinical illness severity score (GRSS). Using AIC-based model selection, we built a sparse linear correlate of GRSS based on 41 genes (NGSS1). We also built an alternate model based upon 13 genes associated with severe infection acutely but displaying stable expression over time (NGSS2).

Results

NGSS1 is strongly correlated with the disease severity, demonstrating a naïve correlation (ρ) of ρ = 0.935 and cross-validated correlation of 0.813. As a binary classifier (mild versus severe), NGSS1 correctly classifies disease severity in 89.6% of the subjects following cross-validation. NGSS2 has slightly less, but comparable, accuracy with a cross-validated correlation of 0.741 and classification accuracy of 84.0%.

Conclusion

Airway gene expression patterns, obtained following a minimally-invasive procedure, have potential utility for development of clinically useful biomarkers that correlate with disease severity in primary RSV infection.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-021-00913-2.

Comparison of Kristjansson Respiratory Score and Wang Respiratory Score in infants with bronchiolitis in a hospital emergency department

Objective

Several respiratory scores have been created to evaluate bronchiolitis' severity level, but it is still not clear which is the best score. The aim of this study is to compare the Wang Respiratory Score (WRS) and the Kristjansson Respiratory Score (KRS) in the setting of an emergency room.

Methods

We performed a prospective observational study with 60 infants with bronchiolitis admitted to a paediatric emergency department. For both scores, we assessed inter-rater reliability between two different health professionals (physician and physiotherapist), internal consistency, and correlation with SpO₂ testing the intraclass-correlation coefficient (ICC), weighted kappa, Cronbach α coefficient and Spearman tests, respectively.

Results

The inter-rater reliability was higher in KRS (ICC 0.79) and the Cronbach α and weighted kappa had similar values in KRS versus WRS. The correlation between the KRS/WRS and SpO₂ was poor/moderate upon admission and discharge for the first observer and the second observer.

Conclusions

While the internal consistency was similar in both scores, inter-rater reliability of KRS was higher than WRS, which allows us to conclude that it would have more consistent results when used to assess bronchiolitis' level of severity by health personnel in a busy hospital emergency room.

Measuring the Severity of Respiratory Illness in the First 2 Years of Life in Preterm and Term Infants

OBJECTIVE

To develop a valid research tool to measure infant respiratory illness severity using parent-reported symptoms.

STUDY DESIGN

Nose and throat swabs were collected monthly for 1 year and during respiratory illnesses for 2 years in a prospective study of term and preterm infants in the Prematurity, Respiratory Outcomes, Immune System and Microbiome study. Viral pathogens were detected using Taqman Array Cards. Parents recorded symptoms during respiratory illnesses using a Childhood Origins of Asthma (COAST) scorecard. The COAST score was validated using linear mixed effects regression modeling to evaluate associations with hospitalization and specific infections. A data-driven method was also used to compute symptom weights and derive a new score, the Infant Research Respiratory Infection Severity Score (IRRISS). Linear mixed effects regression modeling was repeated with the IRRISS illness data.

RESULTS

From April 2013 to April 2017, 50 term, 40 late preterm, and 28 extremely low gestational age (<29 weeks of gestation) infants had 303 respiratory illness visits with viral testing and parent-reported symptoms. A range of illness severity was described with 39% of illness scores suggestive of severe disease. Both the COAST score and IRRISS were associated with respiratory syncytial virus infection and hospitalization. Gestational age and human rhinovirus infection were inversely associated with both scoring systems. The IRRISS and COAST scores were highly correlated (r = 0.93; P < .0001).

CONCLUSIONS

Using parent-reported symptoms, we validated the COAST score as a measure of respiratory illness severity in infants. The new IRRISS score performed as well as the COAST score.

Respiratory syncytial virus associated hospitalizations in preterm infants of 29 to 32 weeks gestational age using a risk score tool for palivizumab prophylaxis

To evaluate the efficacy of palivizumab in infants of 29 to 32 weeks of gestational age (GA) based on a risk score tool developed for Austria. Retrospective single-center cohort study including all preterm infants of 29 (+0) to 32 (+6) weeks of GA born between 2004 and 2012 at a tertiary care university hospital. Data on RSV-related hospitalizations over the first 2 years of life were analyzed and compared between those having received palivizumab and those without. The study population was comprised of 789 of 816 screened infants, of whom 262 (33%) had received palivizumab and 527 (67%) had not. Nine of 107 rehospitalizations (8.4%) in the palivizumab group compared to 32 of 156 rehospitalizations (20.5%) in the group without prophylaxis were tested RSV-positive (p = 0.004; OR 0.356 [CI 90% 0.184-0.689]). Proven and calculated RSV hospitalization rate was 3.1% (8/262) in the palivizumab group and 5.9% (31/527) in the group without (p = 0.042; OR 0.504 [CI 90% 0.259-0.981]). Increasing number of risk factors (up to three) increased the RSV hospitalization rate in infants with (6.1%) and without (9.0%) prophylaxis. RSV-associated hospitalizations did not differ between groups with regard to length of stay, severity of infection, age at hospitalization, demand of supplemental oxygen, need for mechanical ventilation, and admission rate to the ICU. A risk score tool developed for infants of 29 to 32 weeks of gestational age led to a reduction of RSV-associated hospitalizations without influencing the severity of disease.

Influenza and other respiratory viruses: standardizing disease severity in surveillance and clinical trials

INTRODUCTION

Influenza-Like Illness is a leading cause of hospitalization in children. Disease burden due to influenza and other respiratory viral infections is reported on a population level, but clinical scores measuring individual changes in disease severity are urgently needed. Areas covered: We present a composite clinical score allowing individual patient data analyses of disease severity based on systematic literature review and WHO-criteria for uncomplicated and complicated disease. The 22-item ViVI Disease Severity Score showed a normal distribution in a pediatric cohort of 6073 children aged 0-18 years (mean age 3.13; S.D. 3.89; range: 0 to 18.79). Expert commentary: The ViVI Score was correlated with risk of antibiotic use as well as need for hospitalization and intensive care. The ViVI Score was used to track children with influenza, respiratory syncytial virus, human metapneumovirus, human rhinovirus, and adenovirus infections and is fully compliant with regulatory data standards. The ViVI Disease Severity Score mobile application allows physicians to measure disease severity at the point-of care thereby taking clinical trials to the next level.

Development of a Global Respiratory Severity Score for Respiratory Syncytial Virus Infection in Infants

Background

Respiratory syncytial virus (RSV) infection in infants has recognizable clinical signs and symptoms. However, quantification of disease severity is difficult, and published scores remain problematic. Thus, as part of a RSV pathogenesis study, we developed a global respiratory severity score (GRSS) as a research tool for evaluating infants with primary RSV infection.

Methods

Previously healthy infants <10 months of age with RSV infections representing the spectrum of disease severity were prospectively evaluated. Clinical signs and symptoms were collected at 3 time points from hospitalized infants and those seen in ambulatory settings. Data were also extracted from office, emergency department, and hospital records. An unbiased data-driven approach using factor analysis was used to develop a GRSS.

Results

A total of 139 infants (84 hospitalized and 55 nonhospitalized) were enrolled. Using hospitalization status as the output variable, 9 clinical variables were identified and weighted to produce a composite GRSS. The GRSS had an area under the receiver operator curve of 0.961. Construct validity was demonstrated via a significant correlation with length of stay (r = 0.586, P < .0001).

Conclusions

Using routine clinical variables, we developed a severity score for infants with RSV infection that should be useful as an end point for investigation of disease pathogenesis and as an outcome measure for therapeutic interventions.

Risk Factors for Hospitalization for Respiratory Syncytial Virus Infection: A Population-based Cohort Study of Danish Children

BACKGROUND

The aim of this study is to identify the risk factors for hospitalization for respiratory syncytial virus (RSV) infection in Danish children.

METHODS

This is a population-based cohort study with follow-up till 24 months of age. A total of 421,943 Danish children were divided into 5 groups based on gestational age (23-32, 33-35, 36, 37-41 and 42-45 weeks).

RESULTS

In adjusted Cox regression models, chronic disease, asthma hospitalization before the RSV infection and siblings were associated with an increased risk of hospitalization for RSV infection in all children independent of gestational age. Plurality was associated with a decreased risk in children born between 23 and 36 weeks of gestation, whereas young maternal age, maternal asthma, single parenthood, maternal smoking, being born small for gestational age, Caesarian section, male gender and day care were associated with an increased risk of hospitalization for RSV infection in term children. In postterm children, young maternal age, male sex, being born small for gestational age and maternal smoking were associated with an increased risk of hospitalization for RSV. Asthma hospitalization before the RSV infection and siblings were associated with the highest measures of increased risk of hospitalization for RSV infection independent of gestational age.

CONCLUSIONS

By 5 groups of gestational age, we provide estimates of the effects of 12 different factors, which can be regarded as add-on risk factors to those already known to increase the risk of hospitalization for RSV infection. Our study may help clinicians to precisely assess the risk profile in the individual child.

Risk of respiratory syncytial virus infection in preterm infants: reviewing the need for prevention

Premature infants are at substantial risk for a spectrum of morbidities that are gestational age dependent. Respiratory syncytial virus (RSV) infection is most common in the first two years of life with the highest burden in children aged <6 months. Preterm infants ≤35 weeks' gestation are handicapped by incomplete immunological and pulmonary maturation and immature premorbid lung function with the added risk of bronchopulmonary dysplasia. Superimposed RSV infection incites marked neutrophilic airway inflammation and innate immunological responses that further compromise normal airway modeling. This review addresses the epidemiology and burden of RSV disease, focusing on the preterm population. Risk factors that determine RSV-disease severity and hospitalization and the impact on healthcare resource utilization and potential long-term respiratory sequelae are discussed. The importance of disease prevention and the evidence-based rationale for prophylaxis with palivizumab is explored, while awaiting the development of a universal vaccine.