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.

Viral Etiology and Clinical Characteristics of Acute Respiratory Tract Infections in Hospitalized Children in Southern Germany (2014-2018).

Background: Viral acute respiratory tract infections (ARTIs) are a leading cause of hospitalization in infants and young children. Methods: During the winter seasons of 2014-2018, hospitalized children (<18 years) with symptoms of ARTI were prospectively included at the University Hospital Heidelberg, Germany. Nasopharyngeal swabs were obtained for multiplex molecular analysis of 10 groups of respiratory viruses, and clinical data were obtained using a standardized questionnaire. Results: Of 1353 children included in this study, 1142 (84.4%) were positive for ≥1 viral pathogen. Virus monoinfection was detected in 797 (69.8%) children, whereas 345 (30.2%) children had coinfections with 2-4 viral pathogens. Respiratory syncytial virus (RSV), rhinovirus, and influenza virus were the main pathogens detected. RSV-positive children had significantly more often lower ARTIs, including symptoms of severe cough, wheezing, chest indrawing, tachypnea, and pulmonary rales. Hospitalized children aged <6 months represented the largest age group with detection of ≥1 viral pathogen (455/528 [86.2%] children). Coinfection was more frequent in younger children and, particularly for RSV with rhinovirus, significantly associated with more severe respiratory symptoms (P = .01). Conclusions: A better understanding of the etiology of viral ARTIs among hospitalized children plays a key role for future strategies in prevention, control, and treatment of respiratory viral infections.

RSVpredict: An Online Tool to Calculate the Likelihood of Respiratory Syncytial Virus Infection in Children Hospitalized With Acute Respiratory Disease.

BACKGROUND: Respiratory syncytial virus (RSV) is the leading cause of acute lower respiratory tract infection in young children. Early detection of RSV infection can avoid unnecessary diagnostic and therapeutic intervention and is required to prevent the nosocomial spread of RSV infection in pediatric hospitals. We developed a web tool to calculate the probability of RSV infection in children hospitalized with acute respiratory tract infection (ARTI) (RSVpredict). METHODS: During winter seasons 2014/2015 to 2017/2018, 1545 children hospitalized with clinical symptoms of ARTI at the University Hospital Heidelberg/Germany were prospectively included. Medical information was reported on a standardized data sheet, and nasopharyngeal swabs were obtained for multiplex real-time polymerase chain reaction analyses. We applied logistic regression to develop a prediction model and developed a web-based application to predict the individual probability of RSV infection. RESULTS: Duration of clinical symptoms ≥2 days on admission, calendar month of admission, admission for lower respiratory tract infection, the presence of cough and rale and younger age were associated with RSV infection (P < 0.05). Those data were included in the prediction model (RSVpredict, https://web.imbi.uni-heidelberg.de/rsv/). RSVpredict is a web-based application to calculate the risk of RSV infection in children hospitalized with ARTI. The prediction model is based on easily accessible clinical symptoms and predicts the individual probability of RSV infection risk immediately. CONCLUSIONS: Pediatricians might use the RSVpredict to take informed decisions on further diagnostic and therapeutic intervention, including targeted RSV testing in children with relevant RSV infection risk.