External Validation of the Discriminative Validity of the ReSVinet Score and Development of Simplified ReSVinet Scores in Secondary Care

Abstract

Background. There is no consensus on how to best quantify disease severity in infants with respiratory syncytial virus (RSV) and/or bronchiolitis; this lack of a sufficiently validated score complicates the provision of clinical care and, the evaluation of trials of therapeutics and vaccines. The ReSVinet score appears to be one of the most promising; however, it is too time consuming to be incorporated into routine clinical care. We aimed to develop and externally validate simplified versions of this score. Methods. Data from a multinational (the Netherlands, Spain, and United Kingdom) multicenter case-control study of infants with RSV were used to develop simplified versions of the ReSVinet score by conducting a grid search to determine the best combination of equally weighted parameters to maximize for the discriminative ability (measured by area under the receiver operating characteristic curve [AUROC]) across a range of outcomes (hospitalization, intensive care unit admission, ventilation requirement). Subsequently discriminative validity of the score for a range of secondary care outcomes was externally validated by secondary analysis of datasets from Rwanda and Colombia. Results. Three candidate simplified scores were identified using the development dataset; they were excellent (AUROC >0.9) at discriminating for a range of outcomes, and their performance was not significantly different from the original ReSVinet score despite having fewer parameters. In the external validation datasets, the simplified scores were moderate to excellent (AUROC, 0.7–1) across a range of outcomes. In all outcomes, except in a single dataset for predicting admission to the high-dependency unit, they performed at least as well as the original ReSVinet score. Conclusions. The candidate simplified scores developed require further external validation in larger datasets, ideally from resource-limited settings before any recommendation regarding their use.