A new study helps to identify children who are at the highest risk of a severe respiratory syncytial virus (RSV) infection and who would thus benefit most from new RSV prevention measures.
A registry study covering all Finnish and Swedish children and their family members identified 16 major risk factors for a severe RSV infection. The researchers created a clinical prediction model to predict the risk of hospitalisation from an RSV infection and showed that the model performed well in both countries.
"It may not be possible to offer these new preventive measures to all children. Our research helps to identify the children who need them most, both at the individual level and in the population," says the lead author of the study, Pekka Vartiainen, a Postdoctoral Researcher from the Institute for Molecular Medicine Finland FIMM, University of Helsinki, and a MD specialising in paediatrics at HUS.
For creating the prediction model, health data were harmonised and coded for AI use as part of the Finnish FinRegistry study. The resulting model was replicated in the corresponding Swedish registry data."In our study, we applied high-quality data and methodological expertise to solve a clinically important problem. The Nordic countries have exceptionally extensive and reliable registry data.
Risk factors for severe respiratory syncytial virus infection during the first year of life: development and validation of a clinical prediction modelNirsevimab showed 74.5 percent efficacy against medically attended lower respiratory tract infections caused by respiratory syncytial virus in healthy infants, according to an international, ...
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