Health Data Help Better Predict RSV Infection Risk in Children
New study identifies children who would 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. This very large study on risk factors for a severe RSV infection, led by researchers from the University of Helsinki and Helsinki University Hospital (HUS), was recently published in Lancet Digital Health. The researchers created a clinical prediction model to predict the risk of hospitalization from an RSV infection and showed that the model performed well in both countries.
The study confirmed that the risk for a severe RSV infection is highest at less than six months of age and that the risk increases if the infant is born premature, has certain congenital conditions, and has young siblings. The new prognostic factors identified include esophageal malformations and a less severe congenital heart disease.
In recent years, both a long-acting anti-RSV antibody and a vaccine given to mothers during pregnancy have been developed to prevent RSV infections. When targeted properly, such drugs can prevent a large number of complications in young children and decrease the number of hospital visits and intensive care stays, but it is not yet clear how widely these approaches should be used.
"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 an MD specializing in pediatrics at HUS.
High disease burden of RSV infections
RSV is a common virus that causes respiratory infections, but it can be dangerous, especially in infants. The disease burden of RSV epidemics is high all over the world. Globally, over 100,000 children die each year because of RSV infections. "RSV causes severe infections, especially in children under one year of age. In Finland, it is one of the most common causes of hospitalization of young children and a major cause of infant mortality worldwide," says Santtu Heinonen, MD, specialist in pediatrics from the HUS New Children's Hospital.
In Finland, 1 in 3 children under one year of age is infected with RSV: Around 1000 of them require hospital treatment for the RSV infection, which is significantly more than that of influenza or coronavirus.
The vast majority of patients acquire the infection during the few peak months of the epidemic. This places a significant burden on the healthcare system and often leads to the cancellation or postponement of procedures such as heart surgery.
Combining several national registries
The team utilized different national registries to investigate the factors that increase the risk of hospitalization for RSV infections in children younger than a year. The study included 1.25 million children born in Finland between 1997 and 2020 and 1.4 million children born in Sweden between 2006 and 2020, and their parents and siblings. The simple 16-variable clinical prediction model created in the study performed equally well as did the 1,511 variable-containing AI-based model.
For creating the prediction model, researchers harmonized the health data 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. There are few countries where such a study can be done," says Andrea Ganna, associate professor at the University of Helsinki, who led the study.
“This study is an example of how nationwide registry-based studies can help to target preventive efforts. The aim of the FinRegistry project is to produce scientific knowledge on risk factors and trajectories leading to various diseases, also those not observable with traditional methods,” says research professor Markus Perola, MD, PhD, from the Finnish Institute for Health and Welfare (THL).
-This press release was originally published on the University of Helsinki website