A new tool developed by scientists may enable the medical community to cut back on unnecessary antibiotic usage based on a new large prognostic study, and thus help prevent the development of the dreaded “superbug.” Scientists used a point system where they gave one point for each symptom the child was experiencing, and then using it to predict whether the child needed hospitalization for the illness.

Children with respiratory infections were labeled as either the highest, lowest or middle risk of hospitalization, and if antibiotic use can be halved in the low risk group, and increased int he high risk group, it would lead to a 10 percent overall reduction in prescriptions of antibiotics, according to the findings, which were published in the Lancet Respiratory Medicine.

Scientists conducted the study in order to create a simple, usable prediction tool to help identify children that had the lowest and highest risk of future complications and likely hospitalization, allowing them to better target antibiotics. Scientists are worried overuse of antibiotics could lead to the evolution of so-called “superbugs” which are resistant to modern treatment methods, making diseases much harder or even impossible to defeat.

“Antimicrobial resistance is a serious threat to public health, with most antibiotics prescribed in primary care. General practitioners (GPs) report defensive antibiotic prescribing to mitigate perceived risk of future hospital admission in children with respiratory tract infections,” the intro to the paper reads. “We developed a clinical rule aimed to reduce clinical uncertainty by stratifying risk of future hospital admission.

“Clinical characteristics can distinguish children at very low, normal, and high risk of future hospital admission for respiratory tract infection and could be used to reduce antibiotic prescriptions in primary care for children at very low risk,” it adds.