Diagnostic Tool May Reduce Drug Resistance

     (CN) — A new tool could help doctors prescribe antibiotics for children more efficiently, slowing down bacteria’s ability to adapt to antibiotics and rendering the medicines useless.
     In a study published Thursday in the journal The Lancet, researchers presented their findings after analyzing notes on 8,400 children between the ages of three months and 16 years who were seen at 247 general practitioner offices across England.
     Doctors tend to overprescribe antibiotics for children since it’s difficult to determine whether a child is at risk for developing more severe symptoms or issues.
     Using the data, the team determined the most important factors in evaluating the need for antibiotics among the 50 demographic characteristics reported by parents, or found and recorded during physical examinations.
     The researchers highlighted seven factors that put a child at greater risk of hospitalization within 30 days of seeing a general practitioner for respiratory tract infections with cough — the most common reason for prescribing antibiotics to children.
     “Excessive antibiotic use has contributed to the development of resistance to these drugs,” said lead author Alastair Hay. “The aim of our study was to develop a simple, usable prediction tool based on symptoms and signs to help general practitioners and nurses identify children presenting in primary care at the lowest and highest risk of future complications and hospitalization, so that antibiotics can be targeted accordingly.”
     The proposed tool, called STARWAVe, attempts to measure the most significant risk factors including: short illness of less than three days; temperature; age under two years; recession of respiratory distress signs; wheeze; asthma; and vomiting.
     The name STARWAVe is a mnemonic of the characteristics the tool takes into consideration.
     Hay’s team developed the seven-item scoring system to help doctors determine a child’s risk of future hospitalization, which suggests children displaying none or just one of the characteristics have a very low risk — 0.3 percent chance — of hospitalization. Children with two to three of the characteristics would be at normal or moderate risk, 1.5 percent, while those with four or more of the characteristics would be high-risk candidates for future hospitalization with an 11.8 percent chance.
     “This is the first study of its kind, based on a large representative model sample of children who visit the doctor with respiratory illness,” Hay said. “We hope that our proposed clinical tool might eventually enable doctors to quickly and easily identify their lowest and highest risk patients, although more research will be needed to determine just how effective it is in clinical practice.”
     The authors estimate that if antibiotic prescribing for children with low risk of hospitalization, as determined by STARWAVe scoring, were cut in half, and prescriptions of antibiotics for children at high risk of hospitalization were increased to 90 percent, there would be still be a 10 percent reduction in antibiotic prescriptions overall.
     In a linked comment, David Price, a doctor at Britain’s University of Aberdeen in underscored the findings, which he hopes will be supplemented with additional research to validate the tool’s efficacy.
     “Notwithstanding the inclusion of patients prescribed an antibiotic and the absence of an independent validation cohort, STARWAVe promises to achieve better targeting and antibiotics in primary care,” he said. “STARWAVe offers primary care clinicians an evidence-based practical tool to help guide antibiotic prescribing decisions.”

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