HealthDay News — According to a research study published in The Lancet Respiratory Medicine, scientists have discovered a new decision-making tool that doctors may use to help reduce the use of antibiotics in children with respiratory tract infections and cough.
Using information from 8,394 children, the investigators identified 7 key predictors that could be used to help determine whether a child with a respiratory tract infection and cough is likely to require antibiotics.
Those predictors are: short illness (less than 3 days); fever of 100 degrees Fahrenheit or higher; younger than 2 years old; respiratory distress; wheeze; asthma; and moderate/severe vomiting in the previous 24 hours. Children with none, or just 1, of these predictors are at very low risk of future complications, the researchers said.
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The decision-tool “could reduce clinical uncertainty, and thereby antibiotic use, in children at very low risk of future hospital admission who form the majority of children presenting to primary care with acute respiratory tract infection and cough,” the authors write. “If antibiotic prescription in this group halved, remained static in the normal-risk stratum, and increased to 90% in the high-risk stratum, a 10% overall reduction in antibiotic prescribing would be achieved, similar to other contemporary antimicrobial stewardship interventions.”
One author disclosed financial ties to Nanosphere, Hologic, and Sanofi Pasteur.
References
Hay AD, Redmond NM, Turnbull S, Christensen H, Thornton H, Little P, Thompson M, Delaney B, Lovering AM, Muir P, Leeming JP, Vipond B, Stuart B, Peters TJ, Blair PS. Development and internal validation of a clinical rule to improve antibiotic use in children presenting to primary care with acute respiratory tract infection and cough: a prognostic cohort study. Lancet Respir Med. 2016 Sept 1. doi: 10.1016/S2213-2600(16)30223-5. [Epub ahead of print]
Winchester CC, Chisholm A, Price D. A practical tool for primary care antimicrobial stewardship in children. Lancet Respir Med. 2016 Sept 1. doi: 10.1016/S2213-2600(16)30272-7. [Epub ahead of print]
