Risk prediction models to guide antibiotic prescribing: a study on adult patients with uncomplicated upper respiratory tract infections in an emergency department.

ABSTRACT:

Background

Appropriate antibiotic prescribing is key to combating antimicrobial resistance. Upper respiratory tract infections (URTIs) are common reasons for emergency department (ED) visits and antibiotic use. Differentiating between bacterial and viral infections is not straightforward. We aim to provide an evidence-based clinical decision support tool for antibiotic prescribing using prediction models developed from local data.

Methods

Seven hundred-fifteen patients with uncomplicated URTI were recruited and analysed from Singapore's busiest ED, Tan Tock Seng Hospital, from June 2016 to November 2018. Confirmatory tests were performed using the multiplex polymerase chain reaction (PCR) test for respiratory viruses and point-of-care test for C-reactive protein. Demographic

SUBMITTER: Wong JG 

PROVIDER: S-EPMC7605344 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature