Antibiotic prescribing practices for acute respiratory illness in children less than 24 months of age in Kenema, Sierra Leone: is it time to move beyond algorithm driven decision making?

Abstract

Abstract Background Lower respiratory tract infections are the leading cause of mortality in young children globally. In many resource-limited settings clinicians rely on guidelines such as IMCI or ETAT + that promote empiric antibiotic utilization for management of acute respiratory illness (ARI). Numerous evaluations of both guidelines have shown an overall positive response however, several challenges have also been reported, including the potential for over-prescribing of unnecessary antibiotics. The aims of this study were to describe the antibiotic prescribing practices for children less than 24 months of age with symptoms of ARI, that were admitted to Kenema Government Hospital (KGH) in the Eastern Province of Sierra Leone, and to identify the number of children empirically prescribed antibiotics who were admitted to hospital with ARI, as well as their clinical signs, symptoms, and outcomes. Methods We conducted a prospective study of children < 24 months of age admitted to the KGH pediatric ward with respiratory symptoms between October 1, 2020 and May 31, 2022. Study nurses collected data on demographic information, medical and medication history, and information on clinical course while hospitalized. Results A total of 777 children were enrolled. Prior to arrival at the hospital, 224 children (28.8%) reported taking an antibiotic for this illness without improvement. Only 15 (1.9%) children received a chest radiograph to aid in diagnosis and 100% of patients were placed on antibiotics during their hospital stay. Conclusions Despite the lives saved, reliance on clinical decision-support tools such as IMCI and ETAT + for pediatric ARI, is resulting in the likely over-prescribing of antibiotics. Greater uptake of implementation research is needed to develop strategies and tools designed to optimize antibiotic use for ARI in LMIC settings. Additionally, much greater priority needs to be given to ensuring clinicians have the basic tools for clinical diagnosis, as well as greater investments in essential laboratory and radiographic diagnostics that help LMIC clinicians move beyond the sole reliance on algorithm based clinical decision making.