For clinicians using a smartphone-based clinical decision support tool, incorporating an algorithm to estimate the likelihood that diarrhea is due to a viral cause failed to reduce antibiotic prescribing, it found. a randomized crossover trial conducted in Mali and Bangladesh.
In the study of more than 900 children with acute diarrhea, there was no significant difference in the proportion of children who received antibiotics when physicians used the algorithm versus when they did not (69.8% vs. 76.5%; risk difference [RD] -4.2%, 95% CI -10.7 to 1.0), reported Eric Nelson, MD, PhD, of the University of Florida in Gainesville, and colleagues in JAMA Pediatrics.
However, a post hoc analysis evaluating antibiotic prescription when the diarrheal aetiology prediction algorithm (DEP) pointed to viral aetiology showed a potential benefit (RD -5.6%, 95% CI -12, 8 to -10). A 14% drop in the probability of antibiotic prescription was observed for the DEP group for each 10% increase in the predicted probability of viral diarrhea (OR 0.86, 95% CI: 0.76-0.96) .
“If replicated, the use of etiologic prediction in decision support tools represents an important advance to improve antibiotic stewardship in a clinical setting prone to high rates of inappropriate antibiotic use,” the researchers concluded.
Overuse of antibiotics can lead to antimicrobial resistance and put children at risk for adverse events, Nelson’s group noted. But many children in low-income countries are exposed to antibiotics for viral diarrhea despite World Health Organization recommendations that antibiotic use should be reserved for cases of pediatric diarrhea involving suspected cholera or bloody diarrhea .
The researchers had previously developed the DEP algorithm to predict the aetiology of diarrhea based on statistical models from a large multicenter pediatric diarrhea study. “DEP is based on data from the patient’s clinical history and symptoms (patient-specific sources) and location-specific sources, such as clinical presentation of previous patients, historical prevalence, and meteorological parameters,” they explained.
For their study, Nelson and colleagues recruited 30 doctors who treated 941 children with diarrhea at three centers in Bangladesh (from November 2020 to January 2021) and four centers in Mali (from January to March 2021).
Physicians were randomized to treat their patients with the smartphone-based clinical decision support tool alone or with DEP for 4 weeks. After 4 weeks, clinicians underwent a 1-week washout period, followed by a subsequent 4-week crossover period.
In explaining why the primary outcome was not met, the researchers suggested that the trial may have been underpowered. They also noted findings that suggested “older physicians were less willing to change [prescribing] behavior based on expectations [DEP] worth.”
Pediatric participants (median age 12 months, 57% boys) were blinded to the intervention. To be eligible, patients had to be between 2 and 59 months of age, have acute diarrhea (at least 3 stools in 24 hours), and have access to a cell phone for follow-up. Children with severe sepsis, pneumonia, meningitis, malnutrition, or conditions other than gastroenteritis were excluded.
Nearly all children in the study achieved resolution of diarrhea by 10 days after discharge, with similar rates between the DEP (97.9%) and non-DEP (98.6%) groups. On average, it took 2 to 3 days for diarrhea symptoms to go away.
Severe dehydration rates were higher among participants in Bangladesh than in Mali (11.1% vs. 0.22%). Overall, one patient in each group (PED or no PED) died after discharge. Adverse events and serious adverse effects were rare in the two groups.
The authors acknowledged the limitations of the data, including the small number of clinicians, the lack of blinding among clinicians, and that diagnostic stool tests were not performed.
The study was supported by the Bill and Melinda Gates Foundation, the University of Utah Population Health Research Foundation, and the NIH.
Nelson disclosed NIH funding. Coauthors reported funding from AstraZeneca, the Bill and Melinda Gates Foundation, the National Kidney Foundation, NIH, Prometic Life Sciences, the University of Utah, and Value Analytics Labs.