Diarrhea etiology prediction validation dataset - Bangladesh and Mali

Background: Diarrheal illness is a leading cause of antibiotic use for
children in low- and middle-income countries. Determination of diarrhea
etiology at the point-of-care without reliance on laboratory testing has
the potential to reduce inappropriate antibiotic use. Methods: This
prospective observational study aimed to develop and externally validate
the accuracy of a mobile software application (“App”) for the prediction
of viral-only etiology of acute diarrhea in children 0-59 months in
Bangladesh and Mali. The App used previously derived and internally
validated models using combinations of “patient-intrinsic” information
(age, blood in stool, vomiting, breastfeeding status, and mid-upper arm
circumference), pre-test odds using location-specific historical
prevalence and recent patients, climate, and viral seasonality. Diarrhea
etiology was determined with TaqMan Array Card using episode-specific
attributable fraction (AFe) >0.5. Results: Of 302 children with
acute diarrhea enrolled, 199 had etiologies above the AFe threshold.
Viral-only pathogens were detected in 22% of patients in Mali and 63% in
Bangladesh. Rotavirus was the most common pathogen detected (16% Mali; 60%
Bangladesh). The viral seasonality model had an AUC of 0.754 (0.665-0.843)
for the sites combined, with calibration-in-the-large α=-0.393 (-0.455 –
-0.331) and calibration slope β=1.287 (1.207 – 1.367). By site, the
pre-test odds model performed best in Mali with an AUC of 0.783 (0.705 -
0.86); the viral seasonality model performed best in Bangladesh with AUC
0.710 (0.595 - 0.825). Conclusion: The app accurately identified children
with high likelihood of viral-only diarrhea etiology. Further studies to
evaluate the app’s potential use in diagnostic and antimicrobial
stewardship are underway.