A novel mobile phone application for infant stool color recognition: An easy and effective tool to identify acholic stools in newborns.

Abstract

Early diagnosis of biliary atresia is essential to improve long-term outcomes. Newborn screening with an infant stool color card allows early recognition of biliary atresia patients. Our aim was to develop and validate a mobile phone application (PopòApp) able to identify acholic stools. An intuitive app was developed for iOS and Android smartphones. A learning machine process was used to generate an algorithm for stools color recognition based on the seven colors of the infant stool color card, which were considered as the gold standard. Consecutive images of stools were taken by the PopòApp, directly into the diapers of children aged ≤6 months. The PopòApp classified the photographs as "normal", "acholic" or "uncertain". To validate the PopòApp, four doctors independently classified all images, and only those for which all doctors agreed were included. The sensitivity, specificity, positive/negative predictive values, and accuracy of the PopòApp were evaluated. Of 165 images collected, 160 were included in the study. All acholic stools were recognized by the PopòApp. The PopòApp sensitivity was 100% (95% CI:93.9%-100%) with no false negatives, regardless of the brand of phone. The specificity was 99.0% (95% CI:94.6%-99.9%). The accurancy of the PopòApp was 99.4% (95% CI:96.6%-99.9%), with a positive predictive value of 98.4% (95% CI:89.8%-99.8%). The current study proved, in a large cohort, that the PopòApp is an accurate and easy tool for recognition of acholic stools. The mobile App may represent an effective strategy for the early referral of children with acholic stools, and potentially could improve the outcomes of biliary atresia.