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PoopMD, a Mobile Health Application, Accurately Identifies Infant Acholic Stools
Amy Franciscovich1, Dhananjay Vaidya2, Joe Doyle3
1Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.
Insights
PoopMD, a mobile app, accurately identifies infant acholic stools, aiding early diagnosis of biliary atresia (BA). This tool shows high agreement across users and devices, potentially improving outcomes for infants with BA.
Area of Science:
- Pediatric Gastroenterology
- Medical Diagnostics
- Mobile Health Technology
Background:
- Biliary atresia (BA) is the primary cause of pediatric end-stage liver disease in the US.
- Early diagnosis and intervention significantly improve outcomes for BA.
- Parental education using stool color charts has shown promise in improving BA diagnosis timeliness.
Purpose of the Study:
- To evaluate the accuracy and reliability of the PoopMD mobile application in differentiating acholic stools from normal infant stools.
- To assess the agreement of PoopMD's analysis across different users, smartphone models, and lighting conditions.
Main Methods:
- PoopMD utilizes smartphone cameras and color recognition software to analyze infant stool color.
- A gold standard was established by expert pediatrician consensus on 45 infant stool photographs.
- The app's performance was tested for sensitivity, specificity, and agreement (kappa statistic) across various user types, devices (iPhone 5s, Samsung Galaxy S4), and lighting conditions.
Main Results:
- PoopMD achieved 100% sensitivity and 89% specificity in identifying acholic stools, with 3 normal stools misclassified as indeterminate.
- Substantial agreement (kappa=0.68) was observed between lay users and expert analysis.
- Almost perfect agreement (kappa=0.88 for devices, kappa=0.81 for lighting) was found across different smartphone models and lighting conditions.
Conclusions:
- PoopMD demonstrates significant accuracy and reliability in distinguishing acholic from normal infant stools.
- The mobile application shows consistent performance across different users, smartphones, and lighting, suggesting its potential as a valuable tool for parents.
- PoopMD may facilitate earlier detection of biliary atresia, leading to improved clinical outcomes for affected children.
Abstract:
Biliary atresia (BA) is the leading cause of pediatric end-stage liver disease in the United States. Education of parents in the perinatal period with stool cards depicting acholic and normal stools has been associated with improved time-to-diagnosis and survival in BA. PoopMD is a mobile application that utilizes a smartphone's camera and color recognition software to analyze an infant's stool and determine if additional follow-up is indicated. PoopMD was developed using custom HTML5/CSS3 and wrapped to work on iOS and Android platforms. In order to define the gold standard regarding stool color, seven pediatricians were asked to review 45 photographs of infant stool and rate them as acholic, normal, or indeterminate. Samples for which 6+ pediatricians demonstrated agreement defined the gold standard, and only these samples were included in the analysis. Accuracy of PoopMD was assessed using an iPhone 5s with incandescent lighting. Variability in analysis of stool photographs as acholic versus normal with intermediate rating weighted as 50% agreement (kappa) was compared between three laypeople and one expert user. Variability in output was also assessed between an iPhone 5s and a Samsung Galaxy S4, as well as between incandescent lighting and compact fluorescent lighting. Six-plus pediatricians agreed on 27 normal and 7 acholic photographs; no photographs were defined as indeterminate. The sensitivity was 7/7 (100%). The specificity was 24/27 (89%) with 3/27 labeled as indeterminate; no photos of normal stool were labeled as acholic. The Laplace-smoothed positive likelihood ratio was 6.44 (95% CI 2.52 to 16.48) and the negative likelihood ratio was 0.13 (95% CI 0.02 to 0.83). kappauser was 0.68, kappaphone was 0.88, and kappalight was 0.81. Therefore, in this pilot study, PoopMD accurately differentiates acholic from normal color with substantial agreement across users, and almost perfect agreement across two popular smartphones and ambient light settings. PoopMD may be a valuable tool to help parents identify acholic stools in the perinatal period, and provide guidance as to whether additional evaluation with their pediatrician is indicated. PoopMD may improve outcomes for children with BA.
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