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PoopMD, a Mobile Health Application, Accurately Identifies Infant Acholic Stools
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 applicatio...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4519295/ https://www.ncbi.nlm.nih.gov/pubmed/26221719 http://dx.doi.org/10.1371/journal.pone.0132270 |
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author | Franciscovich, Amy Vaidya, Dhananjay Doyle, Joe Bolinger, Josh Capdevila, Montserrat Rice, Marcus Hancock, Leslie Mahr, Tanya Mogul, Douglas B. |
author_facet | Franciscovich, Amy Vaidya, Dhananjay Doyle, Joe Bolinger, Josh Capdevila, Montserrat Rice, Marcus Hancock, Leslie Mahr, Tanya Mogul, Douglas B. |
author_sort | Franciscovich, Amy |
collection | PubMed |
description | 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). kappa(user) was 0.68, kappa(phone) was 0.88, and kappa(light) 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. |
format | Online Article Text |
id | pubmed-4519295 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-45192952015-07-31 PoopMD, a Mobile Health Application, Accurately Identifies Infant Acholic Stools Franciscovich, Amy Vaidya, Dhananjay Doyle, Joe Bolinger, Josh Capdevila, Montserrat Rice, Marcus Hancock, Leslie Mahr, Tanya Mogul, Douglas B. PLoS One Research Article 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). kappa(user) was 0.68, kappa(phone) was 0.88, and kappa(light) 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. Public Library of Science 2015-07-29 /pmc/articles/PMC4519295/ /pubmed/26221719 http://dx.doi.org/10.1371/journal.pone.0132270 Text en © 2015 Franciscovich et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Franciscovich, Amy Vaidya, Dhananjay Doyle, Joe Bolinger, Josh Capdevila, Montserrat Rice, Marcus Hancock, Leslie Mahr, Tanya Mogul, Douglas B. PoopMD, a Mobile Health Application, Accurately Identifies Infant Acholic Stools |
title | PoopMD, a Mobile Health Application, Accurately Identifies Infant Acholic Stools |
title_full | PoopMD, a Mobile Health Application, Accurately Identifies Infant Acholic Stools |
title_fullStr | PoopMD, a Mobile Health Application, Accurately Identifies Infant Acholic Stools |
title_full_unstemmed | PoopMD, a Mobile Health Application, Accurately Identifies Infant Acholic Stools |
title_short | PoopMD, a Mobile Health Application, Accurately Identifies Infant Acholic Stools |
title_sort | poopmd, a mobile health application, accurately identifies infant acholic stools |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4519295/ https://www.ncbi.nlm.nih.gov/pubmed/26221719 http://dx.doi.org/10.1371/journal.pone.0132270 |
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