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一款移动健康应用程序PoopMD能准确识别婴儿无胆汁粪便。

PoopMD, a Mobile Health Application, Accurately Identifies Infant Acholic Stools.

作者信息

Franciscovich Amy, Vaidya Dhananjay, Doyle Joe, Bolinger Josh, Capdevila Montserrat, Rice Marcus, Hancock Leslie, Mahr Tanya, Mogul Douglas B

机构信息

Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.

Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, United States of America.

出版信息

PLoS One. 2015 Jul 29;10(7):e0132270. doi: 10.1371/journal.pone.0132270. eCollection 2015.

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.

摘要

胆道闭锁(BA)是美国儿童终末期肝病的主要病因。在围产期用描绘无胆汁粪便和正常粪便的便卡对家长进行教育,与改善BA的诊断时间和生存率相关。PoopMD是一款移动应用程序,它利用智能手机的摄像头和颜色识别软件来分析婴儿的粪便,并确定是否需要进一步随访。PoopMD是使用自定义HTML5/CSS3开发的,并进行了打包处理,以便在iOS和安卓平台上运行。为了确定粪便颜色的金标准,邀请了七位儿科医生查看45张婴儿粪便照片,并将其评为无胆汁、正常或不确定。有6名及以上儿科医生意见一致的样本被定义为金标准,只有这些样本被纳入分析。使用配备白炽灯照明的iPhone 5s评估PoopMD的准确性。比较了三名外行人与一名专家用户在将粪便照片分析为无胆汁与正常(中间评级按50%一致加权,kappa值)方面的差异。还评估了iPhone 5s与三星Galaxy S4之间以及白炽灯照明与紧凑型荧光灯照明之间输出的差异。6名及以上儿科医生对27张正常照片和7张无胆汁照片达成了一致;没有照片被定义为不确定。敏感性为7/7(100%)。特异性为24/27(89%),有3/27被标记为不确定;没有正常粪便照片被标记为无胆汁。拉普拉斯平滑阳性似然比为6.44(95%可信区间2.52至16.48),阴性似然比为0.13(95%可信区间为0.02至0.83)。用户间kappa值为0.68,手机间kappa值为0.88,照明间kappa值为0.81。因此,在这项初步研究中,PoopMD能够准确区分无胆汁粪便和正常颜色粪便,不同用户之间有较高的一致性,在两款流行智能手机和不同环境光设置下几乎完全一致。PoopMD可能是一个有价值的工具,可帮助家长在围产期识别无胆汁粪便,并就是否需要带孩子去看儿科医生进行进一步评估提供指导。PoopMD可能会改善BA患儿的治疗结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9372/4519295/162ffd0b9e42/pone.0132270.g001.jpg

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