| Literature DB >> 35207269 |
Richard A Schreiber1, Sanjiv Harpavat2, Jan B F Hulscher3, Barbara E Wildhaber4.
Abstract
Biliary atresia (BA) is a rare newborn liver disease with significant morbidity and mortality, especially if not recognized and treated early in life. It is the most common cause of liver-related death in children and the leading indication for liver transplantation in the pediatric population. Timely intervention with a Kasai portoenterostomy (KPE) can significantly improve prognosis. Delayed disease recognition, late patient referral, and untimely surgery remains a worldwide problem. This article will focus on biliary atresia from a global public health perspective, including disease epidemiology, current national screening programs, and their impact on outcome, as well as new and novel BA screening initiatives. Policy challenges for the implementation of BA screening programs will also be discussed, highlighting examples from the North American, European, and Asian experience.Entities:
Keywords: biliary atresia; epidemiology; newborn screening; pediatric liver disease; public health
Year: 2022 PMID: 35207269 PMCID: PMC8876662 DOI: 10.3390/jcm11040999
Source DB: PubMed Journal: J Clin Med ISSN: 2077-0383 Impact factor: 4.241
Figure 1Worldwide incidences of biliary atresia (Jimenez–Rivera et al. [3], © 2013 reprinted by the permission of Wolters Kluwer Health).
Figure 2The Matsui stool colour card. This is the first version of SCC in Tochigi Prefecture, Japan. It was delivered to all pregnant women together with a “Maternal and Child Health Handbook”. Stool colors were numbered. Images 1–3 were pale-pigmented, and images 4–7 were bile-pigmented stools. A mother is asked to compare the colour of her infant’s stool to that of the card, to fill in a corresponding number just before the 1-month health checkup, and to hand it to the attending doctor. When pale-pigmented stools were suspected, the doctor reported to the SCC office by telephone or fax immediately; otherwise SCC were returned to the office by post weekly. The figure is provided to respectfully acknowledge the ground-breaking work of Professor Akira Matsui who passed away in 2020. There are now several versions of the SCC in many languages that are used for BA screening around the world. (Matsui [36], © 2013 reprinted by the permission of Springer Nature).
BA screening performance.
| Stool Colour Card Screening | ||||||||
|---|---|---|---|---|---|---|---|---|
| Country | Year | # Screened Patients | BA Cases | Sensitivity | Specificity | PPV | NPV | KPE Age Pre-/Post Screening |
| Taiwan * [ | 2004–2005 | 422,273 | 75 | 84 | 99.9 | 22.5 | 99.9 | <60 days: 47%/67% |
| Japan # [ | 1994–2011 | 313,230 | 34 | 76.5 | 99.9 | 12.7 | 99.9 | 67/56 |
| Chaoyang District Beijing † [ | 2013–2014 | 29,799 | 4 | 50 | 99.9 | 4.5 | 99.9 | n/a |
| Canada § [ | 2014–2016 | 87,583 | 6 | 83 | 99.9 | 6 | 99.9 | n/a |
| * Diagnostic accuracy statistics for detecting BA by 60 days of life; # Diagnostic accuracy statistics for detecting BA by 1 month of life; † Diagnostic accuracy statistics for detecting BA by 4 months of life; § Diagnostic accuracy statistics for detecting BA by 1 month of life; n/a = not available. | ||||||||
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| UK * [ | 1995–1997 | 23,214 | 100.0 | 99.5 | 10.3 | n/a | n/a | |
| US # [ | 2013–2014 | 11,636 | 2 | 100.0 | 99.9 | 18 | n/a | n/a |
| US # [ | 2015–2018 | 123,279 | 7 | 100.0 | 99.9 | 5.9 | 100 (100–100) | 56/36 |
| * Diagnostic accuracy statistics for detecting BA by 28 days of life (last follow-up test for BA patients performed on day of life 22); # Diagnostic accuracy statistics for detecting BA by 2 weeks of life in a two-stage screening approach (first test in newborn period, second test at 2 weeks of life if first test abnormal); n/a = not available. | ||||||||
Mobile device screening application (Angelico et al. [43], © 2017 reprinted by the permission of Sage Publications).
| Characteristics | PoopMD | Baby Poop | PopòApp |
|---|---|---|---|
| Year | 2015 | 2017 | 2020 |
| Country | USA | Japan | Italy |
| Reference | [ | [ | Current study |
| Programming language | Java | Java | |
| Operating system | iOS/Android | iOS | iOS/Android |
| Source of pictures | Previously validated and recorded | Pre-existing images | Newly acquired images taken with the Pop6App |
| Establishment of the gold standard for stool color | ISCC | Pre-existing BA and non-BA stool images | ISCC |
| Color analyzer system | RGB parameters | RGB and HSV parameters + ma chine learning process | RGB system + machine |
| Clinical assessment of the App | Agreement between 6 doc-tors who revisited the pictures | Performance tested with pre-classi-fied images | Real-time assessment by 4 doctors who took the images (agreement between 4 doctors) |
| Classification of stool color | Acholic, cholic, indeterminate | Acholic, cholic | Acholic, cholic, uncertain, indeterminate |
| Number of pictures for Accuracy test of the App | 34 | 40 | 160 |
| – Acholic | 7 | 5 | 60 |
| – Normal | 24 | 35 | 63 |
| – Uncertain | 16 | ||
| – Indeterminate | 3 | 21 | |
| Sensitivity (95% CI) | 100% | 100% (48–100%) | 100% (93.9–100.0%) |
| Specificity (95% CI) | 89% | 100% (90–100%) | 99% (94.6–99.9%) |
BA: biliary atresia; CI: confidence intervals; HSV: hue-saturation-value; ISCC: infant stool color card; RGB: red-green-blue.