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Record W2789583401 · doi:10.1093/jcag/gwy008.336

A335 BILIARY ATRESIA HOME SCREENING PROGRAM IN BRITISH COLUMBIA: EVALUATION OF FIRST TWO YEARS

2018· article· en· W2789583401 on OpenAlexaffabout
Jessica P. Woolfson, Richard A. Schreiber, Alison Butler, J. W. Macfarlane, Janusz Kaczorowski, Jean‐Paul Collet, Stirling Bryan

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2018
Typearticle
Languageen
FieldMedicine
TopicPediatric Hepatobiliary Diseases and Treatments
Canadian institutionsVancouver Coastal HealthUniversité de MontréalBC Children's HospitalVancouver Coastal Health Research InstituteUniversity of British Columbia
Fundersnot available
KeywordsBiliary atresiaMedicineReferralPediatricsLiver diseaseLiver transplantationFamily medicineSurgeryInternal medicineTransplantation

Abstract

fetched live from OpenAlex

Biliary atresia (BA), a rare newborn liver disease (1:19,000 births in Canada), is the leading cause of cirrhosis and liver related mortality in children. Early referral and timely surgical intervention (≤60 days of age) with a Kasai procedure (KP) offers the best chance for long-term survival without liver transplant. Taiwan has a universal BA screening program using infant stool colour cards (SCCs) with proven effectiveness. We report our experience following introduction of a similar BA screening program in BC. To assess the BC provincial BA home screening program performance and cost during the first 2 years of operation. The study period was from program launch April 1, 2014 to March 31, 2016. SCCs were distributed to families upon discharge from the maternity ward. Parents were instructed to monitor their infant’s stool colour for the first month of life using photos of normal and abnormal stool colour on the SCC and contact the screening centre if concerned. Number of live births, BA cases and program costs were calculated. Frequency and reasons for contacting the centre were recorded. Card distribution was assessed by examining the number of SCCs re-ordered by maternity units compared with their number of births. Also, BC Children’s Hospital charts from four 2-week periods were randomly selected between July 2015 and June 2016 to determine SCC distribution rates based on nurse sign-off of the SCC box on the discharge sheet. Analyses of sensitivity, specificity, PPV and NPV of SCC performance were performed. The UBC IRB approved the study. There were 87,583 live births through the study period and 8 cases of BA (1:10,948). Four BA cases were identified by the SCC and four were missed. The median age of KP in the identified and missed groups was 51 and 112 days respectively. The sensitivity of the SCC was 50%, specificity 99%, PPV 5% and NPV 99%. The false positive rate was 0.08%. 126 maternity units received SCCs. Eight sites did not reorder sufficient number of SCCs based on their number of births, accounting for 2% of the provincial births. 1050 BCCH charts were reviewed. 63 did not contain a discharge record. Of the remaining 987 charts, 94% had the SCC signed off as a discharge item. Reasons for incomplete SCC sign off were early discharge and discharge sheets with multiple unsigned items. The total 2 year operational cost was $42,600 with the SCC cost per birth being $0.48. This first report of the BC BA screening program showed SCC case identification was associated with earlier age of KP. However, the SCC requires modification to improve its sensitivity. Specificity and distribution rates were high and program cost was low. Further assessment of the program after 5 years will provide additional information regarding outcomes and cost effectiveness. None

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.269
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2018
Admission routes2
Has abstractyes

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