Province‐wide Biliary Atresia Home Screening Program in British Columbia
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Biliary atresia (BA), a rare newborn liver disease, is the leading cause of liver-related death in children. Early disease recognition and timely surgical Kasai hepatoportoenterostomy (KP) offers long-term survival without liver transplant. Universal BA screening in Taiwan using infant stool color cards (ISCCs) has proven effectiveness. We report our experience with infant stool color card (ISCC) BA screening in a province-wide program in British Columbia (BC). The objective of this study is to assess program performance and cost from launch April 1, 2014 to March 31, 2016. METHODS: ISCCs distributed to families upon maternity ward discharge. Parents were instructed to monitor their infant's stool color for 1 month and contacted the screening center with concerns. The number of live births, ISCC distribution, BA cases, and costs were recorded. Cases with Program screen success had both acholic stool recognition (ISCC screen success) and timely referral for BA. RESULTS: All 126 maternity units received ISCCs. Of 87,583 live births there were 6 BA cases. Of the 5 cases with ISCC Screen Success 3 had Program Screen Success. The median KP age in the program screen success and failure groups was 49 (42-52) and 116 (49-184) days, respectively. Program sensitivity was 50%, specificity 99%, positive predictive value 4%, and negative predictive value 99%. A random sample of 1054 charts at BC Children's Hospital found an ISCC distribution rate of 94%. After a phase-in period, the annual program cost was $30,033.82, and the ISCC cost per birth was $0.68. CONCLUSIONS: The screening program has high specificity and distribution with low cost. Successful program case identification had earlier age at KP. Program modifications aim to improve sensitivity. Longer-term studies will determine program impact on health outcomes.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".