Home-based screening for biliary atresia using infant stool colour cards: A large-scale prospective cohort study and cost-effectiveness analysis
Bibliographic record
Abstract
OBJECTIVE: Biliary atresia (BA), a leading cause of paediatric liver failure and liver transplantation, manifests by three weeks of life as jaundice with acholic stools. Poor outcomes due to delayed diagnosis remain a problem worldwide. We evaluated and assessed the cost-effectiveness of methods of introducing a BA Infant Stool Colour Card (ISCC) screening programme in Canada. SETTING AND METHODS: A prospective study at BC Women's Hospital recruited consecutive healthy newborns through six incrementally more intensive screening approaches. Under the baseline "passive" strategy, families received ISCCs at maternity, with instructions to monitor infant stool colour daily and return the ISCC by mail at age 30 days. Additional strategies were: ISCC mailed to family physician; reminder letters or telephone calls to families or physicians. Random telephone surveys of ISCC non-returners assessed total card utilization. Primary outcome was ISCC utilization rate expressed as a composite outcome of the ISCC return rate and non-returned ISCC use. Markov modelling was used to predict incremental costs and life years gained from screening (passive and reminder), compared with no screening, over a 10-year time horizon. RESULTS: 6,187 families were enrolled. Card utilization rates in the passive screening strategy were estimated at 60-94%. For a Canadian population, the increase in cost for passive screening, compared with no screening, is $213,584 and the gain in life years is 9.7 ($22,000 per life-year gained). CONCLUSIONS: A BA ISCC screening programme targeting families of newborns is feasible in Canada. Passive distribution of ISCC at maternity is potentially effective and highly cost-effective.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".