Positive impacts of universal newborn screening on the outcome of children with sickle cell disease in the province of Quebec: A retrospective cohort study
Bibliographic record
Abstract
Abstract A universal newborn screening program for sickle cell disease (uNS‐SCD) was implemented in the province of Québec (Qc) in November 2013, close in time to the recommendation of early initiation of hydroxyurea (HU) therapy for children. This retrospective cohort study evaluated the impact of such a program on children first seen between January 2000 and December 2019. Cohorts pre‐SCD‐uNS in Qc (pre‐QcNS) (n = 253) and post‐QcNS (n = 157) for patients seen prior to or after Nov 2013 were compared. Kaplan‐Meier curves, Poisson regression, and logistic regressions were used for statistical analysis, using Software R version 4.2.1. Median age at first visit decreased significantly from 14.4 [interquartile range: 2.4–72.0] to 1.2 months [1.2–57.6] (p < 0.001). The percentage of children born in Qc undiagnosed at birth and referred after a first SCD‐related complication dropped from 42.6% to 0.0% (p < 0.0001). The median age of HU introduction for patients with SS/Sβ°‐thalassemia decreased from 56.4 [31.2–96.0] to 9.0 months post‐QcNS [8.0–12.1] (p < 0.001). Event‐free survival improved significantly for any type of hospitalization as well as for vaso‐occlusive crisis (VOC) (140–257 days (p < 0.001) and 1320 vs. 573 days (p < 0.002), respectively), resulting in a reduction from 2 [interquartile range: 1.0–3.0] to 1.0 hospitalizations/patient‐year [0.6–1.4] (p < 0.001). Children with SS/Sβ°‐thalassemia referred post‐QcNS also had fewer emergency department visits for VOC (RR: 0.69, 95% confidence interval: 0.54–0.88). The Universal NS program allows early detection and referral of children with SCD to comprehensive care centers. Earlier access ensures that children benefit from essential preventive interventions, reducing disease burden. This cohort study highlights that uNS‐SCD is an essential public health measure.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".