The Importance of Newborn Genetic Screening for Early Identification of <i>GJB2</i> and <i>SLC26A4</i> Related Hearing Loss
Bibliographic record
Abstract
OBJECTIVE: To assess the added benefit of newborn genetic screening for GJB2 and SLC26A4 variants in conjunction with newborn hearing screening. STUDY DESIGN: Retrospective cohort study. METHODS: Children with known variants of GJB2 and SLC26A4 were identified from 485 children with hearing loss who underwent testing with Next Generation Sequencing (NGS) between January 2015 and February 2018, prior to expanded screening for genetic variants and congenital CMV. Children with two pathogenic or likely pathogenic variants of GJB2 or SLC26A4 were considered to have genetic hearing loss. NGS genetic data were compared to variants included in the expanded genetic screen for all newborns in Ontario and newborn hearing screening results. SETTING: Canadian tertiary pediatric hospital. RESULTS: Thirty-five children with GJB2 and SLC26A4-associated hearing loss were identified by NGS (n = 27 GJB2-HL; n = 8 SLC26A4-HL). Of these, 20 (57%) had been identified by newborn hearing screening (14/27 52% GJB2-HL; 6/8 75% SLC26A4-HL). Ten of the 20 (50%) would also have been identified by genetic screening if it had been available (9/14 64% GJB2-HL; 1/6 17% SLC26A4-HL). An additional 8 children with GJB2 or SLC26A4-associated hearing loss passed their newborn hearing screen but showed hearing loss later; three of these children (38%) would have been identified by newborn genetic screening (3/6 GJB2-HL; 0/2 SLC26A4-HL). CONCLUSION: Genetic and hearing screening modalities in Ontario's expanded newborn hearing screening program improve early identification of children with hearing loss including those at risk of being missed by hearing screening alone. This was most clear for children with GJB2-hearing loss.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".