39: Five Years of Cystic Fibrosis Newborn Screening: Our Experience
Bibliographic record
Abstract
In the spring of 2008, Newborn Screening Ontario (NSO) expanded their panel to include cystic fibrosis (CF), using an immunoreactive trypsinogen (IRT)/DNA protocol. Those that are positive are referred for a sweat test, which is still considered the gold standard for diagnosis. The goal is to detect a population at risk for CF and upon diagnosis, initiate therapy, minimizing adverse outcomes. We have chosen to perform confirmatory molecular testing on each screen-positive individual, differing from some other centres in Ontario, because our hospital laboratory uses a larger mutation panel (70+6 polymorphisms) compared to that used by NSO (39 +3 polymorphisms). This aligns with the provincial recommendations set out by NSO as part of the diagnostic work up. To examine whether confirmatory molecular testing using our expanded panel on all screen-positive newborns is justified. We performed a retrospective descriptive analysis of the results of our program recorded from April 2008 to 2013 using an internal database. Particular note was made of individuals found to have a second mutation with our confirmatory panel, and of the sweat chloride obtained. 337 patients have screened positive and been referred to our centre for sweat chloride testing. Of these, 25 (7.4%) have been referred with two mutations identified and 258 (76.5%) have one known mutation found. In addition, 47 (13.9%) have no known mutations, but are offered a sweat chloride as their IRT level exceeds the 99th percentile. Using our expanded panel, we uncovered a second mutation in 14 children, eight of whom would have been discharged as unaffected as they had normal initial sweat tests. Thirteen infants had a sweat chloride that fell within the ‘borderline’ range of 30 mmol/L to 60 mmol/L, of whom seven infants had two known mutations already identified by NSO, four infants had an additional mutation identified on our panel, and two infants required sequencing to identify a second mutation. To our knowledge, since the inception of this program, there have been no children with classical CF that were not identified on newborn screen. Though our approach may identify otherwise ‘healthy’ infants with a second mutation of unknown clinical relevance, given the uncertainty of the long-term prognosis associated with some mutations, we feel it continues to be warranted until more information is known.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".