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Record W4361005368 · doi:10.3390/ijns9020018

Secondary Reporting of G6PD Deficiency on Newborn Screening

2023· article· en· W4361005368 on OpenAlexaffabout
Stephanie Chan, Pamela Blumenschein, Margaret Lilley, Larissa Olshaski, Aisha Bruce, Nicola Wright, Ross Ridsdale, Susan Christian

Bibliographic record

VenueInternational Journal of Neonatal Screening · 2023
Typearticle
Languageen
FieldMedicine
TopicNeonatal Health and Biochemistry
Canadian institutionsStollery Children's HospitalUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsGalactosemiaNewborn screeningPediatricsMedicineGlucose-6-phosphate dehydrogenase deficiencyInternal medicineBiology

Abstract

fetched live from OpenAlex

In April 2019, the Alberta Newborn Screening Program expanded to include screening for classic galactosemia using a two-tier screening approach. This approach secondarily identifies infants with glucose-6-phosphate dehydrogenase (G6PD) deficiency. The goals of this study were (i) to evaluate the performance of a two-tier galactosemia screening protocol, (ii) to explore the impact on and acceptability to families of reporting G6PD deficiency as a secondary finding, and (iii) assess the communication and follow-up process for positive G6PD deficiency screening results. The two-tiered galactosemia approach increased the positive predictive value (PPV) for galactosemia from 8% to 79%. An additional 119 positive newborn screen results were reported for G6PD deficiency with a PPV of 92%. The results show that there may be utility in reporting G6PD deficiency results. Most parents who participated in the study reported having some residual worry around the unexpected diagnosis; however, all thought it was helpful to know of their child's diagnosis of G6PD deficiency. Finally, the communication process for reporting G6PD deficiency newborn screen results was determined to result in appropriate follow up of infants.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.967
Threshold uncertainty score0.513

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.049
GPT teacher head0.362
Teacher spread0.312 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2023
Admission routes2
Has abstractyes

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