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Record W2974383071 · doi:10.1002/pd.5563

A 2‐year review of publicly funded cell‐free DNA screening in Ontario: utilization and adherence to funding criteria

2019· review· en· W2974383071 on OpenAlexaffabout
Kara Bellai‐Dussault, Lynn Meng, Tianhua Huang, Jessica Reszel, Mark Walker, Andrea Lanes, Nanette Okun, Christine M. Armour, Shelley Dougan

Bibliographic record

VenuePrenatal Diagnosis · 2019
Typereview
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsMount Sinai HospitalOntario Stroke NetworkNorth York General HospitalUniversity of TorontoOttawa HospitalChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsMedicineCell-free fetal DNAAuditAneuploidyFamily medicineCohortPopulationPrenatal screeningObstetricsGynecologyPregnancyPrenatal diagnosisEnvironmental healthInternal medicineFetusChromosomeBiologyGenetics

Abstract

fetched live from OpenAlex

OBJECTIVE: Ontario offers a publicly funded modified contingent model of prenatal screening for aneuploidy in which cell-free DNA (cfDNA) screening is covered for pregnancies at higher risk of fetal aneuploidy. The objective of this study was to review utilization of provincially funded cfDNA screening and adherence to the criteria laid out in Ontario prenatal screening guidelines. METHODS: This was a descriptive cohort study using data collected by Ontario's prescribed maternal and child registry. The study population included all pregnant individuals who received cfDNA screening from January 2016 to December 2017. RESULTS: The most common criteria for provincially funded cfDNA screening were advanced maternal age ≥40 years (37.7%), positive multiple marker screen (34.1%), modifying risk factors such as ultrasound soft markers (7.1%), and previous aneuploidy (5.5%). The audit demonstrated that 2.9% of funded cfDNA screens tests did not meet funding criteria, and that 11.4% of self-paid cfDNA screens could have been publicly funded. CONCLUSION: Reviewing and auditing the application of criteria for funded cfDNA screening using prescribed registry data allows an opportunity to identify areas where targeted education may improve adherence to standardized screening protocols, and provides a basis for reassessment of the funding model.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.694
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.204
GPT teacher head0.384
Teacher spread0.180 · 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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations11
Published2019
Admission routes2
Has abstractyes

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