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Record W4410122181 · doi:10.1002/pd.6785

Reporting Criteria for Prenatally Identified Variants of Uncertain Significance Differs Among Cytogenetics Laboratories in North America

2025· article· en· W4410122181 on OpenAlexaboutno aff
Matthew A. Shear, Arun P. Wiita, Jingwei Yu, Teresa N. Sparks, Mary E. Norton, Kate Swanson

Bibliographic record

VenuePrenatal Diagnosis · 2025
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsCopy-number variationCytogeneticsMedicinePrenatal diagnosisMedical geneticsFamily medicinePrenatal ultrasoundPregnancyChromosomeBiologyGeneticsGenomeFetus

Abstract

fetched live from OpenAlex

OBJECTIVE: Current technical standards for chromosomal microarray (CMA) interpretation are not prescriptive for reporting variants of uncertain significance (VUS) identified prenatally. We sought to compare prenatal CMA reporting among cytogenetic labs and identify potential drivers of practice variation. METHODS: We conducted an electronic cross-sectional survey of cytogeneticists in the United States and Canada from July-December 2023. Participants were identified through the American Cytogenetics Forum List. RESULTS: Labs reported differences in their size threshold used when reporting CNVs lacking OMIM annotated genes as a VUS, variable use of clinical data such as ultrasound or family history when deciding to report a VUS, and differences in opinion regarding the underlying pathogenicity of certain CNVs. Many cytogeneticists reported concerns about legal liability related to prenatal CMA reporting, and many shared concerns that a patient may terminate a pregnancy based on a VUS. CONCLUSION: Reporting criteria for prenatally identified variants of uncertain significance differs among cytogenetic laboratories in North America. Many possible drivers of this practice variation were identified, including a lack of national guidelines that comprehensively address the unique considerations for prenatal CMA reporting.

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)0.000
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.031
GPT teacher head0.325
Teacher spread0.294 · 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 designObservational
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
Published2025
Admission routes1
Has abstractyes

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