Clinical experience with single‐nucleotide polymorphism‐based non‐invasive prenatal screening for 22q11.2 deletion syndrome
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Bibliographic record
Abstract
OBJECTIVES: To evaluate the performance of a single-nucleotide polymorphism (SNP)-based non-invasive prenatal test (NIPT) for the detection of fetal 22q11.2 deletion syndrome in clinical practice, assess clinical follow-up and review patient choices for women with high-risk results. METHODS: In this study, 21 948 samples were submitted for screening for 22q11.2 deletion syndrome using a SNP-based NIPT and subsequently evaluated. Follow-up was conducted for all cases with a high-risk result. RESULTS: Ninety-five cases were reported as high risk for fetal 22q11.2 deletion. Diagnostic testing results were available for 61 (64.2%) cases, which confirmed 11 (18.0%) true positives and identified 50 (82.0%) false positives, resulting in a positive predictive value (PPV) of 18.0%. Information regarding invasive testing was available for 84 (88.4%) high-risk cases: 57.1% (48/84) had invasive testing and 42.9% (36/84) did not. Ultrasound anomalies were present in 81.8% of true-positive and 18.0% of false-positive cases. Two additional cases were high risk for a maternal 22q11.2 deletion; one was confirmed by diagnostic testing and one had a positive family history. There were three pregnancy terminations related to screening results of 22q11.2 deletion, two of which were confirmed as true positive by invasive testing. CONCLUSIONS: Clinical experience with this SNP-based non-invasive screening test for 22q11.2 deletion syndrome indicates that these deletions have a frequency of approximately 1 in 1000 in the referral population with most identifiable through this test. Use of this screening method requires the availability of counseling and other management resources for high-risk pregnancies.
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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 | 0.000 | 0.019 |
| 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 it