A New Era in Prenatal Diagnosis: The Use of Cell-Free Fetal DNA in Maternal Circulation for Detection of Chromosomal Aneuploidies
Bibliographic record
Abstract
Prenatal screening for chromosomal aneuploidies is a fundamental part of routine obstetric care in most countries. Typically, maternal age, weight, ethnicity, serum biomarkers (including pregnancy-associated plasma protein A, human chorionic gonadotropin, α-fetoprotein, inhibin A, and estriol), and sonographic features (i.e., nuchal translucency) are included in a risk algorithm to determine the probability of the fetus being affected. Pregnant women identified as at high risk according to the prenatal screen can then undergo invasive procedures, such as amniocentesis and chorionic villus sampling, to confirm the diagnosis. Current prenatal-screening methods are able to identify approximately 90% of pregnancies affected by trisomy 21 (Down syndrome) at a false-positive rate of approximately 5%. Given that the prevalence of chromosomal aneuploidies is generally quite low, a false-positive rate of 5% means that a large number of women with unaffected pregnancies undergo invasive procedures, putting the fetus at an unnecessary risk for miscarriage. The discovery of fetal cell-free DNA in the plasma of pregnant women 14 years ago opened up the possibility of identifying chromosomal abnormalities noninvasively, through a single blood sample. Approximately 10% of cell-free DNA in the maternal circulation is of fetal origin, and this property was initially exploited to determine rhesus D status and the sex of the unborn fetus. The advent of next-generation DNA sequencing, however, has allowed prenatal detection of chromosomal aneuploidies, including trisomy 21, from maternal blood. In brief, the proportion of chromosome 21 DNA molecules in maternal plasma is measured directly; an increase above a predetermined threshold is indicative of trisomy 21. The clinical performance of this noninvasive prenatal test has been promising, with recent clinical studies having shown a diagnostic sensitivity of 100% and a diagnostic specificity of 98%–99%, compared with full karyotyping by invasive means. When used as a second-tier screening procedure, this technology also has the …
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How this classification was reachedexpand
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 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".