Population‐based trends in invasive prenatal diagnosis for ultrasound‐based indications: two decades of change from 1994 to 2016
Bibliographic record
Abstract
OBJECTIVE: To assess trends in ultrasound-indicated prenatal diagnostic testing performed over the past two decades in the Australian state of Victoria, in the context of rapidly changing practices in aneuploidy screening and chromosome analysis. METHODS: tests for trend or difference in proportions, as appropriate. RESULTS: During the 23-year study period, 1 533 317 births were recorded and 16 152 diagnostic procedures were performed for the primary indication of ultrasound abnormality. In recent years, ultrasound abnormality became the most common indication for prenatal invasive testing (29.4% of diagnostic tests between 2013 and 2016) due to a steep decline in testing for other indications such as positive result on combined first-trimester screening or advanced maternal age alone. In 2016, over 95% of ultrasound-indicated procedures were performed with CMA; among these, pathogenic copy number variant (CNV) was the most common (3.5%) abnormality detected, followed by trisomy 21 (2.8%). The diagnostic yield of ultrasound-indicated tests performed < 16 weeks was significantly higher than that of tests performed after 20 weeks (31.5% vs 9.0%). CONCLUSIONS: Ultrasound-indicated invasive testing is contributing to prenatal diagnosis in new ways in the genomic era. A pathogenic CNV is now the most likely diagnosis after ultrasound-indicated testing, rather than trisomy 21 or other whole-chromosome aneuploidy. Despite steady improvements in first-trimester screening for aneuploidy, the diagnostic yield of ultrasound-indicated tests > 20 weeks has remained stable due to increased utilization of CMA. Procedures performed for structural abnormalities < 16 weeks continue to have the highest diagnostic yield, supporting the benefits of early fetal structural assessment at 11-13 weeks. Copyright © 2018 ISUOG. Published by John Wiley & Sons Ltd.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".