Use of Clinically Informed Strategies and Diagnostic Yields of Genetic Testing for Fetal Structural Anomalies Following a Non‐Diagnostic Microarray Result: A Population‐Based Cohort Study
Bibliographic record
Abstract
OBJECTIVE: To investigate the performance of targeted gene sequencing, expanded gene panels, and selected exomes for prenatally identified fetal anomalies, after non-diagnostic microarray results. METHOD: All fetal samples received for genetic testing for fetal structural anomalies in the Canadian Maritime Provinces (2014-2022) were identified. Utilization and results of NGS sequencing strategies after a non-diagnostic microarray were correlated with ultrasound findings and autopsy results. RESULTS: Five hundred and ninety-three cases of fetal anomalies with non-diagnostic RAD results were identified, including 319 (54%) with isolated anomalies. Diagnostic yield from the microarray was 7.5%. Sequence-based testing for 131 cases gave an overall diagnostic yield of 38% (8.4% of initial cohort). For isolated anomalies, diagnostic yield was highest in the intracranial, renal, and musculoskeletal systems (44%, 60%, 64% respectively). Appropriate targeted gene sequencing provided a diagnostic yield of 40%. With clinically indicated criteria for exome analysis, diagnostic yields were higher than when clinical information prompted use of a selected gene panel (73% vs. 27%). Expanding to an exome after a non-diagnostic gene panel had an additional diagnostic yield of 13%. CONCLUSION: Multidisciplinary review and comprehensive clinical information can inform the selection of strategies for expanded genetic testing after non-diagnostic microarray for fetal anomalies within a publicly funded health care system.
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 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 | 0.073 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".