MG-120 Chorionic villus sampling: 3 cases with discrepancies between ifish, array-cgh and karyotype
Bibliographic record
Abstract
Background Chorionic villus sampling (CVS) is the method of choice for prenatal diagnosis (PND) in first-trimester pregnancies (10–13thweeks and 6 days), particularly for high risk of fetal abnormalities. This procedure allows earlier diagnosis in order to enable effective pregnancy management. Microarray analysis is now performed on CVS. Objectives/method We review 3 cases using fluorescence in situ hybridization on uncultivated nuclei (iFISH), CGH array results on DNA extraction from the entire villi and karyotype analyses on cultured CVS. Results Two cases showed normal iFISH profile for chromosomes 13, 18, 21, X and Y, while the CGH array revealed a weak mosaicism for monosomy X in one CVS case and for trisomy 18 in the other. Karyotypes showed 45, X and 47, XY, +18 in more than 95% of the cells. In the third case, the iFISH and the CGH array were normal, but the karyotype revealed a trisomy 9 in 76% of the cells. Conclusions CVS mosaicism and feto-placental discrepancies are rare phenomena occurring in ~1–2% of the PND. Cytogenetic analysis of CVS may give different results since CVS is from various placental cell lineages. Therefore, a cultured CVS (mesenchyme) analysis should be completed in order to reduce the incidence of false-positive or false-negative findings. In those cases, amniocentesis follow-up could be offered to complete the prenatal diagnosis.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 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".