Clinical aspects, prenatal diagnosis, and pathogenesis of trisomy 16 mosaicism
Bibliographic record
Abstract
INTRODUCTION: Analysis of data from cases of trisomy mosaicism can provide insight for genetic counselling after prenatal diagnosis and for the elucidation of the pathogenesis of trisomy during pregnancy. METHODS: Statistical analysis was carried out on data from 162 cases of pregnancies with prenatal diagnosis of trisomy 16 mosaicism. RESULTS: The majority of cases resulted in live birth (66%) with an average gestational age of 35.7 weeks and average birth weight of -1.93 standard deviations from the population mean. Among the live births 45% had at least one malformation, the most common being VSD, ASD, and hypospadias. The level of trisomy on direct CVS (cytotrophoblast) was associated with more severe intrauterine growth restriction (IUGR) and higher risk of malformation, while the level of trisomy on cultured CVS (chorionic villous stroma) was associated only with more severe IUGR. Similarly, the presence of trisomy on amniocentesis (amniotic fluid) was associated with both IUGR and malformation, while the presence of trisomy in the amniotic mesenchyme was associated only with IUGR. Surprisingly, the degree of trisomy in placental tissues appeared to be independent of the degree of trisomy in amniotic fluid and amniotic mesenchyme. The sex of the fetus was not associated with any outcome variables, although there was an excess of females (sex ratio = 0.45) that may be explained by selection against male mosaic trisomy 16 embryos before the time of CVS (approximately 9-12 weeks). CONCLUSION: The levels of trisomy in different fetal-placental tissues are significant predictors of some measures of outcome in mosaic trisomy 16 pregnancies.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".