Amniocentesis for Twin Pregnancies: Is Alpha-Fetoprotein Useful in Confirming that the Two Sacs Were Sampled?
Bibliographic record
Abstract
OBJECTIVE: To assess if amniotic fluid alpha-fetoprotein (AFAFP) could be useful to determine if both sacs are sampled during an amniocentesis for twin pregnancies. METHOD: We reviewed all amniocenteses performed on twin pregnancies over a 5-year period. Inclusion criteria were restricted to pregnancies where both karyotypes and AFAFP were available on each fetus. Pregnancies complicated by fetal anomalies were excluded. The following information was obtained: maternal age, gestational age at the procedure, karyotypes, AFAFP values, pregnancy and neonatal outcome. Placental pathology reports were used to confirm chorionicity. Analysis was performed to evaluate the impact of the fetal gender and chorionicity on the AFAFP values. RESULTS: 260 pregnancies were reviewed. Mean maternal age was 36.9 years (33.6, 40.1). Gestational age at the time of the procedure was 16.2 weeks (14.5, 17.9). Complications included 1.8% of misdiagnosis (discrepancy between karyotype and gender). The difference of AFAFP values between the two fetuses was statistically larger in dichorionic pregnancies than in monochorionic gestations. Fetal gender had no influence on the AFAFP. CONCLUSION: Amniocentesis in twin pregnancies is associated with a 1.8% risk of misdiagnosis. AFAFP can help to assess the chorionicity of a twin pregnancy. When the difference between the two values is <0.2 MoM and the chorionicity was thought to be dichorionic and the two karyotypes are similar, then failure to sample both sacs should be suspected.
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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 | 0.003 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".