P59Prenatal diagnosis of fetal rubella infection by ultrasound‐guided cordocentesis
Bibliographic record
Abstract
Objective Our purpose was to compare the accuracy between rubella‐specific IgM and polymerase chain reaction (PCR) for the diagnosis of fetal rubella infection by ultrasound‐guided cordocentesis. Method 30 pregnant women with the evidences of rubella infection were enrolled. Fetal rubella infection was diagnosed by rubella‐specific IgM using microparticle enzyme immunoassay (MEIA) and rubella virus PCR with the blood obtained by ultrasound‐guided cordocentesis after 21 weeks of gestation. Neonatal outcomes were evaluated by physical examination at birth and rubella‐specific IgM if possible. Results 20 cases were evaluated by IgM and PCR, and 10 cases only IgM. No fetus showed positive IgM antibody, and 8 of 20 cases showed positive PCR in cord blood, and 6 in amniotic fluid. One infant with negative rubella‐specific IgM by cordocentesis before completed 22 weeks resulted in positive IgM at birth, low birth weight, strabismus and developmental delay. These findings were compatible with congenital rubella syndrome. No case showed congenital rubella syndrome in the fetuses with positive rubella PCR. Conclusion (1) The incidence of fetal rubella infection may be very low in mothers with rubella infection. It is suggested that prenatal diagnosis should be performed even if maternal infection occurs in early pregnancy; (2) Cord blood rubella‐specific IgM is more accurate than PCR for the prenatal diagnosis of congenital rubella syndrome; (3) Cordocentesis for rubella‐specific IgM detection should be done after 22 weeks of gestation for accurate 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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".