Pregnancy Experiences in the Woman With Mild Hyperphenylalaninemia
Bibliographic record
Abstract
OBJECTIVE: A major issue in maternal phenylketonuria (MPKU) has been whether maternal non-PKU mild hyperphenylalaninemia (MHP) is teratogenic. Such untreated pregnancies and their outcomes are presented on this report. METHODS: Enrolled pregnancies in which the untreated prepregnancy assigned phenylalanine level (APL) was no more than 600 micro mol/L were included in the Maternal PKU Collaborative Study and were followed according to protocol. RESULTS: Forty-eight enrolled women with non-PKU MHP had mean APL 408 +/- 114 micromol/L. They had a total of 58 pregnancies that resulted in live births. Fifty were untreated. Maternal phenylalanine (Phe) levels in the untreated pregnancies decreased during pregnancy for average Phe exposure of 270 +/- 84 micromol/L, virtually identical to the level of 269 +/- 136 micromol/L in the 8 treated pregnancies. Birth measurements in the 50 offspring from untreated pregnancies were within normal limits with z scores of -0.25 for weight, 0.28 for length, and -0.63 for head circumference, although birth head circumference was negatively correlated with maternal APL (r = -0.30). Only 1 offspring had congenital heart disease. Offspring IQ was 102 +/- 15 compared with 96 +/- 14 in the mothers with untreated pregnancies and with 109 +/- 21 in control offspring. CONCLUSION: Maternal non-PKU MHP no more than 600 micromol/L does not require dietary therapy. The naturally lower Phe level during pregnancy seems to protect against teratogenesis.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".