Conservative in utero treatment of fetal dyshormonogenetic goiter with levothyroxine, a systematic literature review
Bibliographic record
Abstract
Fetal goitrous hypothyroidism is a rare condition associated with important obstetrical, neonatal complications, and neurodevelopmental impairments. Prenatal treatment remains controversial, and the risk to benefit ratio must be accurately assessed and considered for individualized management. The objective of this review was to evaluate the feasibility, safety, and effectiveness of the conservative in utero treatment of fetal goitrous hypothyroidism. In total, 25 reports that met our inclusion criteria were selected and the management of 38 cases was analyzed. Prenatal diagnosis consisted mainly of ultrasonographic findings. Fetal thyroid status was assessed by cordocentesis. Prenatal treatment varied widely in terms of levothyroxine (LT4) route of administration, dosage, number of injections, and frequency. Although different regimens and routes of administration were proposed, they seem to have similar results regarding fetal goiter reduction and thyroid status at birth. At birth, most babies had hypothyroidism, but the long‑term follow‑up indicated a normal psycho‑neuromotor development. Our data confirm the feasibility of conservative treatment with LT4 for fetal goitrous hypothyroidism. Further studies are needed to determine the optimal management of this disorder.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".