Bibliographic record
Abstract
Purpose of review The purpose of this review is to summarize findings from research on children with congenital hypothyroidism diagnosed by newborn screening, to relate specific findings to aspects of treatment and follow-up, and to identify areas for concern and directions for future research. Recent findings Although early studies following children with congenital hypothyroidism identified by screening indicate improved outcome relative to cases diagnosed clinically, these children still have a mild IQ loss, which can be attenuated somewhat by an early high-dose level of thyroxine therapy. Additionally described are a number of subtle, selective, and persisting cognitive deficits that vary in type among the studies. Nevertheless, there is a consensus that disease severity and timing of onset predict different deficits than age at starting therapy and initial dose level. Although a series of newer second-generation papers report favorable outcomes when treatment factors are well controlled, sampling issues, age and thyroid status at testing, and aspects of testing all influence the results. Important outstanding issues include the optimal therapy for less severely affected cases and ensuring a high quality of subsequent care. Five areas for future research are highlighted. Summary Although early treatment of congenital hypothyroidism leads to improved outcome, minor deficits may arise from insufficient thyroid hormone before birth and during infancy. It is important to conduct large-scale multicenter investigations to identify and measure the critical factors affecting outcomes in this population.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".