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The Influence of Etiology and Treatment Factors on Intellectual Outcome in Congenital Hypothyroidism

2001· article· en· W2317218604 on OpenAlexaff
Soon-IL Song, Denis Daneman, Joanne Rovet

Bibliographic record

VenueJournal of Developmental & Behavioral Pediatrics · 2001
Typearticle
Languageen
FieldMedicine
TopicThyroid Disorders and Treatments
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of TorontoMedical Council of Canada
Fundersnot available
KeywordsEtiologyCongenital hypothyroidismHormoneThyroidNeuropsychologyMedicinePediatricsPsychologyInternal medicineCognitionPsychiatry

Abstract

fetched live from OpenAlex

To determine the effects of hypothyroidism and hormonal patterns on outcome, we tested 65 7- to 12-year-old children with congenital hypothyroidism using standardized tests of intelligence, neuropsychological functioning, memory, and achievement. Results were analyzed by etiology, time to thyrotropin normalization, and hormone levels at testing. Children with athyreosis scored below other etiologies on visuospatial, attention, and arithmetic indices. Children whose thyroid-stimulating hormone levels normalized by 1 to 2 months of age scored higher than later normalizers on indices of visual memory, attention, and arithmetic. Normalization of thyroid-stimulating hormone by 3 months of age was associated with better memory and learning abilities than later normalization. Thyroid hormone levels at testing were correlated with indices of sensorimotor, spatial, and language abilities. Two children with persistently elevated thyrotropin levels were not adversely affected. Present findings signify the need to establish etiology, normalize thyrotropin early, and maintain hormone levels in the normal range throughout childhood in children with congenital hypothyroidism.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.046
GPT teacher head0.316
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations97
Published2001
Admission routes1
Has abstractyes

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