Associations between Pituitary Imaging Abnormalities and Clinical and Biochemical Phenotypes in Children with Congenital Growth Hormone Deficiency: Data from an International Observational Study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND/AIMS: Magnetic resonance imaging (MRI) is used to investigate the etiology of growth hormone deficiency (GHD). This study examined relationships between MRI findings and clinical/hormonal phenotypes in children with GHD in the observational Genetics and Neuroendocrinology of Short Stature International Study, GeNeSIS. METHODS: Clinical presentation, hormonal status and first-year GH response were compared between patients with pituitary imaging abnormalities (n = 1,071), patients with mutations in genes involved in pituitary development/GH secretion (n = 120) and patients with idiopathic GHD (n = 7,039). RESULTS: Patients with hypothalamic-pituitary abnormalities had more severe phenotypes than patients with idiopathic GHD. Additional hormonal deficiencies were found in 35% of patients with structural abnormalities (thyroid-stimulating hormone > adrenocorticotropic hormone > luteinizing hormone/follicle-stimulating hormone > antidiuretic hormone), most frequently in patients with septo-optic dysplasia (SOD). Patients with the triad [ectopic posterior pituitary (EPP), pituitary aplasia/hypoplasia and stalk defects] had a more severe phenotype and better response to GH treatment than patients with isolated abnormalities. The sex ratio was approximately equal for patients with SOD, but there was a significantly higher proportion of males (approximately 70%) in the EPP, pituitary hypoplasia, stalk defects, and triad categories. CONCLUSION: This large, international database demonstrates the value of classification of GH-deficient patients by the presence and type of hypothalamic-pituitary imaging abnormalities. This information may assist family counseling and patient management.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it