A Case of Functional Growth Hormone Deficiency and Early Growth Retardation in a Child With IFT172 Mutations
Bibliographic record
Abstract
CONTEXT: Ciliopathies are a group of rare conditions that present through a wide range of manifestations. Given the relative common occurrence of defects of the GH/IGF-I axis in children with short stature and growth retardation, the association between ciliopathies and these defects needs further attention. CASE: Our patient is a boy who was born at term and noted to have early growth retardation and weight gain within the first 18 months of life. Biochemical tests demonstrated low IGF-I but a normal peak GH on stimulation and an adequate increase in IGF-I on administration of recombinant human growth hormone (rhGH). A magnetic resonance imaging scan revealed pituitary hypoplasia and an ectopic posterior pituitary. His growth responded well to rhGH therapy. Subsequently he also developed a retinopathy of his rods and cones, metaphyseal dysplasia, and hypertension with renal failure requiring renal replacement therapy. Whole-exome sequencing demonstrated compound heterozygous mutations of IFT172, thus consistent with a ciliopathy. CONCLUSIONS: This is the first reported case of a child with a mutation in IFT172 who presented with growth retardation in early childhood and was initially managed as a case of functional GH deficiency that responded to rhGH therapy. This case highlights the importance of ciliary function in pituitary development and the link between early onset growth failure and ciliopathies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| 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".