Diagnosis, Genetics, and Therapy of Short Stature in Children: A Growth Hormone Research Society International Perspective
Bibliographic record
Abstract
The Growth Hormone Research Society (GRS) convened a Workshop in March 2019 to evaluate the diagnosis and therapy of short stature in children. Forty-six international experts participated at the invitation of GRS including clinicians, basic scientists, and representatives from regulatory agencies and the pharmaceutical industry. Following plenary presentations addressing the current diagnosis and therapy of short stature in children, breakout groups discussed questions produced in advance by the planning committee and reconvened to share the group reports. A writing team assembled one document that was subsequently discussed and revised by participants. Participants from regulatory agencies and pharmaceutical companies were not part of the writing process. Short stature is the most common reason for referral to the pediatric endocrinologist. History, physical examination, and auxology remain the most important methods for understanding the reasons for the short stature. While some long-standing topics of controversy continue to generate debate, including in whom, and how, to perform and interpret growth hormone stimulation tests, new research areas are changing the clinical landscape, such as the genetics of short stature, selection of patients for genetic testing, and interpretation of genetic tests in the clinical setting. What dose of growth hormone to start, how to adjust the dose, and how to identify and manage a suboptimal response are still topics to debate. Additional areas that are expected to transform the growth field include the development of long-acting growth hormone preparations and other new therapeutics and diagnostics that may increase adult height or aid in the diagnosis of growth hormone deficiency.
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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 | 0.012 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 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".