Impact of Patient Characteristics and Clinical Factors on the Decision to Initiate Growth Hormone Treatment in Turner Syndrome
Bibliographic record
Abstract
BACKGROUND/AIMS: To evaluate factors contributing to the decision to initiate treatment with growth hormone (GH) in patients with Turner syndrome (TS). METHODS: Data collected included ethnicity, parents' education and work status, mid-parental height, age at diagnosis, karyotype, pubertal development, clinical severity score, bone age, height SDS and ages when GH was proposed and initiated. RESULTS: GH was proposed to 59 of 72 patients >6 years (82%), and of these 46 (78%) accepted. Reasons for not proposing GH included late diagnosis, good growth and loss to follow-up. GH-treated and untreated girls differed by age at diagnosis (mean +/- SD: 6.8 +/- 4.7 vs. 4.3 +/- 5.1 years; p = 0.04), TS-specific height SDS (0.08 +/- 0.81 vs. 066 +/- 0.87; p = 0.01) and spontaneous puberty (5/46 vs. 4/26, p = 0.024). Mean age at which it was suggested to begin GH was 9.2 +/- 2.9 years. Reasons for parental refusal of GH were not related to reimbursement issues since GH treatment is covered fully by our insurance plan but included concern with other medical issues, mental health problems and fear of injections or unknown side effects. CONCLUSION: GH treatment was not acceptable to all patients with TS.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".