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A multicenter study on interpretable machine learning models predicting the efficacy of growth hormone therapy for dwarfism

A multicenter study on interpretable machine learning models predicting the efficacy of growth hormone therapy for dwarfism

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500103089
Enrollment
Unknown
Registered
2025-05-23
Start date
2025-01-01
Completion date
Unknown
Last updated
2025-05-26

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

short stature

Interventions

Sponsors

Jinan Second Maternal and Child Health Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
3 Years to 18 Years

Inclusion criteria

Inclusion criteria: Inclusion criteria: Age between 3-18 years old, height below the 3rd percentile of the growth curve or 2 standard deviations below the mean of normal healthy children of the same age and gender, diagnosed with growth hormone deficiency, idiopathic short stature, hereditary short stature, skeletal developmental abnormalities, chronic diseases, etc. through endocrine examination, receiving rhGH treatment and regular follow-up for at least one year.

Exclusion criteria

Exclusion criteria: Exclusion criteria: Children with severe organ dysfunction, severe infectious or malignant diseases, severe mental or behavioral disorders, severe concomitant adverse drug reactions, and other factors affecting growth and development who do not cooperate with the study or follow-up.

Design outcomes

Primary

MeasureTime frame
Accuracy of the model;ROC;

Secondary

MeasureTime frame
age ;height;Growth hormone levels;Thyroid Function;Sex hormone levels;Bone Age;

Countries

China

Contacts

Public ContactJunqing li

Jinan Second Maternal and Child Health Hospital

964427679@qq.com+86 151 6344 2503

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026