Mucopolysaccharidosis Type I Disease Prevalence Among Patients With Idiopathic Short Stature in Saudi Arabia: Protocol for a Multicenter Cross-sectional Study
Bibliographic record
Abstract
BACKGROUND: Since the underlying cause of idiopathic short stature can indeed be undiagnosed mucopolysaccharidosis type I, it is critical to identify patients with mucopolysaccharidosis type I among screened patients with idiopathic short stature. OBJECTIVE: The primary objective of this study is to determine the prevalence of mucopolysaccharidosis type I disease in a high-risk group (ie, patients with idiopathic short stature). METHODS: We plan to perform a multicenter, cross-sectional screening study to primarily assess the prevalence of mucopolysaccharidosis type I disease in patients with idiopathic short stature. All eligible patients will be tested after obtaining written informed consent from their parents and guardians. Eligible patients will be recruited over 18 months from specialty care centers for pediatrics and genetics. RESULTS: This protocol was approved by the Institutional Review Board of King Fahd Medical City and funded by Sanofi Genzyme Saudi Arabia. We expect to collect data from ≥800 patients, as determined by our sample size calculation. CONCLUSIONS: Saudi Arabia is the largest country in the Arabian Peninsula; it has a population of more than 28 million people. To date, there are no reliable data regarding the incidence and prevalence of mucopolysaccharidosis type I in Saudi Arabia; therefore, future multicenter studies will be needed. Further, the prevalence of an attenuated form of mucopolysaccharidosis type I is largely underestimated in Saudi Arabia due to the absence of an effective newborn screening program. Therefore, the implementation of a nationwide newborn screening program is essential for the accurate estimation of the burden of mucopolysaccharidosis and the early diagnosis of patients. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/28619.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".