Expanded Newborn Screening Program in Saudi Arabia: Incidence of screened disorders
Bibliographic record
Abstract
AIM: To address the implementation of the National Newborn Screening Program (NBS) in Saudi Arabia and stratify the incidence of the screened disorders. METHODS: A retrospective study conducted between 1 August 2005 and 31 December 2012, total of 775 000 newborns were screened from 139 hospitals distributed among all regions of Saudi Arabia. The NBS Program screens for 16 disorders from a selective list of inborn errors of metabolism (IEM) and endocrine disorders. Heel prick dry blood spot samples were obtained from all newborns for biochemical and immunoassay testing. Recall screening testing was performed for Initial positive results and confirmed by specific biochemical assays. RESULTS: A total of 743 cases were identified giving an overall incidence of 1:1043. Frequently detected disorders nationwide were congenital hypothyroidism and congenital adrenal hyperplasia with an incidence of 1:7175 and 1:7908 correspondingly. The highest incidence among the IEM was propionic acidaemia with an incidence rate of 1:14 000. CONCLUSION: The article highlights the experience of the NBS Program in Saudi Arabia and providing data on specific regional incidences of all the screened disorders included in the programme; and showed that the incidence of these disorders is one of the highest reported so far world-wide.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".