Medical issues among children and teenagers with Down syndrome in Hong Kong
Bibliographic record
Abstract
UNLABELLED: We examined the prevalence of medical problems in children and teenagers with Down syndrome in Hong Kong. METHODS: Children with Down syndrome receiving care from seven regional hospitals were included and their hospital records were reviewed. A total of 407 patients, aged between 0.06 and 17.16 years were included. Cardiovascular problems were observed in 216 (53%), endocrine problems in 111 (27%), gastrointestinal problems in 46 (11%), haematological problems in 18 (4%), neurological problems in 27 (7%), sleep problems in 36 (9%), skeletal problems in 56 (14%), visual problems in 195 (48%) and auditory problems in 137 (34%). CONCLUSIONS: The prevalence of medical problems was high in children and teenagers with Down syndrome in Hong Kong and similar to previous findings elsewhere. Future studies on the local prevalence of medical problems in the adult population with Down syndrome would help to define their medical needs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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 teacher head, 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".