International trends of Down syndrome 1993–2004: Births in relation to maternal age and terminations of pregnancies
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to examine trends of Down syndrome (DS) in relation to maternal age and termination of pregnancies (ToP) in 20 registries of the International Clearinghouse for Birth Defects Surveillance and Research (ICBDSR). METHODS: Trends of births with DS (live-born and stillborn), ToP with DS, and maternal age (percentage of mothers older than 35 years) were examined by year over a 12-year period (1993-2004). The total mean number of births covered was 1550,000 annually. RESULTS: The mean percentage of mothers older than 35 years of age increased from 10.9% in 1993 to 18.8% in 2004. However, a variation among the different registers from 4-8% to 20-25% of mothers >35 years of age was found. The total mean prevalence of DS (still births, live births, and ToP) increased from 13.1 to 18.2/10,000 births between 1993 and 2004. The total mean prevalence of DS births remained stable at 8.3/10,000 births, balanced by a great increase of ToP. In the registers from France, Italy, and the Czech Republic, a decrease of DS births and a great increase of ToP was observed. The number of DS births remained high or even increased in Canada Alberta, and Norway during the study period. CONCLUSIONS: Although an increase in older mothers was observed in most registers, the prevalence of DS births remained stable in most registers as a result of increasing use of prenatal diagnostic procedures and ToP with DS.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".