Determinants of survival in children with congenital abnormalities: A long-term population-based cohort study
Bibliographic record
Abstract
BACKGROUND: Today more children with birth defects survive early childhood because of improved medical care; however, little information is available about patterns of long-term mortality and survival in this population. In particular, it is not clear whether other birth characteristics, apart from birth defects, have any role in their mortality. METHODS: Two large cohorts of children with and without birth defects were followed for up to 17 years. More than 45,000 children with birth defects, and 45,000 matched children without birth defects born in Ontario between 1979 and 1986 were followed. Throughout the study period long-term survival rates and the risk of death were compared between the 2 cohorts. Birth characteristics were also examined to determine their effect on the risk of death. RESULTS: During the study the deaths of 3620 and 301 children with and without birth defects, respectively, were recorded, indicating that those with birth defects had a 13 times higher rate of mortality (relative risk [RR], 12.9, 95% confidence interval [CI], 12.1-13.7). Mortality rates in the birth-defects cohort remained higher even after 10-15 years. In both groups children of low gestational age and low birth weight had a higher risk of death. There was a strong dose-response relationship between the number of defects and the risk of death. CONCLUSIONS: Children born with abnormalities face many challenges throughout their lifetimes. If they survive the high mortality risk of the first year of life, they still have to face the considerably higher risk of death in the years to come. In addition to birth defects, other birth characteristics play an independent role in their mortality. These indicators could be used to identify high-risk children.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".