One-minute and five-minute Apgar scores and child developmental health at 5 years of age: a population-based cohort study in British Columbia, Canada
Bibliographic record
Abstract
OBJECTIVES: We investigated the associations between Apgar scores at 1 and 5 min, across the entire range of score values, and child developmental health at 5 years of age. SETTING: British Columbia, Canada PARTICIPANTS: All singleton term infants without major congenital anomalies born between 1993 and 2009, who had a developmental assessment in kindergarten between 1999 and 2014. MAIN OUTCOMES AND MEASURES: Developmental vulnerability on one or more domains of the Early Development Instrument and special needs requirements. Adjusted rate ratios (aRRs) and 95% CIs were estimated using log-linear regression. RESULTS: Of the 150 081 children in the study, 45 334 (30.2%) were developmentally vulnerable and 3644 (2.5%) had special needs. There was an increasing trend in developmental vulnerability and special needs with decreasing 1 min and 5 min Apgar scores. Compared with children with an Apgar score of 10 at 5 min, the aRR for developmental vulnerability increased steadily with decreasing Apgar score from 1.02 (95% CI 1.00 to 1.04) for an Apgar score of 9 to 1.57 (95% CI 1.03 to 2.39) for an Apgar score of 2. Among children with 1 min Apgar scores in the 7-10 range, changes in Apgar scores between 1 and 5 min were associated with significant differences in developmental vulnerability. Compared with children who had an Apgar score of 9 at 1 min and 10 at 5 min, children with an Apgar score of 9 at both 1 and 5 min had higher rates of developmental vulnerability (aRR 1.03, 95% CI 1.01 to 1.05). Compared with infants with an Apgar of 10 at both 1 and 5 min, infants with a 1 min score of 10 and a 5 min score of <10 had higher rates of developmental vulnerability (aRR 1.53, 95% CI 1.08 to 2.17). CONCLUSION: Risks of adverse developmental health and having special needs at 5 years of age are inversely associated with 1 min and 5 min Apgar scores across their entire range.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".