Grade 3 school performance among children born preterm: a population-based cohort study
Bibliographic record
Abstract
OBJECTIVE: To study the association between prematurity and grade 3 school performance in a contemporary cohort of children. METHODS: Population-based retrospective cohort study in Manitoba, Canada. Children born between 1999 and 2011 who had their grade 3 school performance data available were eligible. Preterm birth (<37 weeks) was the exposure of interest assessed using multivariable logistic regression models. Our primary outcomes were 'needs ongoing help' or 'outside the range' in at least two of each of the (1) four numeracy and (2) three reading competencies. RESULTS: Of the 186 956 eligible children, 101 436 children (7187 preterm (gestational age, median (IQR) 35 weeks (34, 36)) and 94 249 term (40 weeks (39,40)) were included. Overall, 19% of preterm and 14% of term children had the numeracy outcome (adjusted OR (aOR) 1.38; 95% CI 1.29 to 1.47, p<0.001), while 19% and 13% had the reading outcome (aOR 1.38; 1.29 to 1.48, p<0.001). These differences showed a gestational age gradient. Gestational age (for numeracy, <28 weeks aOR 4.93 (3.45 to 7.03), 28-33 weeks 1.72 (1.50 to 1.98), 34-36 weeks 1.24 (1.15 to 1.34); for reading, <28 weeks 3.51 (2.40 to 5.14), 28-33 weeks 1.72 (1.49 to 1.98), 34-36 weeks 1.24 (1.17-1.37)), male sex, small for gestational age and maternal medical and sociodemographic factors were associated with the numeracy and reading outcomes in this cohort. CONCLUSIONS AND RELEVANCE: Children born preterm had poorer performance in grade 3 numeracy and reading proficiencies than children born full term. All children born preterm, not just those born extremely preterm, should be screened for reading and numeracy performance in school and strategies implemented to address any deficits.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".