Which growth standards should be used to identify large- and small-for-gestational age infants of mothers with type 1 diabetes? A pre-specified analysis of the CONCEPTT trial
Bibliographic record
Abstract
Abstract BackgroundOffspring of women with type 1 diabetes are at increased risk of accelerated fetal growth which is associated with perinatal morbidity. Growth standards are used to identify large- or small- for gestational age (LGA, SGA) infants. Our aim was to examine which growth standards identify infants at risk of perinatal complications during the Continuous Glucose Monitoring in Type 1 Diabetes Pregnancy Trial (CONCEPTT).MethodsThis was a pre-specified analysis of CONCEPTT involving 225 pregnant women from 31 international centres. Infants were weighed immediately at birth and GROW, INTERGROWTH and WHO centiles calculated. Unadjusted logistic regression identified the associations between different growth standards and perinatal outcomes including preterm delivery, Caesarean delivery, neonatal hypoglycaemia, hyperbilirubinaemia, respiratory distress, neonatal intensive care unit (NICU) admission and a composite neonatal outcome. ResultsAccelerated fetal growth was common, with mean birthweight percentiles of 82.1, 85.7 and 63.9 and LGA rates of 62%, 67% and 30% using GROW, INTERGROWTH and WHO standards respectively. Corresponding rates of SGA were 2.2%, 1.3% and 8.9% respectively. All standards were associated with some but not all perinatal outcomes studied. Infants born >97.7th centile using GROW or INTERGROWTH standards were at highest risk of complications. Conclusions WHO standards underestimated birthweight centile. GROW and INTERGROWTH standards identified similar numbers of infants as LGA and SGA with GROW showing stronger associations with neonatal hypoglycaemia, hyperbilirubinaemia and NICU admission. Infants with suspected birthweight >97.7th centile using GROW or INTERGROWTH standards may require extra surveillance. Definitions of LGA and SGA should be re-evaluated in diabetic pregnancy. Trial registration: This trial is registered with ClinicalTrials.gov. number NCT01788527.
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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 | 0.021 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".