CHIPS-Child: Testing the developmental programming hypothesis in the offspring of the CHIPS trial
Bibliographic record
Abstract
OBJECTIVES: As a follow-up to the CHIPS trial (Control of Hypertension In Pregnancy Study) of 'less tight' (versus 'tight') control of maternal blood pressure in pregnancy, CHIPS-Child investigated potential developmental programming of maternal blood pressure control in pregnancy, by examining measures of postnatal growth rate and hypothalamic-pituitary adrenal (HPA) axis activation. METHODS: CHIPS follow-up was extended to 12 ± 2 months corrected post-gestational age for anthropometry (weight, length, head/waist circumference). For eligible children with consent for a study visit, we collected biological samples (hair/buccal samples) to evaluate HPA axis function (hair cortisol levels) and epigenetic change (DNA methylation analysis of buccal cells). The primary outcome was 'change in z-score for weight' between birth and 12 ± 2 mos. Secondary outcomes were hair cortisol and genome-wide DNA methylation status. RESULTS: = 0.06]; median (95% confidence interval) hair cortisol (N = 35 samples) was lower [-496 (-892, -100) ng/g; p = 0.02], and buccal swab DNA methylation (N = 16 samples) was similar. No differences in growth rate could be demonstrated up to 5 years. CONCLUSIONS: Results demonstrate no compelling evidence for developmental programming of growth or the HPA axis. Clinicians should look to the clinical findings of CHIPS to guide practice. Researchers should seek to replicate these findings and extend outcomes to paediatric blood pressure and neurodevelopment.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.004 | 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".