Parent-reported health in extremely preterm and extremely low-birthweight children at age 8 years compared with comparison children born at term
Bibliographic record
Abstract
AIM: Extremely preterm and extremely low-birthweight (EP/ELBW) children (<28 completed weeks' gestation; birthweight <1000g) have a high risk of long-term adverse outcomes. Clinical developmental surveillance is difficult to achieve for all of these children. Our aim was to study the ability of two parent-completed questionnaires to differentiate health status of EP/ELBW children from that of a comparison group of children born at term, and to screen EP/ELBW children for disability compared with the ability of a multidisciplinary clinical assessment. METHOD: A geographic cohort of 189 EP/ELBW children (100 males, 89 females) and a comparison group of 173 term children (92 males, 81 females) born in 1997 were assessed at the age of 8 years using parent questionnaires (the Child Health Questionnaire [CHQ] and the Health Utilities Index Mark 2 [HUI2]) and a multidisciplinary clinical assessment. The questionnaires and clinical assessment were compared with respect to their ability to differentiate between the health status of EP/ELBW children and children born at term and also to identify children with a disability. RESULTS: The HUI2 was better than the CHQ at differentiating the health status of EP/ELBW and comparison children. Moderate and severe disability status were identified by the HUI2 with sensitivity ranging from 86 to 97%, specificity from 60 to 64%, positive predictive values from 34 to 39%, and negative predictive values from 95 to 99%. INTERPRETATION: The HUI2 had suitable sensitivity and specificity to be used as a developmental screening tool for EP/ELBW children, but the CHQ did not. Given its low positive predictive values, however, the HUI2 should be viewed with caution as a final outcome measure for intervention trials, and would be better used to identify at-risk children who need a definitive clinical assessment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".