25 More than meets the eye: Parental perspectives on the health of their extremely preterm children when they reach 18 months, 5 and 7 years
Bibliographic record
Abstract
Abstract Background Extremely preterm birth is associated with death and a higher risk of adverse long-term outcomes. Neurodevelopmental impairment (NDI) has become the focus of neonatal follow-up and outcome research, with classifications chosen by clinicians and researchers. However, parents were never consulted about this classification. Objectives To examine parental perspectives about the health of their ex-preterm infants. Design/Methods Over a one-year period, at Sainte-Justine University Hospital’s Neonatal Follow-Up Clinic, all parents of children born <29 weeks’ gestational age, aged between 18 months corrected age and 7 years were approached. They were asked two questions: “Please rate your child’s health from your point of view on a scale from 0 (very poor) to 10 (excellent)” and “If you could improve up to two things about your child’s health and/or development, what would they be?” Responses were analyzed using mixed methods. Results 249 parental responses were obtained (98% participation rate). On average, parents rated their child’s health to be 8/10 (range 3-10/10, median 8/10). Main themes invoked about areas for improvement were developmental outcomes (65%):“if he could talk and hold his head up himself”; respiratory heath and overall medical fragility (35%): “improve the health of her lungs”; and behavior/emotional issues (21%): “his anxiety”. Twenty-three percent did not wish to improve anything: “I am very happy with his health and development. I hope he continues on the same path.” When examining developmental outcomes more closely, the recurrent sub-themes for improvement were: language/communication (22%), motor/movement (17%) and cognitive/learning (16%): “improving her attention in school”. Conclusion When they come to neonatal follow-up, parents generally perceive the health of their extremely preterm children in a positive way. While some parents have no wishes for improvement in their children, many are concerned by their children’s NDI. On the other hand, several parent-important outcomes, such as lung health and overall medical fragility, are insufficiently investigated during follow-up at the present time.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".