Neurodevelopmental outcome descriptions in cohorts of extremely preterm children
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Caregivers and clinicians of extremely preterm infants (born before 26 weeks' gestation) depend on long-term follow-up research to inform clinical decision-making. The completeness of outcome reporting in this area is unknown. The objective of this study was to evaluate the reporting of outcome definitions, selection, measurement and analysis in existing cohort studies that report on neurodevelopmental outcomes of children born extremely preterm. METHODS: We evaluated the completeness of reporting of 'cognitive function' and 'cerebral palsy' in prospective cohort studies summarised in a meta-analysis that assessed the effect of preterm birth on school-age neurodevelopment. Outcome reporting was evaluated using a checklist of 55 items addressing outcome selection, definition, measurement, analysis, presentation and interpretation. Reporting frequencies were calculated to identify strengths and deficiencies in outcome descriptions. RESULTS: All 14 included studies reported 'cognitive function' as an outcome; nine reported both 'cognitive function' and 'cerebral palsy' as outcomes. Studies reported between 26% and 46% of the 55 outcome reporting items assessed; results were similar for 'cognitive function' and 'cerebral palsy' (on average 34% and 33% of items reported, respectively). Key methodological concepts often omitted included the reporting of masking of outcome assessors, methods used to handle missing data and stakeholder involvement in outcome selection. CONCLUSIONS: The reporting of neurodevelopmental outcomes in cohort studies of infants born extremely preterm is variable and often incomplete. This may affect stakeholders' interpretation of study results, impair knowledge synthesis efforts and limit evidence-based decision-making for this population.
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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 | 0.310 | 0.604 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.009 |
| Bibliometrics | 0.014 | 0.011 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| 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".