A New IVH Scoring System Based on Laterality Enhances Prediction of Neurodevelopmental Outcomes at 3 Years Age in Premature Infants
Bibliographic record
Abstract
Objective To compare the new intraventricular hemorrhage (IVH) Abdi score to the Papile grading system of IVH for prediction of composite outcome of death or neurodevelopmental impairment (NDI). Methods In a cohort study, all preterm infants with IVH who were born ≤1,250 g and/or ≤ 28 weeks of gestation at birth were prospectively followed up in our neonatal follow-up clinic. All cranial ultrasounds of the included infants were reviewed by neuroradiologists who were blinded to the clinical data and neurodevelopmental outcomes. Cranial ultrasounds were graded according to the Papile scoring system and by calculation of the Abdi score. Results A total of 183 preterm infants met inclusion and exclusion criteria. Of these, 80 (44%) had the composite primary outcome of death or NDI (51 died, 29 survived with NDI). The area under receiver operating characteristic curve for predicting death or NDI was 0.87 (95% confidence interval [CI]: 0.81–0.93) for Abdi score and 0.85 (95% CI: 0.79–0.91) for Papile grading ( p = 0.04). Abdi scores had higher specificity than Papile grade II at Abdi score 5 (63.9 vs. 39.2%; p < 0.001) and Abdi score 6 (73.2 vs. 39.2%; p < 0.001). Conclusion Abdi scores seem to be more specific than Papile grading system in predicting death or NDI by 3 years' corrected age.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".