386 A Count of three Neonatal Morbidities may Substitute for Long-Term Neurodevelopmental follow-up in very Low Birth Weight (VLBW) Infants
Bibliographic record
Abstract
Background In very preterm infants who survive to a postmenstrual age (PMA) of 36 weeks, a count of BPD, brain injury and severe ROP predicts the risk of a later death or neurosensory impairment at 18 months (JAMA 2003; 289:1124). Objective To validate this count of 3 neonatal morbidities as a predictor of poor long-term outcome in VLBW infants who participated in the CAP Trial. Methods Five-year follow-up of 1514 CAP trial participants who survived to a PMA of 36 weeks. Poor outcome was a late death or survival with one or more disabilities. Results The incidences of BPD, brain injury and severe ROP were 40%, 13%, and 6.0%, respectively. Each morbidity was similarly and independently correlated with a poor 5-year outcome. Table 1 shows the risks of a poor long-term outcome with none, any 1, any 2, and all 3 neonatal morbidities. Conclusions In VLBW infants who survive to a PMA of 36 weeks, a count of BPD, brain injury and severe ROP predicts the risk of a later death or survival with disability at age 5 years. This morbidity count may substitute for long-term outcome assessments in very preterm infants whose families do not comply with neurodevelopmental follow up.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".