Perinatal Regionalization and Implications for Long-Term Health Outcomes in Cerebral Palsy
Bibliographic record
Abstract
BACKGROUND: Perinatal regionalization is linked to improved neonatal outcomes; however, the effects on long-term outcomes in cerebral palsy (CP) are not known. We estimate the effect of highest levels of neonatal care available at delivery on the risk of developing a nonambulatory CP status. METHODS: Children with CP born in Quebec from the Canadian CP Registry excluding postneonatal causes were included (N=360). We estimate the effect of level of care available at delivery on risk of nonambulatory status among children with CP using propensity score matching and instrumental variables methods to adjust for differences in case mix among the three groups of hospitals. The outcome variable is an indicator for CP nonambulation assigned according to Gross Motor Function Classification System (levels IV and V). This study used data that predated therapeutic hypothermia in Quebec. RESULTS: Propensity score estimates of change in the adjusted risk of having a nonambulatory CP status because of birth at level II versus level I is -0.081, 95% confidence interval (CI; -0.2182 to 0.0562); level III versus level I is -0.072 95% CI (-0.225 to 0.08), and level III versus level II is 0.157 95% CI (0.027 to 0.286). CONCLUSIONS: Differences in levels of neonatal care available at hospital where the delivery was carried out are not associated with the risk of a nonambulatory CP phenotype. This suggests that level of care and associated medical technology within the Quebec regionalized neonatal-perinatal system is used efficiently because it does not offer any further marginal benefit in the reduction of severe CP outcomes. The system works well as it is, which is supportive of the perinatal regionalization. The success of the neonatal resuscitation program and referral of high-risk births to regional hospitals with sufficient obstetric and perinatal competence and resources may contribute to this lack of variability.
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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 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".