Epidemiology of Posthemorrhagic Ventricular Dilatation in Canadian Neonatal Intensive Care Units
Bibliographic record
Abstract
Abstract BACKGROUND: Severe intraventricular hemorrhage (IVH) is a common cause of neonatal morbidity and mortality .The incidence and management of post-hemorrhagic ventricular dilatation (PHVD) vary among different centres. OBJECTIVES: To assess the incidence, temporal trend, management and associated outcomes of PHVD in Canadian NICUs. DESIGN/METHODS: We conducted a retrospective review of all pre-term infants (22+0 -32+6 weeks) who were admitted to NICUs participating in the Canadian Neonatal Network between 2010 and 2014. Infants with severe IVH (IVH with ventricular dilatation or parenchymal bleeding) who survived ≥ 72 hours were included. We compared the rates of severe IVH, PHVD and VP shunting between the 5 Canadian regions. Short-term outcomes of infants who developed PHVD (ventricles size ≥10 mm) were compared with those who did not. RESULTS: Of 16600 eligible infants, 1964 (11.8%) developed severe IVH. Of 1815 infants with severe IVH who survived ≥72 hours, 616 (34%) developed PHVD and 91 (5%) treated with VP shunt. No significant difference in the incidence of severe IVH, PHVD or VP shunting over the last five years was noted. There was a statistically significant difference in the rates of severe IVH (p<0.0001) and PHVD (p=0.02) among the 5 Canadian regions. VP shunts rates were variable with some Canadian regions with higher rates of PHVD had low rates of VP shunts. [figure 1]. Infants with PHVD had significantly higher mortality and short term morbidities. [table 1]. On regression analysis, PHVD is an independent predictor of death in infants with severe IVH [adjusted OR 1.55, 95% CI (1.18, 2.04)]. Infants with VP shunt had significantly higher rates of severe ROP (p<0.0001), meningitis (p<0.0001), and hospitalization (89 vs 41 days, p<0.0001). CONCLUSION: PHVD is an independent predictor of death and is associated with adverse short- term outcomes. Variability exists between different regions in managing PHVD. Further studies are needed to investigate the impact of this variability on long-term outcomes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 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".