Abstract 13524: Examining Variation in Interstage Mortality Rates Across the National Pediatric Cardiology Quality Improvement Collaborative: Do Lower Mortality Centers Have Lower Risk Patients?
Bibliographic record
Abstract
Introduction: Although overall interstage mortality for infants with hypoplastic left heart syndrome has declined within the National Pediatric Cardiology Quality Improvement Collaborative (NPC-QIC), variation in outcomes across centers persists. It remains unclear whether centers with lower mortality rates have lower risk interstage patients or whether differences in the type of interstage care provided may explain this variation. We examined previously established patient risk factors across NPC-QIC centers with higher and lower interstage mortality rates. Methods: Lower mortality NPC-QIC centers were defined as those with >25 consecutive interstage survivors, and included 7 centers. Higher mortality centers were defined as those with cumulative interstage mortality rates greater than the NPC-QIC historic baseline rate (>10%), and included 4 centers. Patient risk factors were compared between lower and higher mortality centers, accounting for within center clustering. Results: The 7 lower mortality centers (n=331 patients) had a lower interstage mortality rate of 2.7% compared to 13.3% in the 4 higher mortality centers (n=173 patients); p<0.0001. Post-natal diagnosis was the only risk factor less prevalent in the lower mortality centers (Figure) compared to higher mortality centers (18.4% vs. 31.8%, p=0.04). All other risk factors examined were either similar between the lower and higher mortality centers (including gestational age, anatomic diagnoses, birth weight), or more prevalent in the lower mortality centers (major syndrome- 6.9% vs. 4.0%, p=0.03; major anomalies- 7.3% vs. 4%, p=0.047). Conclusions: Differences in interstage mortality rates among NPC-QIC centers do not appear to be explained by a lower rate of patient risk factors in lower mortality centers. Further study is necessary to evaluate differences in interstage care practices across centers in order to identify targets for efforts to reduce variation and improve 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 | 0.008 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".