Evaluating the Prevalence of Optimal Neurodevelopmental Outcome at 2 Years in Children Previously on Ventricular Assist Device Support
Bibliographic record
Abstract
Background Literature reporting neurodevelopmental outcomes for patients who undergo ventricular assist device (VAD) therapy is limited to posttransplant cohorts. This study aims to determine the prevalence of optimal neurodevelopmental outcome and factors associated with nonoptimal outcome in patients implanted with a VAD at ≤15 months of age. Methods Patients followed by the Complex Pediatric Therapies Follow‐Up Program were included in a prospective‐inception cohort study if born between January 2006 and December 2022 and implanted with a VAD at ≤15 months of age. A modified optimal neurodevelopmental outcome was defined as scores of ≥80 on the Bayley Scales of Infant and Toddler Development and on the Adaptive Behavior Assessment System, and in the absence of cerebral palsy, permanent hearing loss, visual impairment, or seizure disorder. Firth multiple regression analysis was used to determine independent factors associated with nonoptimal outcome. Results A total of 56 patients underwent VAD implant at ≤15 months with neurodevelopmental assessments available for 39/40 patients who survived to 2 years. The mean age of VAD implant was 5.45 (SD 3.99) months, 69.2% were male, and 38.5% had congenital heart disease. Optimal neurodevelopmental outcome was seen in 25.6% of patients. Neurological insult (OR, 12.34 [95% CI, 1.29–1660.36], P =0.026) was the only independent factor identified associated with nonoptimal outcome. Conclusions Optimal outcome was demonstrated in one quarter of patients who had a VAD at ≤15 months of age and underwent neurodevelopmental testing at 2 years of age. A potentially modifiable factor of neurological insult was demonstrated as being independently associated with nonoptimal outcome.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".