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Abstract 4146813: Evaluating the Prevalence of Optimal Neurodevelopmental Outcome at 2 Years in Children Previously on VAD Support

2024· article· en· W4404381828 on OpenAlexaff
Jennifer Conway, Holger Buchholz, Darren H. Freed, Mohammed Al Aklabi, D. Jonker, Ari R. Joffe, Simon Urschel, Tara Pidborochynski, Joseph Atallah, Charlene M.T. Robertson

Bibliographic record

VenueCirculation · 2024
Typearticle
Languageen
FieldEngineering
TopicMechanical Circulatory Support Devices
Canadian institutionsUniversity of AlbertaStollery Children's Hospital
Fundersnot available
KeywordsMedicineOutcome (game theory)PediatricsIntensive care medicine

Abstract

fetched live from OpenAlex

Background: Ventricular assist devices (VADs) are becoming a standard part of advanced heart failure therapy in children. They are utilized mostly as a bridge to transplant (HTx) but also can be used for recovery. While information on complications during VAD therapy is available, there is limited information on long term outcomes in this patient population, specifically neurodevelopmental outcomes. Research Question: To determine the prevalence of ‘optimal neurodevelopmental outcomes’ in 2-year-old children previously treated with a VAD. Methods: Patients were followed through the Complex Pediatric Therapies Follow-Up Program. This study included patients born between January 2006 and December 2022, implanted with a VAD at < 15 months of age and surviving to 2 years of age. A modified optimal neurodevelopmental outcome was defined as the Cognitive, Language and Motor Composite Scores on the Bayley Scales of Infant and Toddler Development and the Adaptive Behaviour Assessment System - General Adaptive Composite Score ≥ 80 each, with the absence of cerebral palsy, permanent hearing loss, visual impairment, or seizure disorder. Results: There were 56 patients who met inclusion criteria with 40 patients surviving to the age of 2 years. Of the survivors, the median (IQR) gestational age (GA) was 38 [37, 39] (4 [7.1%] <37completed weeks GA), 70% were male and 7.5% had a chromosomal abnormality. The median age of implant was 0.39 [0.19, 0.64], years and weight 5.8Kg [4.1, 7.5]. The majority of patients did not have congenital heart disease (62.5%). The most common implant strategy was a left VAD (87.5%) with paracorporeal continuous support (42.5%). Most patients were supported with ECMO (55%) pre- or post-VAD implant. One-third of the cohort had a neurological insult either pre- or post-implant. Total duration of support was a median 32 days [8, 93] with 65% undergoing HTx and 35% decannulated for recovery. Thirty-nine patients underwent full neurodevelopmental testing at 2 years of age with only 25.6% (n=19) of the patients classified as having an optimal neurodevelopmental outcome with 43.6% (n=17) having a Bayley cognitive score <80. Conclusion: Optimal neurodevelopmental outcome at 2 years of age was present in only one-quarter of children following a treatment pathway that included VAD therapy in infancy. Important next steps will be to identify associations, including modifiable risk factors, for optimal neurodevelopmental outcomes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.035
GPT teacher head0.293
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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