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Abstract 4355216: Nonlinear mixed effect modeling of natriuretic peptides and associations with clinical events in interstage infants with single ventricle heart disease

2025· article· en· W4415793851 on OpenAlexaff
Elizabeth J. Thompson, Rodrigo Gonzalez Ramirez, Anil R. Maharaj, Henry P. Foote, Karan R. Kumar, Kiona Y. Allen, Alexis Benscoter, Chi D. Hornik, Erica Del Grippo, Brett R. Anderson, Danyal Khan, John Costello, Denise Suttner, Pirooz Eghtesady, Nancy Halnon, Christoph Hornik

Bibliographic record

VenueCirculation · 2025
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBiomarkerNatriuretic peptideVentricleClinical endpointBrain natriuretic peptideProspective cohort studyCohortHeart failureHeart disease

Abstract

fetched live from OpenAlex

Introduction: Infants with single ventricle disease experience high morbidity and mortality, especially in the interstage period between the first and second palliative surgery. Identifying high-risk infants may prompt interventions and improve outcomes. Myocardial stress or stretch triggers release of natriuretic peptides (N-terminal pro-brain natriuretic peptide [NTproBNP]; mid-regional pro-atrial natriuretic peptide [MRproANP]) that may be used as biomarkers. We modeled longitudinal biomarker trajectories and aimed to understand how these relate to clinical events in interstage infants. Methods: We prospectively collected biomarker samples from interstage infants enrolled in a prospective, multicenter study (NCT03877965), excluding preterm infants, those with creatinine >2mg/dL, and those on extracorporeal support. We performed nonlinear mixed effect modeling in NONMEM to describe the two phases of biomarker decline and evaluated covariate effects. We explored associations between model parameters, biomarker concentrations, and clinical events. Results: Across 10 sites, 50 infants contributed 142 MRproANP and 151 NTproBNP plasma samples in the interstage period. Table 1 shows cohort characteristics and clinical events. There was a >15x faster decline in biomarker concentrations in the first month after stage 1 palliation (S1P) which then slowed ( Figure 1A ). A biexponential model ( Table 2 ) with fast and slow elimination phases after S1P best described these trajectories. The coefficient of the slow elimination phase (ECH) of both biomarkers trended higher for in infants who died (median [range] MRproANP 610 [593, 628] v 492 [329, 1309] pmol/L; p=0.05; NTproBNP 13,199 [12,179, 14,219] v 8538 [2838, 27,523] pg/mL, p=0.14; Figure 1B/C ). Absolute NTproBNP concentrations were higher 15-28 days after S1P (14185 [12627, 15743] v 6822 [1672, 17997] pg/mL) in infants who died. Absolute MRproANP and NTproBNP concentrations at 29-60 days after S1P were lower in those with tachyarrhythmias, (219 [192, 411] v 508 [258, 2755] pmol/L; 2977 [939, 5177] v 8341 [726, 65078] pg/mL). Absolute MRproANP concentrations in the same timeframe were higher in those with bradyarrhythmias (704 [369, 2755] v 494 [192, 1191] pmol/L). Conclusion: A biexponential model described biomarker trajectories. An elevated ECH may identify interstage infants at increased risk of death. Utility of serial biomarker measurement to evaluate biomarker trajectories should be explored in future studies.

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)0.012
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.017
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0030.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.023
GPT teacher head0.312
Teacher spread0.289 · 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 designSimulation or modeling
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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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