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Record W4399273567 · doi:10.1101/2024.05.31.24308306

Surgical Decision-Making in Neonates with Borderline Left Ventricular Hypoplasia without Significant Aortic or Mitral Valve Stenosis using Cardiovascular Magnetic Resonance

2024· preprint· en· W4399273567 on OpenAlexaff
Aswathy Vaikom House, Aakansha Ajay Vir Singh, Ankavipar Sapruangrang, Edgar Jaeggi, David J. Barron, Christopher Z. Lam, Shi‐Joon Yoo

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsCardiologyStenosisHypoplasiaInternal medicineMagnetic resonance imagingMedicineCardiac magnetic resonanceRadiology

Abstract

fetched live from OpenAlex

Abstract Background Most patients with significant left ventricular (LV) hypoplasia undergo single ventricle (SV) palliation, but biventricular (Bi-V) repair is viable in some patients with borderline LV hypoplasia. We sought to identify CMR (cardiovascular magnetic resonance) criteria predictive of successful primary Bi-V repair in neonates with borderline LV hypoplasia without significant stenosis of the mitral valve (MV) and aortic valve (AV), and to determine reasons for reintervention after successful Bi-V repair. Methods This retrospective study included all patients with borderline LV hypoplasia who underwent CMR from 2003-2024 for surgical decision-making. Patients with abnormal segmental connections, atrioventricular septal defects, unrestrictive ventricular septal defects, those with more than mild MV stenosis (mean Doppler flow gradient > 5 mmHg) and/or more than mild AV stenosis (peak Doppler flow gradient >20 mmHg) were excluded. Patients were divided into two groups based on initial intervention - primary Bi-V repair and hybrid/ other staging procedure. Outcomes were categorized as successful primary Bi-V repair, successful staged Bi-V repair and failure to achieve Bi-V repair (hybrid followed by SV palliation, transplant, death). Fisher exact test and Mann-Whitney U test was utilized to explore potential relationships. ROC curves were used to test diagnostic accuracy of parameters to predict successful primary Bi-V repair. Results Among 37 patients meeting the inclusion criteria, 23 (62%) patients underwent successful primary Bi-V repair, 8 (22%) underwent staged Bi-V repair, 6 (16%) failed to achieve Bi-V repair. Patients who underwent successful primary/ staged Bi-V repair had higher values for left ventricular diastolic volume index (LVEDVi 28 mL/m 2 vs. 17.4.00 mL/m 2 ; p <0.002), higher blood flow volume through the ascending aorta (Q Ao :1.99 L/min/m 2 vs. 0.97 L/min/m 2 , p <0.012), and Q Ao / superior vena cava (Q SVC ) flow ratio (1.44 vs. 0.85, p =0.034) compared to those who had failure to achieve Bi-V repair. CMR LVEDVi cutoff of CMR 27 mL/m², had 87% sensitivity and 79% specificity with an AUC of 87.6% and Q Ao threshold of 1.9 L/min/m 2 had 65.2% sensitivity and 92.9% specificity (AUC: 86.0%) to predict successful primary Bi-V repair. Of 31 patients with primary or staged Bi-V repair, 7 (22%) underwent reinterventions for LVOT obstruction followed by mitral stenosis. Conclusions CMR plays a critical role in pre-operative evaluation, surveillance and decision-making in patients with borderline LV hypoplasia. In patients with borderline LV hypoplasia without MV/AV stenosis, successful primary Bi-V repair can be achieved when the CMR-derived LVEDVi is >27 mL/m 2 and Q Ao is > 1.99 L/min/m 2 .

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)0.005
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 score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.295
Teacher spread0.275 · 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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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