Biventricular Repair in Borderline Left Hearts
Bibliographic record
Abstract
Cardiac magnetic resonance imaging (CMR) may augment 2-dimensional (2D) echocardiography in decision-making for biventricular repair in borderline hypoplastic left hearts. This study evaluates: 1) the relationship between 2D echocardiography and CMR; 2) imaging variables affecting assignment to biventricular vs non-biventricular management; and 3) variables affecting transplant-free biventricular survival. We reviewed clinical, echocardiographic, and CMR data in 67 infants, including CMR-determined ascending aortic (AAo) flow and comparable left ventricular end-diastolic volume indexed (LVEDVi) by 2D-echocardiography and CMR. Treatment assignment to biventricular repair was either direct (BV, n = 45) or with a bridging hybrid procedure (H1-BV, n = 12). Echocardiographic LVEDVi was <20 mL/m2 in 83% of biventricular repair infants and underestimated CMR-LVEDVi by 16.8 mL/m2. AAo flows had no/weak correlation with aortic and mitral valve z-scores or LVEDVi. AAo flows differed between BV, H1-BV, and single-ventricle groups (median): 2.1, 1.7, and 0.7 L/min/m2, respectively. Important variables for treatment assignment were presence of endocardial fibroelastosis, AAo flow, and mitral valve z-score. Biventricular repair was achieved in 54. The median follow-up was 8.0 (0.1-16.4) years. Transplant-free biventricular survival was 96%, 82%, and 77% at 1, 5, and 10 years, respectively. Patients without aortic coarctation repair were at higher risk of death, transplantation, or single-ventricle conversion (HR: 54.3; 95% CI: 6.3-47.1; P < 0.001) during follow-up. AAo flow had a smaller nonlinear effect with hazard ratio increasing at lower flows. Historical 2D echocardiographic criteria would have precluded many patients from successful biventricular repair. AAo flow, an integrative index of left heart performance, was important in assigning patients to a biventricular circulation and affected survival. Biventricular survival was strongly associated with the need for aortic coarctation repair.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".