Abstract 5399: Myocardial Contractile Dysfunction is Associated with Fetal Cardiac Bypass in a Sheep Model
Bibliographic record
Abstract
Declining cardiac output and placental dysfunction are the key barriers to successful fetal cardiac bypass for in utero repair of congenital heart defects. Identifying myocardial dysfunction, especially in the RV that is considered the systemic ventricle in fetal life, may be important for success. We hypothesized that fetal cardiac bypass results in myocardial contractile dysfunction that reduces cardiac output and placental perfusion, leading to placental dysfunction and fetal demise. Three fetuses from mid-term pregnant ewes were subjected to 30 min of cardiac bypass and followed for 120 min after bypass. Piezoelectric crystals (Sonometrics, Ontario, CA) were placed on three axes of the fetal heart and pressure catheters (Millar Instruments, Houston, TX) were inserted in the left and right ventricle (RV). Data were analyzed by repeated measures ANOVA with Fisher’s PLSD post hoc analyses. Representative RV pressure-volume loops in the figure showed that preload increased after bypass, indicated by increased end-diastolic volume (mean 4.1±.7 vs. 4.4±1 mL) and pressure (mean 14.3 ±7 vs. 31.3± 3 mmHg, P<.05). RV contractility decreased after bypass: pre-bypass dPdt max (mmHg/sec) - 880±93 vs. 731±102 at 120 min after bypass (P≤.1) and dP/dt min - 798±4 vs. 689±11 (P≤.1). Preload recruitable stroke work (slope of regression line) also decreased from 28.5±7 pre-bypass to 22.1±5 at 120 min post-bypass. Increased RV preload and RV contractile dysfunction are evident after fetal cardiac bypass. Minimizing the associated myocardial dysfunction is important for the success of fetal surgery to repair complex congenital heart defects. This research has received full or partial funding support from the American Heart Association, AHA National Center.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".