Abstract 18745: Outcomes of Mechanical Circulatory Support for Patients With Functionally Single-Ventricle Physiology at Different Stages of Surgical Palliation
Bibliographic record
Abstract
Introduction: Mechanical circulatory support (MCS) for functionally single ventricle (SV) physiology poses significant challenges. We sought to analyze the results of MCS at 4 different stages of the surgical palliation process. Methods: From 2003 to 2013, 86 SV patients required MCS: Group 1, before any surgical palliation (n=13, 15%), Group 2, between stage I and II (n=59, 69%), Group 3, between stage II and Fontan (n=10, 12%), Group 4, after Fontan (n=4, 5%). Indications for MCS included failure to wean from cardiopulmonary bypass in 6 (7%) patients, circulatory failure in 7 (8%), respiratory failure in 9 (10%), cardiopulmonary failure in 4 (5%), and cardiac arrest in 58 (67%). Kaplan-Meier analysis was used to compare freedom from death and freedom from failure to wean between groups. Cox analysis was used to determine risk factors. Results: The median MCS duration was 3 days (IQR, 1-6). Of 86 patients, 58 (67%) were successfully weaned: 32 (37%) patients recovered, 8 (9%) were transplanted, 12 (14%) had operation/reoperation, and 1 (1%) had conversion to a different form of MCS. Fifty-two (60%) patients had complications including bleeding in 20, thromboembolism in 9, sepsis in 12, neurologic injury in 6, and multi-organ failure in 5. Thirteen patients required a second run of MCS. Freedom from death at 6 months after MCS initiation was comparable between the groups (Group 1, 23%, Group 2, 33%, Group 3, 15%, Group 4, 50%, p=0.66; Figure 1). Failure to wean from MCS was also comparable among the groups (p=0.46). Cox analysis revealed MCS-related complications as a risk factor for death (p=0.006) and longer duration of arrest as a risk factor for inability to wean from ECMO (p=0.036). The timing of MCS was not a risk factor for poor outcomes. Conclusions: Two thirds of SV patients who required MCS were rescued, although subsequent survival is generally poor across all stages of palliation. Given the poor outcomes in this cohort, consideration of alternative strategies is warranted.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".