Effects of donor cause of death, ischemia time, inotrope exposure, troponin values, cardiopulmonary resuscitation, electrocardiographic and echocardiographic data on recipient outcomes: A review of the literature
Bibliographic record
Abstract
BACKGROUND: Heart transplantation has become standard of care for pediatric patients with either end-stage heart failure or inoperable congenital heart defects. Despite increasing surgical complexity and overall volume, however, annual transplant rates remain largely unchanged. Data demonstrating pediatric donor heart refusal rates of 50% suggest optimizing donor utilization is critical. This review evaluated the impact of donor characteristics surrounding the time of death on pediatric heart transplant recipient outcomes. METHODS: An extensive literature review was performed to identify articles focused on donor characteristics surrounding the time of death and their impact on pediatric heart transplant recipient outcomes. RESULTS: Potential pediatric heart transplant recipient institutions commonly receive data from seven different donor death-related categories with which to determine organ acceptance: cause of death, need for CPR, serum troponin, inotrope exposure, projected donor ischemia time, electrocardiographic, and echocardiographic results. Although DITs up to 8 hours have been reported with comparable recipient outcomes, most data support minimizing this period to <4 hours. CVA as a cause of death may be associated with decreased recipient survival but is rare in the pediatric population. Otherwise, however, in the setting of an acceptable donor heart with a normal echocardiogram, none of the other data categories surrounding donor death negatively impact pediatric heart transplant recipient survival. CONCLUSIONS: Echocardiographic evaluation is the most important donor clinical information following declaration of brain death provided to potential recipient institutions. Considering its relative importance, every effort should be made to allow direct image visualization.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".