Antemortem Heparin in Organ Donation After Circulatory Death Determination: A Systematic Review of the Literature
Bibliographic record
Abstract
Donation after circulatory death determination frequently involves antemortem heparin administration to mitigate peri-arrest microvascular thrombosis. We systematically reviewed the literature to: (1) describe heparin administration practices and (2) explore the effects on transplant outcomes. We searched MEDLINE and EMBASE for studies reporting donation after circulatory death determination heparin practices including use, dosage, and timing (objective 1). To explore associations between antemortem heparin and transplant outcomes (objective 2), we (1) summarized within-study comparisons and (2) used meta-regression analyses to examine associations between proportions of donors that received heparin and transplant outcomes. We assessed risk of bias using the Newcastle Ottawa Scale and applied the GRADE methodology to determine certainty in the evidence. For objective 1, among 55 eligible studies, 48 reported heparin administration to at least some donors (range: 15.8%-100%) at variable doses (up to 1000 units/kg) and times relative to withdrawal of life-sustaining therapy. For objective 2, 7 studies that directly compared liver transplants with and without antemortem heparin reported lower rates of primary nonfunction, hepatic artery thrombosis, graft failure at 5 y, or recipient mortality (low certainty of evidence). In contrast, meta-regression analysis of 32 liver transplant studies detected no associations between the proportion of donors that received heparin and rates of early allograft dysfunction, primary nonfunction, hepatic artery thrombosis, biliary ischemia, graft failure, retransplantation, or patient survival (very low certainty of evidence). In conclusion, antemortem heparin practices vary substantially with an uncertain effect on transplant outcomes. Given the controversies surrounding antemortem heparin, clinical trials may be 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 | 0.009 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".