Peripheral versus central cannulation of VA-ECMO for primary graft dysfunction after heart transplantation: A systematic review and meta-analysis
Bibliographic record
Abstract
Background: Severe primary graft dysfunction (PGD) after heart transplantation (HT) is a major cause of death and requires veno-arterial extracorporeal membrane oxygenation (VA-ECMO). Methods: We conducted a systematic review and meta-analysis including studies of adult HT recipients who required VA-ECMO for PGD to determine whether a peripheral or central configuration was associated with higher mortality. The primary endpoints were short-term and one-year mortality. Secondary endpoints were VA-ECMO-related complications. Results: Overall, we included 16 studies comprising 874 patients from 33 centers. Using a random-effects model, peripheral cannulation was associated with a nonsignificant reduction in short-term mortality (odds ratios [OR] = 0.73, 95% confidence interval [CI] = 0.41-1.28, I2 = 55.8%) and a significant reduction in 1-year mortality (OR = 0.60, 95%CI = 0.37-0.97, I2 = 35.9%). Peripheral cannulation decreased the risk of bleeding but increased the risk of limb ischemia and infection, with similar rates of stroke and need for renal replacement therapy. Overall, certainty of evidence was low. Conclusions: With low certainty evidence, peripheral VA-ECMO cannulation may reduce short-term and 1-year mortality with lower bleeding rates but higher limb-related complications, supporting peripheral configuration in HT recipients with severe PGD.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.030 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".