The Effect of Ventricular Assist Devices on Long-Term Post-Transplant Outcomes: A Systematic Review of Observational Studies
Bibliographic record
Abstract
AIMS: Ventricular assist device (VAD) therapy is widely used as a bridge to cardiac transplant. Studies addressing the effect of VADs on post-transplant outcomes have shown conflicting results. It is imperative to review this evidence to inform clinical decision making and future research. Our aim was to systematically evaluate the effect of VAD therapy on long-term post-transplant outcomes in heart transplant recipients. METHODS AND RESULTS: We searched online databases (Medline, PubMed, Embase, and CINAHL) and references of included articles. Comparative studies evaluating the effect of VADs on post-transplant outcomes in adults were included and study results were meta-analysed using random-effects models. We conducted subgroup analyses to assess the effect estimate of extra- vs. intra-corporeal VADs and to evaluate the impact of transplant era and listing status. Overall, we identified 31 observational studies. One-year post-transplant mortality in recipients bridged with an extra-corporeal VAD was significantly higher than in non-bridged recipients (RR 1.8, 95% CI 1.53-2.13, I(2)= 1%), while patients supported with an intra-corporeal VAD had similar mortality to non-bridged recipients (RR 1.08, 95% CI 0.95-1.22, I(2)= 0%). The risks of rejection within the first post-transplant year and coronary allograft vasculopathy were not significantly different between patients with or without VAD support prior to transplant. Publication bias was low; however, the risk of bias across studies was moderate to high. CONCLUSION: Intra-corporeal VAD support does not have a deleterious impact on post-transplant outcomes. However, post-transplant survival may be poorer in the subgroup of patients supported with extra-corporeal devices. Studies with greater methodological rigour are warranted.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| 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".