Left Ventricular Assist Device Decommissioning Compared with Explantation for Ventricular Recovery: A Systematic Review
Bibliographic record
Abstract
Left ventricular assist device (LVAD) withdrawal with ventricular recovery represents the optimal outcome for patients previously implanted with an LVAD. The aim of this systematic review was to examine the patient outcomes of device withdrawal via minimally invasive pump decommissioning as compared with reoperation for pump explantation. An electronic search was performed to identify all studies in the English literature assessing LVAD withdrawal. All identified articles were systematically assessed for inclusion and exclusion criteria. Overall, 44 studies (85 patients) were included in the analysis, of whom 20% underwent decommissioning and 80% underwent explantation. The most commonly used LVAD types included the HeartMate II (decommissioning 23.5% vs. explantation 60.3%; p = 0.01) and HeartWare HVAD (decommissioning 76.5% vs. explantation 17.6%; p < 0.001). At median follow-up of 389 days, there were no significant differences in the incidence of cerebrovascular accidents (p = 0.88), infection (p = 0.75), and survival (p = 0.20). However, there was a trend toward a higher recurrence of heart failure in patients who underwent decommissioning as compared with explantation (decommissioning 15.4% vs. explantation 8.2%, cumulative hazard; p = 0.06). Decommissioning appears to be a feasible alternative to LVAD explantation in terms of overall patient outcomes.
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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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".