Association between continuous‐flow left ventricular assist device infections requiring long‐term antibiotic use and post‐heart transplant morbidity and mortality
Bibliographic record
Abstract
BACKGROUND AND AIM OF STUDY: There exists controversy regarding the impact of infection in patients with a left ventricular assist device (LVAD) on post-heart transplant outcomes. This study evaluated the association between infections during LVAD support and the risk of early and late post-heart transplant infection, rejection, and mortality in transplant recipients bridged with an LVAD. METHODS: This is a single-center retrospective observational cohort study of consecutive adults supported with a continuous flow LVAD undergoing heart transplant between 2006 and 2019 at the Toronto General Hospital. The grade of LVAD infection was classified as per International Society of Heart and Lung Transplantation guidelines. Patients were divided into three groups: (1) patients with LVAD-specific infection confirmed with positive cultures requiring long-term antibiotic use until the time of transplant; (2) patients with any type of infection in whom antibiotics were stopped at least 1 month before transplant; (3) patients without any infections between LVAD implant and transplant. Logistic regression and Cox proportional hazard models were used to evaluate early- and late-post transplant outcomes, respectively. RESULTS: We included 75 LVAD recipients: 16 (21%) patients had a chronic LVAD-related infection on suppressive antibiotics, 30 (40%) had a resolved infection, and 29 (39%) had no infections. During a median post-transplant follow-up time of 4 (2 to 7) years, 65 (87%) patients developed infections, 43 (64%) rejections, and 17 (23%) deaths. Both short- and long-term risks of infection, rejection, and mortality did not differ significantly among the groups. CONCLUSION: LVAD patients with infections did not have a significantly higher risk of infection, rejection, or mortality at any time point after transplant.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".