Stroke in Patients with Left Ventricular Assist Devices
Bibliographic record
Abstract
BACKGROUND: Left ventricular assist devices (LVADs) are artificial pumps used in end-stage heart failure to support the circulatory system. These cardiac assist devices work in parallel to the heart, diverting blood from the left ventricle through an outflow graft and into the ascending aorta. LVADs have allowed patients with end-stage heart failure to live longer and with improved quality of life compared to best medical therapy alone. However, they are associated with significant risks related to both thrombosis and bleeding in this medically complex patient population. As LVADs continue to be used more widely, stroke neurologists need to become familiar with the unique physical exam and vascular imaging findings associated with this population. SUMMARY: Reported rates of LVAD-associated stroke at 2 years post-implantation range from 10 to 30%, which is significantly higher than in age-matched controls. There are approximately equal rates of ischemic and hemorrhagic strokes, and rates are highest during the peri-implantation period and in the first year of therapy. Risk factors associated with ischemic and hemorrhagic stroke in this cohort can be grouped into treatment-related factors, including specific devices and antithrombotic/anticoagulation strategy, and patient-related factors. Evidence for reperfusion therapy for acute stroke in this population is limited. Intravenous tissue plasminogen activator (IV-tPA) is often contraindicated as events may occur in the perioperative setting, or in the context of therapeutic anticoagulation. Endovascular therapy with successful recanalization is reported, but there is little experience documented in the published literature. Key messages: LVAD use is increasingly common. Given the high associated risks of stroke, neurologists will need to become increasingly familiar with an approach to assessment and therapy for LVAD patients with cerebrovascular issues.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".