Citations

Introduction: Embolic stroke of undetermined source (ESUS) is a clinical construct encompassing heterogenous possible mechanisms of incident stroke, potentially with variable responsiveness to anticoagulation and antiplatelet treatment. This study aims to identify differences in recurrent stroke risk based on phenotypic clusters in an ESUS population, and whether some clusters may benefit relatively more from anticoagulation over antiplatelet therapy. Methods: We identified patient phenotypes from a multicenter, retrospective cohort study of 1909 ESUS patients by dividing them into groups using Partitioning Around Medoids (PAM) with correlation-weighted Gower distance over 23 baseline demographic, clinical, laboratory, radiographic, and cardiac features. We confirmed optimal clustering at 3 groups. We assessed cluster associations with time to recurrent stroke using Kaplan-Meier survival analysis. We then employed a causal survival forest to estimate conditional average treatment effects (CATE) of anticoagulation versus antiplatelet therapy using the same baseline features as predictors with a 365-day horizon for restricted mean survival time differences. Finally, we used best linear projection to identify baseline features predictive of treatment effect and assessed whether effects differed significantly by cluster. Results: Cluster 1 (n=542) identified a low-risk, younger sample with minimal baseline disability and comorbidity burden. Cluster 2 (n=743) comprised a moderate-risk phenotype with intermediate comorbidity. Cluster 3 (n=626) represented the oldest and highest-risk phenotype. Kaplan-Meier analysis demonstrated significant differences in stroke-free survival across patient clusters (p < 0.001), where Cluster 1 experienced the lowest recurrent stroke rate and Cluster 3 had the highest. The clustering algorithm successfully identified clinically meaningful phenotypes with distinct risk profiles. While CATE varied across clusters, the differences were not statistically significant. Conclusion: In a multicenter ESUS population, we identified 3 distinct phenotypic clusters, each comprising nearly one-third of the sample and with a differential risk of recurrent stroke. Although cluster was not a significant effect modifier, substantial CATE variability by cluster was observed. Future clinical trials may consider evaluating secondary stroke prevention therapies among phenotypically similar patients who may respond differentially to novel therapies.

Abstract Background Heart failure (HF) and atrial fibrillation (AF) are intertwined, sharing common risk factors and influencing each other in a reciprocal manner. While left ventricular diastolic dysfunction (LVDD) stands as a hallmark of HF's hemodynamic profile, its direct correlation with heightened AF risk remains uncertain. Our recent validation of an artificial intelligence-enabled electrocardiogram (AI-ECG) algorithm for LVDD detection has opened new avenues. Yet, whether AI-ECG-detected LVDD correlates with long-term AF risk remains unexplored. Methods We performed a retrospective study among all patients with a comprehensive LVDD assessment from the test population of the AI-ECG LVDD study between September 2001 and June 2022. Patients with prior documented AF according to health records or previous ECG were excluded. Patients were classified by AI-ECG as normal diastolic function (DF), grade 1 (G1), grade 2 (G2), or grade 3 (G3) LVDD. We assessed the risk of AF across AI-ECG LVDD grade, with normal DF as reference, with competing risk models. Results Of 97,023 patients free of AF at baseline, 63,533 (65.4%), 10,776 (11.1%), 18,940 (19.5%), and 3,774 (3.9%) were classified as normal DF, G1-LVDD, G2-LVDD, and G3-LVDD, respectively. Worse AI-ECG LVDD was associated with older age, lower left ventricular ejection fraction (LVEF), and higher rates of HF, diabetes, hypertension, chronic pulmonary disease, renal failure, and cardiovascular disease (p-of-trend&lt;0.001 for all). Over a median follow-up of 4.8 years (interquartile range 1.8-9.2 years), new-onset AF occurred in 6,795 (7.0%) patients. In multivariable survival analysis, adjusted to multiple risk factors including LVEF and clinical HF, G2 and G3 LVDD, representing patients with high filling pressures, were independently associated with a higher AF-risk [G2-LVDD: adjusted hazard ratio (aHR) 1.64 (95% confidence interval (95%CI) 1.52-1.73), G3-LVDD: aHR 2.24 (95%CI 2.02-2.48)]. Conclusion The AI-ECG LVDD algorithm independently predicts long-term AF risk, regardless of LVEF and clinical HF status, highlighting its potential for identifying high-risk populations and guiding proactive monitoring and management.

Abstract Background Non-bacterial thrombotic endocarditis (NBTE) is a non-infectious condition characterized by thrombotic and/or inflammatory depositions involving the cardiac valves. It is a challenging diagnosis of exclusion. Purpose This study aimed to better characterize patients with pathologically proven NBTE and assess its clinical, echocardiographic characteristics and prognostic implications. Methods We retrospectively identified patients with pathology-proven NBTE at a single center. Patients with positive preoperative blood cultures, a history of active or treated infective endocarditis, or identification of valvular organisms by special stains were excluded from the study. Patients with pathology reports of valve perforation or chordal rupture were also excluded because of the high likelihood of an infectious etiology for these lesions. Results A total of 53 patients with NBTE (median age 57 years; 61% females) were identified. In this cohort, 22% had a history of malignancy, 30% had connective tissue disease, 32% had coronary artery disease, and 11% prior history of NBTE. Neurological events accounted for 18 (34%) of the presenting symptoms (TIA n=17, CVA n=9), while new valvular dysfunction in 7 (13%) and fever in 8 (15%) of patients. Five patients (9%) had NBTE involving more than one valve. NBTE involved the mitral valve in 64%, aortic valve in 38% prosthetic/mechanical valve in 11%, and tricuspid valve in 5%. NBTE was identified at the time of autopsy in 34% of patients. NBTE recurred in 3 patients during follow-up. Excluding patients diagnosed at the time of autopsy, 9% of patients died within 1 year of NBTE diagnosis. Conclusion NBTE was diagnosed pathologically in the presence of hyper-inflammatory states due to critical illness or immunological diseases. It was predominantly on the left side of the heart and was associated with embolic phenomena, either clinically or on imaging. Patients diagnosed with antemortem with NBTE have a high mortality in the first year (9%).

Abstract Background The determination of left ventricular diastolic dysfunction (LVDD) and filling pressure in patients with significant (&gt;moderate) mitral regurgitation (MR) poses a complex challenge. We recently validated an artificial intelligence-enabled electrocardiogram (AI-ECG) algorithm to detect LVDD and estimate LV filling pressures. Methods This retrospective study sought to examine the risk of all-cause mortality across AI-ECG LVDD grades. Patients from the AI-ECG LVDD study test cohort who underwent transthoracic echocardiography confirming significant MR and an ECG within fourteen days of each other at Mayo Clinic between 09/2001 and 06/2022 were included. LVDD status was determined based on the index ECG, and patients were categorized into groups representing normal diastolic function (NDF) or LVDD grades 1 (G1), 2 (G2), or 3 (G3). Results Of 4,019 patients with significant MR (mean age 69.8, 49.0% women), 1,175 (29.2%), 1,881 (46.8%), and 963 (24.0%) were classified by AI-ECG as NDF/G1-LVDD, G2-LVDD, and G3-LVDD, respectively. The median mitral effective regurgitant orifice area was 26 mm² (interquartile range 20-36 mm²). Over a median follow-up of 3.5 years, 1,636 (40.7%) patients died. In multivariable survival analysis adjusted for multiple risk factors, a worse AI-ECG LVDD grade was independently associated with an increased death risk [G2DD: adjusted hazard ratio (aHR) 1.98 (95% confidence interval (95% CI) 1.63-2.40), G3DD: aHR 2.59 (95% CI 2.09-3.20)]. These findings were consistent when accounting for mitral valve intervention and among patients with &gt;moderate MR or after mitral valve intervention. Conclusion In patients with significant MR, the grading of LVDD by AI-ECG is independently associated with all-cause mortality.

Background: Optimal Blood pressure management after thrombectomy for acute ischemic stroke and its association with clinical outcomes remains unclear. We performed this study to compare clinical outcomes between intensive systolic blood pressure (SBP) control (<120-140mmHg) and conventional SBP control (< 180mmHg). Methods: In September 2023, this registered systematic review (CRD42023464176) was performed using multiple databases for the following keywords: stroke, thrombectomy, and Blood Pressure from 2010 to present. Randomized control studies were included if they had the reported the outcome for adults aged >18 who underwent successful thrombectomy (defined as mTICI 2b or higher) for acute ischemic stroke. The primary outcome of interest was the rate of functional independence, defined as a modified Rankin scale of 0-2 at 90 days. The secondary outcomes of interest included rates of mortality, and symptomatic intracranial hemorrhage (sICH). For all outcome events, corresponding odds ratios (OR) and 95% confidence intervals (CI) were calculated using a random-effects meta-analysis model. Results: Four studies comprising 1497 patients were included. Compared to conventional SBP control, intensive SBP control was associated with lower rates of functional independence (OR 0.67, 95% CI 0.51- 0.88 p=0.0). There were comparable rates of sICH (OR 1.12, 95% CI 0.75-1.67; p = 0.56) and mortality (OR 1.21, 95% CI 0.90-1.64; p = 0.19) between intensive and conventional SBP control groups. Conclusions: Our findings suggest that intensive blood pressure control does not improve clinical outcomes. More robust data is needed to draw definite conclusions.

Objectives: The development and evaluation of percutaneous thrombectomy devices for pulmonary embolism (PE) pose a need for standardized large in vivo models with representative anatomical and physiological conditions and clots analogs. In this study, we present a swine model of PE model employing human-derived clot analogs. Material and Methods: Baseline angiographic and physiological pressure measurements were obtained in six adult Yorkshire pigs (45–65 kg) and results were benchmarked for interspecies comparison with published human data using fluoroscopic examinations, intra-arterial pressure measurements, and histologic studies. Then, clot analogs were created ex vivo employing banked human blood and a subset incubated in iodinated contrast for fluoroscopic visualization. Clot analogs were then embolized via a femoral venous access and angiographic/physiological consequences were evaluated. Results: The main, right, and left pulmonary artery diameters were 24 ± 1.1 mm, 16.5 ± 0.8 mm, and 12.6 ± 1.2 mm, respectively. The angle between the main pulmonary artery at the bifurcation point was approximately 90–95°. The clot analogs were heterogeneous and had increased fibrin content along the clot length. The overall composition was 96.63% red blood cell (RBC)/3.37% fibrin in the initial section, 48.85% RBC/51.15% fibrin in the intermediate section, and 3.44% RBC/96.56% fibrin in the final section. Embolization of the clot analogs resulted in distal occlusion of the right and left pulmonary arteries. Conclusions: This swine model coupled with clot analog is able to accurately mimic human anatomical and physiological conditions in PE making it feasible for the evaluation of pulmonary thrombectomy devices.

Background: Understanding clot composition may allow for better technical planning and improved outcomes in mechanical thrombectomy (MT). We sought to correlate clot composition with reperfusion outcomes in MT. Methods: Clinical, imaging, and clot data from patients enrolled in the STRIP Registry from September 2016 to September 2020 were analyzed. Samples were fixed in 10% phosphate-buffered formalin and stained with hematoxylin and eosin and Martius Scarlett Blue. Percent composition, richness, and gross appearance were evaluated. Outcome measures included the rate of First-Pass Effect (mTICI2c/3, FPE) and the number of device passes. Results: A total of 1430 patients (mean age, 68.4±13.5years; median [IQR] baseline NIHSS,17.2 [10.5-23]; IV-tPA use, 36%; Stent-Retrievers [SR], 27%; Contact Aspiration [CA], 27%; Combined SR + CA, 43%) were included. The median [IQR] number of passes was 1 [1-2]. FPE was achieved in 39.3% of the cases. There was no association between percent histological composition or clot richness and FPE in the overall population. However, the combined technique resulted in lower FPE rates for RBC-rich (P<0.0001), platelet-rich (P=0.003), and mixed (P<0.0001) clots. Fibrin-rich and platelet-rich clots required a higher number of passes compared to RBC-rich and mixed clots (median, 2 and 1.5 vs.1, respectively, P=0.02). CA displayed a trend towards a higher number of passes with fibrin-rich clots (2 vs.1, P=0.12). By gross appearance, mixed/heterogeneous clots had lower FPE rates than red and white clots. Conclusion: Despite the lack of correlation between clot histology and FPE in the overall population, our study adds to the growing body of evidence supporting the notion that clot composition influences reperfusion treatment strategy outcomes. Additional studies are needed.

Background Although successful recanalization (modified Thrombolysis in Cerebral Infarction score 2b–3) can be achieved in >80% of patients experiencing stroke attributable to large‐vessel occlusion, up to 50% of patients may develop poor clinical outcomes (modified Rankin scale score at 90 days of 3–6), termed as futile recanalization (FR). The meta‐analysis aims to determine various risk factors associated with FR. Methods In February 2021, a comprehensive literature search on risk factors associated with FR was performed with keywords, including “stroke,” “thrombectomy,” “treatment outcome,” and “risk factors.” Their correlations with FR were evaluated using the random effect size meta‐analysis model. Results Twenty studies with 3037 patients were included with an FR rate of 51.0%. Our meta‐analyses showed that age (mean difference [MD], 5.6; 95% CI, 4.7–6.6), National Institutes of Health Stroke Scale score (MD, 4.2; 95% CI, 3.2–5.1), Alberta Stroke Program Early Computed Tomography (CT) Score (MD, −0.5; 95% CI, 0.8–0.3), hypertension (odds ratio [OR], 1.5; 95% CI, 1.3–1.9), systolic blood pressure (MD, 6.9; 95% CI, 3.6–8.7), atrial fibrillation (OR, 1.5; 95% CI, 1.2–1.8), IV tPA (tissue‐type plasminogen activator) (OR, 0.7; 95% CI, 0.5–0.8), puncture to recanalization time (MD, 9.6; 95% CI, 5.3–13.8), and time of onset to recanalization (MD, 32.1; 95% CI, 6.5–47.7) were significantly associated with FR ( P <0.001). Conclusions Age, admission National Institutes of Health Stroke Scale score, Alberta Stroke Program Early CT Score, comorbidities, including hypertension, systolic blood pressure, atrial fibrillation, and use of IV tPA, as well as time frames, including onset to recanalization and onset to arrival, were significant influencing factors for FR after mechanical thrombectomy. Future research on the mechanism underlying FR is warranted.