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ABSTRACTBackgroundThe factors contributing to sustained ventricular arrhythmias (VAs) >30 days after left ventricular assist device (LVAD) implantation are not well‐established.ObjectivesThis study aimed to predict the factors associated with late sustained VAs after LVAD implantation and develop a predictive score to identify patients with an increased risk of late sustained VAs after the procedure.MethodsWe performed a retrospective cohort study on a training cohort of 623 patients and a validation cohort of 157 patients who underwent LVAD implantation at the Mayo Clinic (Rochester, Phoenix, and Jacksonville) from January 1, 2000, to December 30, 2020. Late sustained VAs were defined as ventricular tachycardia (VT) and ventricular fibrillation (VF) occurring >30 days after the LVAD procedure. Detailed chart reviews of the electronic health records within the Mayo Clinic and outside medical records were performed.ResultsA total of 780 patients were included in our study. Late sustained VAs occurred in 30% (n = 232) of the patients. The significant factors associated with late sustained VAs after LVAD were the history of VAs prior to LVAD (34.1% vs. 23.0%, p < 0.01), implantable cardiac defibrillator (ICD) (87.9% vs. 77.6%, p < 0.01) or cardiac resynchronization therapy (CRT) in situ (43.5% vs. 33.6%, p = 0.008), VT ablation prior to LVAD (5.2% vs. 1.8%, p = 0.010), use of amiodarone (49.1% vs. 38.7%, p = 0.007), use of mexiletine (15.5% vs. 5.7%, p < 0.01), and higher left ventricular end‐diastolic diameter (LVEDD) on echocardiography prior to LVAD implantation (71.4 vs. 68.7 mm, p = 0.002). During follow‐up, the patients who developed late sustained VAs after LVAD had lower survival than those who did not (HR = 1.96, 95% CI:156–2.4, p < 0.001). The average time from LVAD to orthotopic heart transplant was longer among late sustained VAs patients (23 vs. 14 months, p < 0.01). The “VIN” risk score was created to identify four risk groups: low (scores 0), intermediate (score 1), high (score 2), and very high (score 3). The rates of late VA's in the training cohort at 1 year were 9.5%, 14%, 18%, and 25% which was almost similar to the risk of late VA's at validation cohort 10%, 12%, 20%, and 63%, respectively.ConclusionsLate sustained VAs occurred in 30% of the patients who received LVAD and were associated with lower survival. The VIN risk score was developed and validated to stratify patients into low, intermediate, high, and very high risk of late sustained VAs.

Migraine with aura(MwA) is associated with an increased risk of stroke and adverse vascular outcomes compared to those with migraine without aura (MwoA). AI-ECG prediction models developed at our institution can evaluate the probability of atrial fibrillation (AF) and estimate a patient’s age based on a normal sinus rhythm (NSR) ECG. Delta age, AI-ECG estimated age minus chronological age, indicates endothelial dysfunction and is associated with cardiovascular mortality. We aim to assess how AI-ECG prediction model outputs, specifically the AF probability and delta age, are associated with adverse vascular outcomes in patients with migraine. Adult patients diagnosed with MwA and MwoA from 2000-2020 with at least one digital, standard 12-lead ECG were identified. The first ECG that showed NSR is used as the index ECG. Patients with any adverse vascular outcomes before the index ECG were excluded. Adverse vascular outcomes used as endpoints include acute ischemic stroke, acute myocardial infarction, deep vein thrombosis/pulmonary embolism, AF, and carotid artery dissection. A total of 31301 patients (13783 MwA, 17518 MwoA) were included in our analysis. The mean age at the time of the index ECG was 44.3 (14.5), and the average follow-up time was 71.6 (69.8) months. Based on the index ECG, the mean AF probability was significantly higher in MwA compared to MwoA (2.39 vs 2.06, p< 0.001), while the delta age was lower in MwA compared to MwoA (3.7 vs 4.2, p <.001). The prevalences of all vascular outcomes are summarized in Table 1. Multivariate Cox regression models showed that a higher AF prediction model output (every 10% increase), as well as a higher delta age (every 10-year increase), are associated with an increased risk of composite vascular outcomes (HR1.20, 95%CI 1.17-1.23, p<.001, and HR1.19, 95%CI 1.14-1.23, p < .001) [Table 2]. The Kaplan-Meier curve of adverse vascular outcome-free survival by AF prediction model output, using 1% as the cutoff (HR 1.49, 95% CI 1.41, 1.57, p<.001), and by delta age, using 2-year as the cutoff (HR 1.14, 95% CI 1.08, 1.21, p <. 001) are presented in Figure 1. Having aura, older age, male, coronary artery disease, congestive heart failure, diabetes, hypertension, and tobacco use were also associated with a higher risk of adverse vascular outcomes. Our results demonstrated the potential of using AI-ECG AF prediction model output and delta age to identify migraine patients at risk for adverse vascular outcomes.

AbstractBackgroundLewy body (LB) diseases can present with overlapping prodromal, cognitive, motor, autonomic or neuropsychiatric symptoms. Intuitively, greater symptom severity should correlate with greater pathological burden, but this has not been consistently shown. LB pathology does not translate to clinical expression in Incidental LB disease. While several composite scores/toolkits utilize overlapping schemes for diagnosis, a composite data‐derived score to predict LB pathologic burden is lacking. We aimed to utilize an autopsy‐confirmed cohort, and validated, brief, and standardized clinical, functional, pathologic assessments, and machine learning (ML)/quantitative modeling techniques to identify clusters and importance rankings among assessments/measures to predict LB pathologic severity and density.MethodA total of 234 subjects with neuropathological finding of LB at autopsy in the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND) who were classified as Cognitively Unimpaired or Mild Cognitive Impairment after their first study clinical evaluation were included. Of these, 145 subjects had complete scores for 32 of 46 measures (clinical, cognitive, behavioral and functional) that were utilized as predictors of LB pathology. Olfactory function was assessed using the University of Pennsylvania Smell Identification Test (UPSIT). LB severity was assessed by the Unified Staging System for Lewy Body Disorders (USSLB). Several ML algorithms and quantitative prediction models were explored and compared: artificial neural network (ANN), partial least square regression (PLSR), support vector regression (SVR), relevance vector regression (RVR) and ensemble forest regression (EFR) with leave‐one‐out (LOO) scheme. Game‐theory based Shapley methods assessed the impact, including rankings, consistency and magnitude, of model predictors.ResultRVR predicted aggregate LB density with large effect size (R2 = 0.691, p<0.00001). ANN predicted USSLB severity stage with large effect size (R2 = 0.74, p<2.5e‐43). All other ML algorithms/models provided substantial prediction. Across all models, UPSIT was the most influential predictor (>65%), followed by Controlled Oral Word Association Test (COWAT) and age.ConclusionThese preliminary and exploratory results support the utilization of ML techniques/models to assess LB pathologic burden with key measures collected in relatively small samples. UPSIT was consistently ranked highest impactful among clinical and functional measures/predictors. Integrated together in ML/data‐derived composites, UPSIT, COWAT and other clinical characteristics may be of antemortem utility to predict USSLB stages.

ObjectivesTo combine sonographic Murphy sign (SMS) with clinical parameters to effectively stratify patients into risk groups for acute cholecystitis.MethodsConsecutive emergency department patients from April 1, 2019 to August 31, 2022 with possible acute cholecystitis were grouped using patient age, sex, and white blood cell count to determine the rate of acute cholecystitis found in subgroups. Three distinct clinical risk groups were established and then regrouped by prospective assessment of SMS into three non‐imaging risk groups. Differences in the rate of acute cholecystitis for clinical parameters, clinical risk groups, and non‐imaging risk groups were statistically analyzed.ResultsOf 1231 patients (mean [SD] age, 51.2 [19.5]; 476 [38.7%] male), 156 had acute cholecystitis (mean [SD] age, 62.0 [15.4]; 85 [54.5%] male). Rates differed based on sex (9.4% female vs 17.9% male, P < .001), age group (1.8% for patients <30 years, 9.0% for patients 30–59 years, 22.3% for patients ≥60 years; P < .001), and white blood cell count (23.1% elevated vs 6.6% not elevated; P < .001). The low, average, and high non‐imaging risk groups had acute cholecystitis rates of 1.8%, 14.0%, and 43.1%, respectively. Relative risk (95% CI) for the low non‐imaging group compared with others was 0.07 (0.04, 0.12; P < .001); relative risk for the high non‐imaging risk group compared with others was 7.05 (5.32, 9.43; P < .001).ConclusionsSonographic Murphy sign assessment combined with patient age, sex, and white blood cell count effectively stratifies acute care patients into distinct acute cholecystitis risk groups.

ABSTRACTPurposeThis study aimed to assess whether kidney stone burden and risk factors at the time of kidney donor evaluation were associated with a symptomatic stone event post‐donor evaluation.MethodsWe identified adults evaluated at Mayo Clinic (two sites) (2000–2011) for living kidney donation and had either a personal history or radiological evidence of kidney stone disease. We analyzed demographics, stone risk factors, stone number/size, and the committee's donation decision and reasons. A follow‐up survey (2022–2023) assessed post‐evaluation symptomatic kidney stones and related morbidity.ResultsAmong 412 potential donors with kidney stone disease, 258 donated, 75 did not donate due to kidney stones, and 79 did not donate for other reasons. Multivariable analysis showed that candidates not donating due to stones had higher body mass index (BMI), prior symptomatic kidney stones, multiple stones on imaging, bilateral kidney stones, and diameter of largest stone ≥3 mm. Of 147 who completed the survey, 26 (18%) had a symptomatic kidney stone post‐donor evaluation. Younger age (p = 0.031) and multiple stones on imaging (p = 0.02) were significant predictors of post‐evaluation symptomatic stones regardless of donation status (p = 0.41).ConclusionsStone burden on imaging and prior symptomatic stone events were associated with not donating. Younger age and stone burden on imaging were the primary risk factors for a symptomatic kidney stone event after donor evaluation.

Objective To determine the frequency and accuracy of diffusion restriction (DR) of the retina and/or optic nerve (ON) detection on standard brain magnetic resonance diffusion-weighted imaging (DWI-MRI) in patients presenting with acute non-arteritic central retinal artery occlusion (CRAO). Methods This is a retrospective case-control study that includes all consecutive patients presenting to our tertiary academic center from 2013-2021 with acute non-arteritic CRAO (cases) or acute ischemic stroke syndrome (controls, age and gender-matched) that had brain MRI performed within 14 days from symptom onset. Two neurology residents (junior and senior), a vascular neurologist, and two neuroradiologists, blinded to the site of CRAO, independently reviewed the brain MRIs to assess for the presence of retina and ON DR. The consensus agreement between the two neuroradiologists was used to perform sensitivity and specificity analyses and calculate inter-rater reliability (prevalence-adjusted bias-adjusted kappa coefficient). Results A total of 128 patients with acute non-arteritic CRAO (mean (SD) age 69 (14) years; 50% female; median time from CRAO to DW-MRI 2 days (IQR 1-5)) and 128 age and gender-matched controls with acute cerebral ischemia were included. After the neuroradiologist consensus, DR was correctly identified in the retina or ON in 51/128 (39.8%) CRAO cases, retina alone 27.3%, ON alone 24.2%, and both retina and ON 11.7%, with almost perfect neuroradiologists’ inter-rater reliability for retina (K = 0.91) and ON (K = 0.83). Among controls, the retina DR was identified in 1/128 (0.8%) and ON DR in 5/128 (3.9%). The sensitivity, specificity, positive predictive value, and negative predictive value were 28.1%, 99.2%, 97.3%, and 58.0% for retina DR, and 27.3%, 96.1%, 87.5%, and 56.9% for ON DR. Conclusions Though experienced neuroradiologists identified retina and ON DR with excellent inter-rater reliability, these are infrequent findings in real world CRAO practice, with excellent specificity but limited sensitivity. Prospective studies with larger cohort of patients, optimization of standardized orbit DWI-MRI protocols are needed to facilitate a more accurate and reliable identification of retina and ON DR in acute CRAO.

ABSTRACTBackgroundAdenovirus (ADV) infection can lead to significant morbidity and mortality in immunocompromised patients, particularly in those with hematopoietic stem cells or solid organ transplants. The incidence of ADV infection in kidney transplant (KT) is not well‐defined as ADV is often asymptomatic and not routinely checked.MethodsThis retrospective case‐series study included KT and simultaneous pancreas‐KT (SPKT) recipients from January 1, 2008, to January 31, 2024, across three Mayo Clinic sites (Arizona, Florida, and Minnesota) with symptomatic adenovirus polymerase chain reaction cases. The primary outcomes were allograft function at various intervals post‐ADV infection, allograft, and patient survival.ResultsWe report one of the largest multi‐site case series regarding outcomes of ADV in KT with 17 patients. The median time to ADV infection was 30 weeks (5–74). Five patients (29%) developed disseminated infection. Nine patients (53%) of the entire cohort experienced graft loss within a median of 35 (4–168) weeks, with four (44%) of graft loss attributed to ADV. Nine patients (53%) developed rejections post‐ADV infection with a median of 4 (2–8) weeks after resolution. One patient died from acute hypoxic respiratory failure from ADV infection.ConclusionADV should be considered in KT/SPKT patients with renal dysfunction, hematuria, and with or without fever. Despite the low mortality rate, there is a significant risk of graft loss and rejection after ADV infection. It is crucial to screen for ADV and develop intervention strategies for treatment. Further multicenter studies are needed to better define, stage, and manage ADV infection. image

BACKGROUND Cutaneous lichen planus (LP) is a recalcitrant, difficult-to-treat, inflammatory skin disease characterized by pruritic, flat-topped, violaceous papules on the skin. Baricitinib is an oral Janus kinase (JAK) 1/2 inhibitor that interrupts the signaling pathway of IFN-γ, a cytokine implicated in the pathogenesis of LP. METHODS In this phase II trial, 12 patients with cutaneous LP received 2 mg daily baricitinib for 16 weeks, accompanied by in-depth spatial, single-cell, and bulk transcriptomic profiling of pre- and posttreatment samples. RESULTS An early and sustained clinical response was seen, with 83.3% of patients responsive at week 16. Our molecular data identified a unique, oligoclonal IFN-γ, CD8 + , and CXCL13 + cytotoxic T cell population in LP skin and demonstrated a rapid decrease in IFN signature within 2 weeks of treatment, most prominently in the basal layer of the epidermis. CONCLUSION This study demonstrates the efficacy and molecular mechanisms of JAK inhibition in LP. TRIAL REGISTRATION NCT05188521 FUNDING Eli Lilly, Appignani Benefactor Funds, 5P30AR075043, Mayo Clinic Clinical Trials Stimulus Funds.

Introduction Telestroke enables timely and remote evaluation of patients with acute stroke syndromes. However, stroke mimics represent more than 30% of this population. Given the resources required for the management of suspected acute ischemic stroke, several scales have been developed to help identify stroke mimics. Our objective was to externally validate four mimic scales (Khan Score (KS), TeleStroke Mimic Score (TS), simplified FABS (sFABS), and FABS) in a large, academic telestroke network. Methods This is a retrospective, Institutional Review Board-exempt study of all patients who presented with suspected acute stroke syndromes and underwent video evaluation between 2019 and 2020 at a large academic telestroke network. Detailed chart review was conducted to extract both the variables needed to apply the mimic scales, the final diagnosis confirmed by final imaging, and discharge diagnosis (cerebral ischemic vs stroke mimic). Overall score performance was assessed by calculating the area under curve (AUC). Youden cutpoint was established for each scale and used to calculate sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and accuracy. Results A total of 1043 patients were included in the final analysis. Final diagnosis of cerebral ischemia was made in 63.5% of all patients, and stroke mimic was diagnosed in 381 patients (36.5%). To predict stroke mimic, TS had the highest AUC (68.3), sensitivity (99.2%), and NPV (77.3%); KS had the highest accuracy (67.5%); FABS had the highest specificity (55.1%), and PPV (72.5%). Conclusions While each scale offers unique strengths, none was able to identify stroke mimics effectively enough to confidently apply in clinical practice. There remains a need for significant clinical judgment to determine the likelihood of stroke mimic at presentation.