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AbstractBackgroundRecent studies showed that neuroinflammation plays a key role in triggering specific neuropsychiatric symptoms (NPS), such as irritability and agitation, in individuals with Alzheimer’s disease (AD). While prior studies showed an association between tau pathology and all NPS domains, the extent to which tau influences each specific NPS domain remains unclear. Here, we aim to investigate the association of tau and NPS domains in the AD continuum. We hypothesize that tau plays a comparatively greater effect on the emergence of psychotic symptoms compared to other NPS domains.MethodWe assessed 56 individuals (21 cognitively unimpaired (CU), 23 MCI, and 12 AD dementia) from the HEAD study who underwent clinical assessments with the Neuropsychiatry Inventory Questionnaire (NPI‐Q) and had positron emission tomography (PET) for amyloid‐β (Aβ) ([18F]AZD4694 or [11C]PiB), and tau tangles ([18F]MK6240) at the same visit. We selected individuals with an NPI‐Q total score ≥1. Tau SUVR values were tailored with a mask from Braak stages I‐VI, using the inferior cerebellar gray matter as reference region. Leave‐one‐out voxel wise and linear regression tested the association between each NPI‐Q domain and biomarkers accounting for age, sex, cognitive status, and study site.ResultCI individuals had significantly higher NPI‐Q score and Braak VI PET SUVR than CU individuals (Table 1). NPI‐Q score was significantly associated with tau‐PET in the periRolandic and supplementary motor cortex (Figures 1A). Linear regression showed that NPI‐Q associates with tau‐PET in the Braak stage VI (Figure 1B). Leave‐one‐out regression analysis revealed that delusions, motor disturbances, and anxiety contributed most to the association between tau‐PET and NPS (Figure 2A, C). These domains presented a higher magnitude of association compared to each other NPI‐Q domain (Figure 2B). Notably, irritability, agitation, and disinhibition exerted a negative effect to the association, emphasizing that tau may not play a role in the development of these symptoms (Figure 2A, D)ConclusionOur study supports previous evidence suggesting that irritability and agitation may not be triggered by tau, but rather by other pathological process such as neuroinflammation. These findings provide additional rationale for the therapeutics aiming to mitigate irritability and agitation in AD patients.

Bioprosthetic aortic valve degeneration (BAVD) is a significant clinical concern following both transcatheter aortic valve replacement (TAVR) and surgical aortic valve replacement (SAVR). The increasing use of bioprosthetic valves in aortic valve replacement in younger patients and the subsequent rise in cases of BAVD are acknowledged in this review which aims to provide a comprehensive overview of the incidence, diagnosis, predictors, and management of BAVD. Based on a thorough review of the existing literature, this article provides an updated overview of the biological mechanisms underlying valve degeneration, including calcification, structural deterioration, and inflammatory processes and addresses the various risk factors contributing to BAVD, such as patient demographics, comorbidities, and procedural variables. The difficulties in early detection and accurate diagnosis of BAVD are discussed with an emphasis on the need for improved imaging techniques. The incidence and progression of BAVD in patients undergoing TAVR versus SAVR are compared, providing insights into the differences and similarities between the two procedures and procedural impacts on valve longevity. The current strategies for managing BAVD, including re-intervention options of redo surgery and valve-in-valve TAVR, along with emerging treatments are discussed. The controversies in the existing literature are highlighted to offer directions for future investigations to enhance the understanding and management of BAVD.

OBJECTIVE Preclinical studies suggest that robotic carotid artery stenting (CAS) could be superior to manual CAS. However, very limited comparative data exist for patients who have undergone robotic versus manual CAS. In addition, no data exist comparing the costs of manual and robotic CAS. METHODS All robotic CAS cases at two academic neurosurgery centers were retrospectively reviewed and 1:1 propensity matched with manual CAS cases. Personnel costs, supply costs, and total procedure costs were collected in collaboration with hospital administration by using time-driven activity-based cost analysis. RESULTS A total of 24 robotic CAS operations were performed between 2019 and 2023. Comorbidities and baseline procedural characteristics were well matched between robotic and manual cases. Unplanned manual conversion was observed in only 1 robotic case (4.2%). Robotic CAS complications and outcomes were comparable to manual. Robotic CAS was associated with a significantly increased fluoroscopy time (29.0 vs 19.2 minutes; p < 0.001). Robotic procedure time (88.9 ± 18.2 minutes) was significantly (p = 0.003) longer than manual time (68.72 ± 22.4 minutes). Health personnel costs ($1589.71 ± $176.92 vs $1375.99 ± $233.39, p = 0.005); supply costs ($3918.25 ± $421.20 vs $2152.74 ± $1030.26, p < 0.001); and total procedure costs ($5306.11 ± $608.95 vs $3437.56 ± $1165.67, p < 0.001) were greater for robotic CAS. CONCLUSIONS In the first multicenter study and largest sample to date, the authors show that robotic CAS, with a low rate of procedural failure and postoperative complications, is safe and feasible. In addition, robotic CAS achieves comparable clinical outcomes to manual CAS. Robotic CAS was associated with increased fluoroscopy time, but fluoroscopy time decreased as operators gained familiarity with the CorPath GRX system. Robotic CAS was associated with a greater procedural cost, which was driven by greater personnel and supply costs. Robotic CAS failed to show superiority to manual CAS. These findings set a foundation for randomized controlled trials of robotic CAS, and also highlight the need for further studies to optimize robotic CAS and reduce its associated costs.

Background Lipoprotein(a) [Lp(a)] is an independent, causal risk factor for cardiovascular disease. However, it is still unclear whether controlling low-density lipoprotein cholesterol (LDL-C) to optimal levels can attenuate cardiovascular risk mediated by elevated Lp(a), especially in the setting of secondary prevention. Methods Adult patients with a baseline Lp(a) measurement who underwent percutaneous coronary intervention (PCI) and reached their LDL-C target levels (<70 mg/dl) at Mayo Clinic sites between 2006 and 2017 were included. Primary outcomes included major adverse cardiovascular events (MACE) and all-cause mortality. Kaplan–Meier curves were created to compare the survival probabilities among patients with Lp(a) ≥ 50 mg/dl compared with Lp(a) < 50 mg/dl. Multivariable Cox regression analyses were performed to quantify the association of elevated Lp(a) with our relevant outcomes and to control for possible confounders. Results In total, 878 patients (median age: 68 years, and 74% males) who underwent PCI were included for analysis. Of them, 29.7% had elevated Lp(a) ≥ 50 mg/dl. Kaplan–Meier curves did not reveal any significant difference in survival probabilities for elevated Lp(a) for any outcome including MACE (P = 0.91), all-cause mortality (P = 0.26), or the separate MACE components. Similarly, the multivariable analysis showed no significant association for MACE (hazard ratio: 1.07, 95% confidence interval: 0.84–1.37) or all-cause mortality (hazard ratio: 0.98, 95% confidence interval: 0.74–1.30). Conclusion In patients who underwent PCI and have their LDL-C controlled below 70 mg/dl, no significant association was found between elevated Lp(a) ≥ 50 mg/dl and risk for MACE or all-cause mortality.

Introduction: Pulmonary hypertension (PHTN) is common in patients with chronic kidney disease (CKD), however categorization as precapillary or postcapillary is challenging due to the need for invasive right heart catheterization (RHC). Studies have validated transthoracic echocardiography (TTE) to characterize PHTN and ECG-artificial intelligence (AI) to predict diastolic dysfunction risk. The utility of these noninvasive tools in patients with CKD is unknown. Methods: Retrospective analysis of patients with end stage CKD who underwent RHC between 2011 and 2021. Patients with PHTN (pulmonary artery pressure >20mmHg on RHC) were categorized as having precapillary (pulmonary capillary wedge pressure, PCWP, ≤15mmHg and pulmonary vascular resistance, PVR, >2WU) or postcapillary PHTN (PCWP >15mmHg and PVR ≤2WU for isolated postcapillary or PVR >2WU for combined). TTE and ECG within 3 months of RHC were obtained. TTE measurements were used to calculate ePLAR (echocardiographic pulmonary to left atrial ratio); tricuspid regurgitant peak velocity (TRV max ) divided by mitral E/e’. ECGs were analyzed with an AI risk tool for diastolic dysfunction (score 0-3, increasing with increasing risk). Receiver operating curves (ROC) evaluated the performance of these tests. Results: 60 patients were included; 16 (27%) with precapillary and 44 (73%) with postcapillary PHTN. ROC analysis found good accuracy for both ECG-AI diastolic dysfunction risk score to predict precapillary PHTN with AUC 0.724 (sensitivity=60% and specificity=88% for an ECG score value ≤1) and ePLAR with AUC 0.715 (sensitivity=75% and specificity=70% for ePLAR >0.17m/sec). Highest accuracy for detection of precapillary PHTN was reached by combination of ePLAR and ECG-AI tool, with AUC 0.756 (sensitivity=73%, accuracy of 86% for a value ≤1.17). Conclusions: ECG-AI generated diastolic risk score of 0-1 (low risk) and high ePLAR showed good accuracy in characterizing precapillary PHTN in patients with end stage CKD. The combination of these noninvasive tools further increased the diagnostic accuracy, reflecting its potential utility in classification of patients with CKD and PHTN, a crucial determinant of the ideal therapeutic plan in kidney transplant candidates.

Background: Atrial fibrillation (AF), the most common clinically managed cardiac arrhythmia, is known to increase the risk of heart failure, stroke, and mortality. Lipoprotein(a) [Lp(a)], a well-established risk factor for atherosclerotic cardiovascular disease (ASCVD), also plays a role in cardiovascular health. However, the influence of Lp(a) on the development of AF, independent of its association with ASCVD, remains unclear. Hypothesis: Elevated Lp(a) may be associated with increased risk of new-onset AF. Methods: A retrospective study was conducted on patients from the three Mayo Clinic sites who had their Lp(a) levels measured and had no prior history of AF. Patients were categorized into two groups based on their serum Lp(a) concentrations: high Lp(a) (≥50 mg/dL) and low Lp(a) (<50 mg/dL). New AF diagnoses were identified during the follow-up period. Survival probabilities between the two Lp(a) groups were compared using the Kaplan–Meier curve and the Log-Rank test. Cox regression analyses, both univariable and multivariable, were performed to evaluate established risk factors and compare the risk of new-onset AF between the high and low Lp(a) groups. Results: A total of 108,930 patients were included (median age: 55 years, 58% males), with a follow-up duration for up to 10 years. Incident AF was detected in 8432 (7.7%) patients. Median serum levels of Lp(a) were significantly higher in patients with AF versus non-AF patients: 15 (IQR 43) vs. 12 (IQR 34) mg/dL, p<0.001. The percentage of patients having elevated Lp(a) was significantly higher in the AF group versus non-AF group: 2119 (25%) vs 21151 (21%), p<0.001. Survival probability for new-onset AF was significantly lower in patients with elevated Lp(a) compared with those with low Lp(a) (log rank p<0.001, Figure 1). In the univariate analysis, high Lp(a) levels were associated with a 17% increase in the risk of AF (HR = 1.17, 95% CIs: 1.12 to 1.23). The multivariate analysis adjusted for well-established risk factors for AF showed a less strong but still significant association, with a 10% increase in AF risk (HR = 1.10, 95% CI: 1.05 to 1.15). Conclusion: Our study suggests that elevated Lp(a) (≥50 mg/dL) seems to be an independent risk factor for new-onset AF. Future prospective studies are still warranted to validate our results.

Background: Secondary prevention after percutaneous coronary interventions (PCIs) is still challenging and lipoprotein(a) [Lp(a)] is believed to be a residual risk factor in this setting. However, the effect of Lp(a) in case of well-controlled low-density lipoprotein cholesterol (LDL-C) is still unclear. The interaction between Lp(a) and LDL-C has been studied in primary prevention but still needs to be investigated in secondary prevention. Hypothesis: Achieving adequate LDL-C control after PCI may reduce the cardiovascular (CV) risk associated with Lp(a). Methods: A retrospective study of consecutive patients who underwent PCI and reached their LDL-C target levels (<70mg/dL) at three academic centers sites between 2006 and 2017. All included patients must have an Lp(a) measurement before the PCI intervention. Clinical outcomes on 10-year follow-up were collected by reviewing the electronic patients' records. The primary outcomes included all-cause mortality (ACM) and major adverse CV events (MACE) including non-fatal MI, ischemic stroke, coronary revascularization, and CV death. Kaplan-Meier curves were created to compare the survival probabilities among patients with high Lp(a) (≥50mg/dL) versus those with low Lp(a) (<50mg/dL). Univariate and multivariate Cox regression analyses were performed to quantify the association of elevated Lp(a) with outcomes and control for potential confounders. Results: In total, 878 patients (median age = 68 years, 74% males) were included in the analysis. Of them, 242 (27.6%) had high Lp(a) ≥50mg/dL. Kaplan Meier analyses did not reveal any significant difference in survival probabilities across the Lp(a) groups for any of the outcomes (Figure 1). The results were consistent in univariate (MACE, HR: 1.08 [95%CIs 0.85-1.35]; ACM, HR: 0.97 [95% CI 0.76-1.23]) and multivariate analyses (MACE, HR: 1.14, [95% CIs 0.90-1.45]; ACM, HR: 1.08 [95% CI 0.84-1.39]). Conclusion: These findings suggest that, in patients who underwent PCI and achieved an LDL-C target of <70 mg/dL, elevated Lp(a) levels were not associated with and increased risk of MACE or mortality. Controlling the LDL-C should still be the cornerstone in secondary prevention after PCI, however, larger prospective studies are still warranted to validate our results.

Background: Myocarditis is a dreaded complication of immune-checkpoint inhibitor (ICI) therapy but challenging to diagnose. There are no published data comparing the two leading diagnostic criteria for ICI myocarditis and their association with cardiovascular events. Methods: Patients treated with ICI and cardiac Troponin (cTnT) measurements thereafter at a tertiary institution from 2011 to 2022 were identified. Charts were reviewed for ICI-related myocarditis according to the Bonaca et. al criteria and the ESC-ICOS guideline criteria. A propensity matched control group was identified of patients treated with ICI but without developing myocarditis. Medical records were reviewed for baseline characteristics and long-term outcomes, including cardiac death, MACE (myocardial infarction, TIA/stroke, new heart failure diagnosis), and arrhythmias (V-tach, A-fib, complete heart block). Results: A total of 59 patients were identified as having a diagnosis of ICI-related myocarditis per Bonaca criteria (16 having definite, 13 probable and 30 possible myocarditis), and 47 met the ESC-ICOS guideline criteria. Mean age was 73.1±10.2 years, 60.1% were male, median follow-up was 2.5 years. ICI-related myocarditis as diagnosed by both diagnostic criteria had prognostic value for cardiac death (HR 13.94, 95%CI 1.84-105.64, p=0.011 per Bonaca, HR 6.22, 95%CI 1.77-21.88, p=0.004 per ESC-ICOS), MACE, (HR 3.17, 95%CI 1.34-7.47, p=0.008 per Bonaca, HR 2.97, 95%CI 1.37-6.45, p=0.006 per ESC-ICOS), and arrhythmias (HR 1.93, 95%CI 1.10-3.38, p=0.022 per Bonaca, HR 2.09, 95%CI 1.21-3.60, p<0.001 per ESC-ICOS), (Figures 1 and 2). There was no significant difference for cardiac death (AUC 0.75 for Bonaca, AUC 0.74 for ESC, p=0.765) or MACE (AUC 0.66 for Bonaca, AUC 0.66 for ESC, p=0.916) when both criteria were compared with each other. Conclusion: The ESC-ICOS criteria were more restrictive than the Bonaca criteria for the diagnosis of ICI-related myocarditis but similar in terms of prognostic value.

Background: VICTORION-INITIATE (NCT04929249) showed significantly greater LDL-C lowering in patients (pts) with ASCVD with an inclisiran first (IF) strategy (adding inclisiran immediately on failure to achieve LDL-C <70 mg/dL on maximally tolerated statin therapy) vs usual care (UC). Tokenization can be leveraged to link clinical trial data to pt-level real-world data (RWD) to provide a comprehensive overview of the pt journey pre- and post-trial and enhance understanding of clinical trial and long-term pt outcomes. Aim: To utilize tokenization and linked RWD to characterize the pt journey pre-VICTORION-INITIATE enrollment. Methods: Eligible pts from VICTORION-INITIATE were deidentified and tokenized with unique IDs, allowing linking to RWD (EMR, claims, hospital, and lab records) to follow the pt journey in the 3-year pre-trial and 2-year post-trial periods. Here we present demographics, clinical characteristics, and lipid-lowering therapy (LLT) use of pts with linked pre-trial RWD. Results: Of 450 pts randomized, 383 (85.1%) were linked with pre-trial RWD (IF arm, n=193; UC arm, n=190); 26.9% were female, first available recorded mean (SD) age was 64 (9.36) years. Among the 74.2% (n=284) of pts with linked, pre-trial, lipid test RWD, mean (SD) earliest and latest LDL-C values were 100.1 mg/dL (35.70) and 99.3 mg/dL (30.06), respectively, for pts in the IF arm vs 97.3 mg/dL (40.43) and 97.8 mg/dL (27.60) for pts in the UC arm ( Table ). Overall, in the pre-trial period, LLT was dispensed/prescribed to 66.1% of pts, statins to 64.5%, ezetimibe to 4.4%, and PCSK9i to 4.4%. Of pts with ≥1 recorded ASCVD events in the pre-trial period (n=141), 53.2% and 68.8% had available LLT dispensing/prescription records pre- and post-event, respectively. Conclusions: In the 3 years pre-VICTORION-INITIATE, mean LDL-C levels were above recommended goals, non-statin LLT prescription was infrequent, and ~31% of pts with ≥1 recorded ASCVD event had no evidence of post-event LLT use, highlighting a need for more aggressive LDL-C management. Full data visibility for each pt is a limitation of this approach. Tokenization post-trial will allow for long-term evaluation of LLT practices.

Background: New-onset atrial fibrillation (AF) is common among kidney transplant (KTx) recipients and is associated with reduced patient survival. Predictors of AF after KTx are not well understood, although AF can be associated with traditional and non-traditional risk factors. While artificial intelligence-enabled electrocardiography (AI-ECG) has shown promise in predicting incident AF, its predictive and prognostic implications in the KTx population have not yet been evaluated. Hypothesis: AI-ECG can predict new-onset AF and carries prognostic implications in patients undergoing KTx. Aims: To evaluate the clinical implications of applying AI-ECG to the preoperative ECGs of recipients of a KTx. Methods: Patients without a history of AF who underwent KTx at three referral centers between 2011 and 2021, with at least one preoperative ECG, were included in this retrospective study. Preoperative ECGs were analyzed using a previously developed AI-ECG algorithm to estimate the probabilities of new-onset AF. Based on these probabilities, patients were categorized into two groups: high and low probability of incident AF. The optimal cut-off value for the AI-ECG tool was determined using ROC analysis. The incidence of new-onset AF and mortality at 5 years post KTx were compared between these two groups using univariate and multivariate Cox regression analyses. Results: In total, 6246 patients were included (mean age 52.9 ±14.3 years, 58.7% males). A pre-transplant AI-ECG probability of AF >10% was identified as the most accurate cutoff point to distinguish between patients at low risk and high risk of incident AF (ROC = 0.72). The study found that a preoperative AI-ECG high risk of AF demonstrated not only a strong association with new-onset AF (HR 2.54, 95%CI 2.02-3.19, p<0.001 on multivariable analysis, Figure 1A ) but was also associated with an increased risk of mortality both on univariate (HR 2.73, 95%CI 2.34-3.18, p<0.001) and multivariate (HR 1.57, 95%CI 1.29-1.91, p<0.001 ) analysis at 5-year follow-up ( Figure 1B ). Conclusion: The application of AI-ECG to a single widely available test may help assess the risk of new-onset AF and mortality in patients undergoing KTx. Accurate risk stratification may identify a high-risk subgroup of transplant recipients who can benefit from closer AF monitoring, risk factor modification, and early management.