Citations

Abstract Medical devices that use electromagnetic fields for diagnostic and therapeutic purposes are rapidly evolving. Understanding the interactions between electromagnetic signals and biological tissue is fundamental to developing safe, novel diagnostic and therapy treatments. This study characterizes the dielectric properties of porcine hearts from 10 male and 10 female animals. Dielectric properties are measured using an open-ended coaxial probe dielectric spectroscopy method over a frequency range of 0.5 to 20 GHz. Scatter parameters (S11) collected from various anatomical cardiac locations (LA, RA, LV, RV, SA, IAS, IVS) are converted into frequency-dependent complex permittivity. The calculated dielectric properties vary regionally within the heart, indicating heterogeneity in tissue properties observed at microwave frequencies.

The human voice is an important medium of communication and expression of feelings or thoughts. Disruption in the regulatory systems of the human voice can be analyzed and used as a diagnostic tool, labeling voice as a potential “biomarker”. Conversational artificial intelligence is at the core of voice-powered technologies, enabling intelligent interactions between machines. Due to its richness and availability, voice can be leveraged for predictive analytics and enhanced healthcare insights. Utilizing this idea, we reviewed artificial intelligence (AI) models that have executed vocal analysis and their outcomes. Recordings undergo extraction of useful vocal features to be analyzed by neural networks and machine learning models. Studies reveal machine learning models to be superior to spectral analysis in dynamically combining the huge amount of data of vocal features. Clinical applications of a vocal biomarker exist in neurological diseases such as Parkinson’s, Alzheimer’s, psychological disorders, DM, CHF, CAD, aspiration, GERD, and pulmonary diseases, including COVID-19. The primary ethical challenge when incorporating voice as a diagnostic tool is that of privacy and security. To eliminate this, encryption methods exist to convert patient-identifiable vocal data into a more secure, private nature. Advancements in AI have expanded the capabilities and future potential of voice as a digital health solution.

Background: Varicose veins (VVs) of the lower limbs, characterized by palpable, dilated, and tortuous veins, affect 2–73% of the global population. Artificial intelligence (AI) offers significant potential to enhance healthcare efficiency and decision-making, particularly in managing VVs through improved risk factor identification, diagnosis, and treatment planning. Objective: This abstract explores the role of AI in VV management, focusing on its applications in risk detection, image analysis, treatment planning, and surgical interventions, while addressing challenges to its widespread adoption. Methods: AI leverages advanced techniques such as computer vision and deep learning to analyze patient data, including medical history, symptoms, physical examinations, and imaging (e.g., ultrasounds, venography). It identifies patterns in large datasets to support personalized treatment plans, early risk detection, and disease severity assessment. Results: AI demonstrates promise in automating VV detection and classification, assessing disease severity, and aiding treatment planning. It enhances surgical interventions through preoperative planning, intraoperative navigation, and recurrence risk prediction. However, its adoption is limited by a lack of large-scale studies, concerns over accuracy, and the need for regulatory and ethical oversight. Conclusion: AI has the potential to revolutionize VV management by improving diagnosis, treatment precision, and patient outcomes. Further research, validation, and integration are critical to overcoming current limitations and fully realizing AI’s capabilities in clinical practice.

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.

Abstract Background and Aims Patients with inflammatory bowel disease (IBD) face increased risk of colorectal cancer (CRC). While the natural history of conventional dysplastic precursor lesions has been well-studied, the neoplastic potential of recently described nonconventional (NC) IBD-associated colonic mucosal lesions is unclear. We aimed to assess the incidence of antecedent NC lesions in patients with IBD who developed CRC. Methods A case-cohort study was performed to include patients with a diagnosis of IBD with or without CRC who underwent at least 2 surveillance endoscopic procedures at our institution between 1/1/2007 and 5/31/2023. NC lesions included serrated change and indefinite for dysplasia. Detection rates pre- and post-introduction of high-definition (HD) surveillance colonoscopy were compared. Results In total, 87 patients with IBD and CRC and 200 patients with IBD without CRC were identified. Of the cases, a majority had ulcerative colitis (n = 52, 60%), most commonly with extensive involvement (n = 46, 89%). Conventional (hazard ratio [HR] 2.18, 95% confidence interval [CI] 1.34-3.52) and NC (HR 2.28, 95% CI 1.59-3.26) lesions were associated with increased risk of CRC. Conventional lesions in the post-HD era appeared to have a stronger association with CRC (HR 2.79, 95% CI 1.62-4.77) than NC lesions (HR 1.62, 95% CI 0.86-3.06). Conclusions Both conventional and NC lesions seem to be associated with increased risk of CRC. Conventional lesions are more strongly associated with CRC than NC lesions in the post-HD era, but misclassifications in the pre-HD era may have resulted in a biased increased risk estimate for NC lesions.

Abstract Approximately 50% of prostate cancer (PCa) patients harbor fusions involving the TMPRSS2 and ERG genes. Despite this, tailored therapies targeting the fused gene, tERG , remain undeveloped. Our study analyzed biopsy samples from two clinical trials assessing the efficacies of androgen receptor (AR) signaling inhibitors (ARSIs). The results revealed that tERG promotes resistance to ARSIs and is associated with elevated levels of the glucocorticoid receptor (GR). Subsequent assays showed that GR directly interacts with tERG, alleviates allosteric autoinhibition and prevents chemotherapy-induced tERG degradation. In PCa models, either inhibiting GR or lowering cortisol levels suppressed tumor growth in tERG-positive models, but not in fusion-negative models. In addition, patient-derived fusion-positive xenografts displayed enhanced sensitivity to combined GR and AR inhibitors. Collectively, these findings highlight TMPRSS2-ERG as a new biomarker and propose that simultaneous inhibition of GR and AR may specifically benefit tERG -positine patients. However, GR stimulatory corticosteroid therapies may not be advisable for this patient subgroup.

Background: PAINESD score was established as a predictor of periprocedural acute hemodynamic instability, long-term mortality and heart failure among patients undergoing catheter ablation for ventricular tachycardia (VT-CA). Objective: To assess the validity of PAINESD score and compare outcomes of high-risk patients undergoing catheter ablation for ventricular tachycardia (VT) with and without mechanical circulatory support (MCS) use during procedure. Methods: We conducted an observational dual-center study of consecutive patients with SHD undergoing VT-CA over a decade (2012-2022). The PAINESD score, based on 7 variables (COPD, age >60 years, general anesthesia, ischemic cardiomyopathy, NYHA class III or IV, ejection fraction <25%, VT storm, and diabetes mellitus), was calculated and categorized into low risk (<10), intermediate risk (10-16), and high risk (>16) as previously reported. Two survival analyses were performed to compare outcomes between different groups: one using all-cause mortality or heart transplant as the event, and another using recurrent or repeat ablation as the event. Multivariable Cox proportional hazards regression models were used to calculate hazard ratios for each PAINESD category and to determine the hazard ratio for the use of MCS among high-risk patients. Results: We found that between 2012 to 2022, 559 ablations were performed on 441 patients. There were 296 (53%), 182 (32.6%) and 81(14.5%) patients in low, medium, and high risk. Using low risk as reference, aHR for medium risk was 2.1 (1.24-3.7; p=0.006) and for high risk was 4.6(2.54-8.3; p <0.001). Among patients with high PAINESD score (n=81), 5 patients (6.2%) required MCS (Intra-arterial balloon pump (IABP)=1, ECMO only=1, ECMO+IABP=1, bypass=2). 4/5 (80%) patients on MCS stayed on them post procedure, except one patient on IABP. In this cohort, there was no difference between patients with and without MCS in primary outcome [aHR= 1.6 (0.48-5.4); p=0.43] and in secondary OUTCOME [1.29 (0.3-5.5; p=0.735)]. Conclusion: PAINESD was a significant predictor of mortality or heart failure, but it did not help in prediction of recurrence of VT, or repeat VT-CA.

Introduction: Tricuspid regurgitation (TR) is a common complication of right ventricle lead extraction (RVLE) in 5 to 10% of cases. This study aims to identify clinical outcomes such as predictors of heart failure hospitalization, need for tricuspid valve intervention, and death among patients with new severe TR after device lead removal (DLR). Methods: Patients who underwent DLR (pacemaker/ICD) between 3/1997 and 3/2024 were identified. Those who had an echocardiogram before and after RVLE with evidence of new severe TR were included. Cox univariable regression controlling for current age was used to assess association with death. Prentice Williams Peterson total time (PWPTT) Cox univariable regression was used to determine the rate of heart failure hospitalization up to three events per subject. Bivariable cox regression was used to control for ejection fraction for ICD and coil removal. Analysis was conducted using Stata IC16. Results: We identified 2,122 people who underwent RVLE, of whom 90 (4.24%) developed new severe TR and were included in the analysis. There were 68 hospitalizations among 38 people at a median of 2 years following lead extraction (IQR 0.57 to 4.5 years). The rate of hospitalization was 11.60 [9.14 to 14.71] per 100 person-years. Removal of an ICD was associated with increased hospitalization (HR 5.48 p<0.001) but not mortality (HR 1.21, p=0.707). Removal of a single coil ICD lead was associated with increased hospitalization rate (HR 3.01, p=0.031) but not mortality (HR =0.51, p=0.380). Removal of dual coil ICD lead was associated with more than a tenfold increase in hospitalization rate (HR 11.55, p=0.001) and four times the mortality rate (HR 4.05, p=0.031) (Figures 1&2). The presence of an abandoned (pacemaker/ICD) lead was associated with increased hospitalization (HR 5.75, p=0.004) and mortality (HR4.95, p=0.034). There was no change in hospitalization rate following tricuspid valve replacement (HR 1.33, p=0.716, n=18). Conclusion: Among people with new severe TR following DLR, the characteristics of the leads are strongly correlated with morbidity and mortality.