There are several coronary diseases that human beings can suffer from, which in themselves generate health deterioration and can lead to the development of other diseases that diminish the quality of life. Ischemic diseases are unique in that they are evidenced by blockages generated by the accumulation of fat that impedes circulation, triggering heart and brain-related problems. By means of fractional Brownian motion in relation to Hurst’s parameter, an analysis of a data of 137 patients aged between 30 and 71 years, who present some type of ischemic disease such as mixed, restricted, effort angina and angina pectoris, is performed. The data used was European, which is found in the PhysioNet open-access medical research data repository, managed by the Massachusetts Institute of Technology Computational Physiology Laboratory. This data shows the Hurst coefficient calculations associated with each type of ischemic heart disease.
Funding Acknowledgements Type of funding sources: None. Background A new functional mapping strategy based on targeting deceleration zones (DZs) has become one of the most commonly used strategies within the armamentarium of substrate-based ablation methods for ventricular tachycardia (VT) in patients with structural heart disease. The classic conduction channels detected by voltage mapping can be accurately determined by cardiac magnetic resonance (CMR). Objectives To analyze the evolution of DZs during ablation and their correlation with CMR. Methods Forty-two consecutive patients with scar-related VT undergoing ablation after CMR (October 2018-December 2020) were included (medium age 65.3±11.8 years; 94.7% male; 73.7% ischemic heart disease). Baseline DZs and their evolution in isochronal late activation remaps were analyzed. A comparison between DZs and CMR conducting channels (CMR-CCs) was realized. Patients were prospectively followed for VT recurrence for one year. Results Overall, 95 DZs were analyzed, 93.68% of which were correlated with CMR-CCs: 44.8% located in the middle segment and 55.2% located in the entrance/exit of the channel. Remapping was performed in 91.7% of patients (1remap: 33.3%, 2remaps: 55.6% and 3remaps: 2.8%). Regarding the evolution of DZs, 72.2% disappeared after the first ablation set, with 14.13% not ablated at the end of the procedure. A total of 32.5% of DZs in remaps correlated with a CMR-CCs already detected, and 17.5% were associated with an unmasked CMR-CCs. One-year VT recurrence was 22.9%. Conclusions DZs are highly correlated with CMR-CCs. In addition, remapping can lead to the identification of hidden substrate initially not identified by electroanatomic mapping but detected by CMR.
Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): MPL received the Catalan Society of Cardiology Research Grant in 2019 and 2020 (Catalonia, Spain); the Josep Font Grant (2019-2022) from Hospital Clínic Barcelona (Catalonia, Spain). Background Left bundle branch pacing (LBBP) has emerged as an alternative to biventricular pacing. However, lack of a systematic stepwise application of the left bundle branch (LBB) capture criteria complicates implantation. Objective To define a stepwise application of LBBP capture criteria that will simplify implantation and ensure LBB capture. Methods A cohort of 24 patients from the LEVEL-AT trial who received LBBP and had electrocardiographic imaging (ECGI) at 45 days post-implant were included. The usefulness of ECG and electrogram based criteria to predict accurate LBB capture were analyzed. A two-step approach was developed to ensure LBB capture. The gold standard used to confirm LBB capture was the change in ventricular activation pattern and shortening in left ventricular activation time, assessed by ECGI. Results Twenty-two (91.6%) patients showed LBBP capture on ECGI. All patients fulfilled pre-screwing requisites: lead in septal position in left-oblique projection and W paced morphology in V1. In the first step, presence of either right bundle branch conduction delay pattern (qR or rSR in V1) or left bundle branch capture Plus (QRS ≤120ms) resulted in 95% sensitivity and 100% specificity to predict LBB capture, with an accuracy of 95.8%. In the second step, the presence of selective capture (100% specificity, only 41% sensitivity) or a spike-R<80ms (100% specificity, sensitivity 46%) ensured 100% accuracy to predict LBBP capture. Conclusions Stepwise application of ECG and electrogram criteria ensured an accurate assessment of left conduction system capture.
Alzheimer’s disease is a neurodegenerative cognitive, affective, and behavioral disorder aligned to the aging process and other coronary diseases. To contribute to the early diagnosis of the disease, a neuroimaging treatment is implemented through a preprocessing to subsequently calculate the fractal dimension associated with these images in order to propose an alternative to the one proposed in medical physics through positron emission tomography. In this work, a comparative analysis is made of a previous work using the Box Counting methodology versus the calculation of the fractal dimension by means of software developed by the researchers based on the same method. The differences between the fractal dimensions of the neuroimages of control patients and patients with the presence of the disease are maintained showing a lower value of fractal dimension in patients with the disease due to the physical deterioration of the brain.
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