To simulate a short segment of the aorta, we studied wave propagation in an elastic tube with a side branch balloon. The small balloon simulated the organ (group of arterioles). Ligation of this side branch would reduce the moduli of the higher harmonics when the length of the side branch was appropriate. Electrical analogy of vessels was used to analyze this phenomenon. This simulation can explain the ligation results we found in rats. It may also clarify the discrepancies between the prediction of the Womersley equation and the experimental results. We suggest that the aorta and the closely attached organ can produce coupled oscillation; theoretically, this structure is equivalent to a resonance circuit.

BackgroundThe clinical factors associated with the recurrence of atrial fibrillation (Af) in patients undergoing catheter ablation (CA) are still ambiguous to date.Purpose1. To recognize preoperative serologic factors and clinical features associated with Af recurrence after the first ablation treatment. 2. To Develop a Logical Regression Model for Predicting the Likelihood of Recurrence Within 1 Year After the Initial Radio-Frequency Catheter Ablation (RFCA) Therapy.MethodsAtrial fibrillation patients undergoing RFCA at our institution from January 2016 to June 2021 were included in the analysis (n = 246). A combined dataset of relevant parameters was collected from the participants (clinical characteristics, laboratory results, and time to recurrence) (n = 200). We performed the least absolute shrinkage and selection operator (Lasso) regression with 100 cycles, selecting variables present in all 100 cycles to identify factors associated with the first recurrence of atrial fibrillation. A logistic regression model for predicting whether Af would recur within a year was created using 70% of the data as a training set and the remaining data to validate the accuracy. The predictions were assessed using calibration plots, concordance index (C-index), and decision curve analysis.ResultsThe left atrial diameter, albumin, type of Af, whether other arrhythmias were combined, and the duration of Af attack time were associated with Af recurrence in this sample. Some clinically meaningful variables were selected and combined with recognized factors associated with recurrence to construct a logistic regression prediction model for 1-year Af recurrence. The receiver operating characteristic (ROC) curve for this model was 0.8695, and the established prediction model had a C-index of 0.83. The performance was superior to the extreme curve in the decision curve analysis.ConclusionOur study demonstrates that several clinical features and serological markers can predict the recurrence of Af in patients undergoing RFCA. This simple model can play a crucial role in guiding physicians in preoperative evaluation and clinical decision-making.

Korotkoff sounds (K-sounds) have been around for over 100 years and are considered the gold standard for blood pressure (BP) measurement. K-sounds are also unique for the diagnosis and treatment of cardiovascular diseases; however, their efficacy is limited. The incidences of heart failure (HF) are increasing, which necessitate the development of a rapid and convenient pre-hospital screening method. In this review, we propose a deep learning (DL) method and the possibility of using K-methods to predict cardiac function changes for the detection of cardiac dysfunctions.

Background. We have obtained prospective clinical outcomes using the brachial artery largely, such as Korotkoff sound and vasomotor function measurement by ultrasound guidance to predict the prognosis of cardiovascular diseases. Very few reports on the quantitative measurement of the relationship between the brachial artery blood flow and cardiac output have been reported. Purpose. (1) To investigate whether the quantitative relationship between the brachial artery blood flow and cardiac output existed. (2) To provide a theoretical basis for taking advantage of artificial intelligence (AI) using Korotkoff sound analogously as far as possible to predict the cardiac output. Methods. A total of 586 patients who underwent cardiac color ultrasound in our center from 2021.3 to 2021.7 were included for analyses. The vascular parameters of the right upper limb brachial artery (such as the Diameter, Area, Blood Velocity, and Flow) were measured immediately after the cardiac color ultrasound, and some basic clinical parameters (Age, Sex, BMI, and Disease) were recorded subsequently. Ultimately, the Mann–Whitney and independent sample T-test were used to analyze the data. Results. (1) The mean Rate of the brachial arterial blood flow to cardiac output was 1.23%, and the mean 95% CI was (1.18%, 1.29%), indicating that the value was mainly concentrated in the current value interval. The indicator demonstrates that there is no significant difference currently among the patients with hypertension, coronary heart disease, and cardiac dysfunction. (2) The brachial artery wall diameter (Dist) is significantly thicker in patients with coronary heart disease and hypertension compared to patients with other cardiovascular diseases. (3) Cardiac output augments remarkably in patients with hypertension. Conclusion. Our study suggests that the Rate (brachial artery blood flow/cardiac output) is a constant of 1.23% approximately. It provides a theoretical basis for the subsequent application of the artificial intelligence (AI) method to predict heart function using Korotkoff sound, cope with large computational amounts, and improve computational speed. It is also indirectly proved that hypertension can lead to a change in peripheral vascular hyperplasia and increase cardiac output.

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