Assessment of late gadolinium enhancement in hypertrophic cardiomyopathy improves risk stratification based on current guidelines.

BACKGROUND AND AIMS: Identifying patients with hypertrophic cardiomyopathy (HCM) who are candidates for implantable cardioverter defibrillator (ICD) implantation in primary prevention for sudden cardiac death (SCD) is crucial. The aim of this study was to externally validate the 2022 European Society of Cardiology (ESC) model and other guideline-based ICD class of recommendation (ICD-COR) models and explore the utility of late gadolinium enhancement (LGE) in further risk stratification. METHODS: Seven hundred and seventy-four consecutive patients who underwent cardiac magnetic resonance imaging were retrospectively enrolled. RESULTS: Forty-six (5.9%) patients reached the SCD-related endpoint during 7.4 ± 2.5 years of follow-up. Patients suffering from SCD had higher ESC Risk-SCD score (4.3 ± 2.4% vs. 2.8 ± 2.1%, P < .001) and LGE extent (13.7 ± 9.4% vs. 4.9 ± 6.6%, P < .001). Compared with the 2014 ESC model, the 2022 ESC model showed increased area under the curve (.76 vs. .63), sensitivity (76.1% vs. 43.5%), positive predictive value (16.8% vs. 13.6%), and negative predictive value (98.1% vs. 95.9%). The C-statistics for SCD prediction of 2011 American College of Cardiology (ACC)/American Heart Association (AHA), 2014 ESC, 2020 AHA/ACC, and 2022 ESC models were .68, .64, .76 and .78, respectively. Furthermore, in patients without extensive LGE, LGE ≥5% was responsible for seven-fold SCD risk after multivariable adjustment. Whether in ICD-COR II or ICD-COR III, patients with LGE ≥5% and <15% showed significantly worse prognosis than those with LGE <5% (all P < .001). CONCLUSIONS: The 2022 ESC model performed better than the 2014 ESC model with especially improved sensitivity. LGE enabled further risk stratification based on current guidelines.

A Composite Particle Swarm Optimization Algorithm for Hospital Equipment Management Risk Control Optimization and Prediction.

Aiming at the problem that particles cannot realize multidimensional analysis and poor global search ability, a composite particle swarm optimization algorithm is proposed, improving the accuracy of particle swarm optimization. Firstly, k-clustering is used to cluster risk management particle swarm optimization. The advantages of particle swarm optimization have to be given full play, and the risk of hospital equipment management from various aspects has to be controlled. Then, the multidimensional particle swarm is segmented to obtain an ordered multidimensional risk particle swarm set, which provides a basis for later risk prediction. Finally, through the fusion function of multidimensional risk particle swarm, the risk particle swarm set based on the clustering degree is constructed, and the optimal extreme value is obtained, so as to improve the accuracy of management risk calculation results. Through MATLAB simulation analysis, it can be seen that the composite particle swarm optimization algorithm is better than particle swarm optimization algorithm in global search accuracy and search time. Moreover, the calculation time and accuracy are better. Therefore, the composite particle swarm optimization algorithm can be used to analyze the risk of hospital equipment and effectively control the risk of hospital equipment management.

Positional Distributions of the Tethered Modules in Nitric Oxide Synthase: Monte Carlo Calculations and Pulsed EPR Measurements.

The nitric oxide synthase (NOS) enzyme consists of multiple domains connected by flexible random coil tethers. In a catalytic cycle, the NOS domains move within the limits determined by the length and flexibility of the interdomain tethers and form docking complexes with each other. This process represents a key component of the electron transport from the flavin adenine dinucleotide/reduced nicotinamide adenine dinucleotide phosphate binding domain to the catalytic heme centers located in the oxygenase domain. Studying the conformational behavior of NOS is therefore imperative for a full understanding of the overall catalytic mechanism. In this work, we have investigated the equilibrium positional distributions of the NOS domains and the bound calmodulin (CaM) by using Monte Carlo calculations of the NOS conformations. As a main experimental reference, we have used the magnetic dipole interaction between a bifunctional spin label attached to T34C/S38C mutant CaM and the NOS heme centers, which was measured by pulsed electron paramagnetic resonance. In general, the calculations of the conformational distributions allow one to determine the range and statistics of positions occupied by the tethered protein domains, assess the crowding effect of the multiple domains on each other, evaluate the accessibility of various potential domain docking sites, and estimate the interaction energies required to achieve target populations of the docked states. In the particular application described here, we have established the specific mechanisms by which the bound CaM facilitates the flavin mononucleotide (FMN)/heme interdomain docking in NOS. We have also shown that the intersubunit FMN/heme domain docking and electron transfer in the homodimeric NOS protein are dictated by the existing structural makeup of the protein. Finally, from comparison of the calculated and experimental docking probabilities, the characteristic stabilization energies for the CaM/heme domain and the FMN domain/heme domain docking complexes have been estimated as -4.5kT and -10.5kT, respectively.