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  1. Rehman A, Hassan MF, Yew KH, Paputungan I, Tran DC
    PeerJ Comput Sci, 2020;6:e334.
    PMID: 33816982 DOI: 10.7717/peerj-cs.334
    In the near future, the Internet of Vehicles (IoV) is foreseen to become an inviolable part of smart cities. The integration of vehicular ad hoc networks (VANETs) into the IoV is being driven by the advent of the Internet of Things (IoT) and high-speed communication. However, both the technological and non-technical elements of IoV need to be standardized prior to deployment on the road. This study focuses on trust management (TM) in the IoV/VANETs/ITS (intelligent transport system). Trust has always been important in vehicular networks to ensure safety. A variety of techniques for TM and evaluation have been proposed over the years, yet few comprehensive studies that lay the foundation for the development of a "standard" for TM in IoV have been reported. The motivation behind this study is to examine all the TM models available for vehicular networks to bring together all the techniques from previous studies in this review. The study was carried out using a systematic method in which 31 papers out of 256 research publications were screened. An in-depth analysis of all the TM models was conducted and the strengths and weaknesses of each are highlighted. Considering that solutions based on AI are necessary to meet the requirements of a smart city, our second objective is to analyze the implications of incorporating an AI method based on "context awareness" in a vehicular network. It is evident from mobile ad hoc networks (MANETs) that there is potential for context awareness in ad hoc networks. The findings are expected to contribute significantly to the future formulation of IoVITS standards. In addition, gray areas and open questions for new research dimensions are highlighted.
  2. Bautista JAL, Lin CY, Lu CT, Lo LW, Lin YJ, Chang SL, et al.
    Front Cardiovasc Med, 2023;10:1265890.
    PMID: 37953760 DOI: 10.3389/fcvm.2023.1265890
    BACKGROUND: Atrial fibrillation (AF) and mitral regurgitation (MR) have a complex interplay. Catheter ablation (CA) of AF may be a potential method to improve the severity of MR in AF patients.

    METHODS: Patients with symptomatic AF and moderate to severe MR who underwent catheter ablation from 2011 to 2021 were retrospectively included in the study. Patients' baseline characteristics and electrophysiological features were examined. These patients were classified as group 1 with improved MR and group 2 with refractory MR after CA.

    RESULTS: Fifty patients (age 60.2 ± 11.6 years, 29 males) were included in the study (32 in group 1 and 18 in group 2). Group 1 patients had a lower CHA2DS2-VASc score (1.7 ± 1.5 vs. 2.7 ± 1.5, P = 0.005) and had a lower incidence of hypertension (28.1% vs. 66.7%, P = 0.007) and diabetes mellitus (3.1% vs. 22.2%, P = 0.031) as compared to group 2 patients. Electroanatomic three-dimensional (3D) mapping showed that group 1 patients demonstrated less scars on the posterior bottom of the left atrium compared to group 2 patients (12.5% vs. 66.7%, P 

  3. Bautista JAL, Liu CM, Ibrahim AE, Lo LW, Chung FP, Hu YF, et al.
    Heart Rhythm, 2025 Jan;22(1):49-56.
    PMID: 38997056 DOI: 10.1016/j.hrthm.2024.06.062
    BACKGROUND: Prior studies have investigated cardiac anatomy and clinical parameters as predictors for pulmonary vein and non-pulmonary vein triggers.

    OBJECTIVE: We aimed to assess the link between the descending aorta to left inferior pulmonary vein (Dao-LIPV) distance and the occurrence of triggers and drivers in atrial fibrillation (AF) ablation procedures.

    METHODS: Drug-refractory AF patients who underwent first-time index catheter ablation from January 2010 to December 2019 were retrospectively assembled. The Dao-LIPV distance was measured from preablation pulmonary vein computed tomography. Patients were assigned to groups on the basis of the presence of LIPV triggers or drivers. Multivariate logistic regression was used to identify risk factors.

    RESULTS: A total of 886 consecutive patients with drug-refractory AF were studied, and 63 (7.1%) patients were identified to have LIPV triggers or drivers. The Dao-LIPV distance had a better predictive performance (area under the curve, 0.70) compared with persistent AF (area under the curve, 0.57). Multivariate logistic regression analysis showed that Dao-LIPV distance ≤2.5 mm (odds ratio, 3.96; 95% CI, 2.15-7.29; P < .001) and persistent AF (odds ratio, 1.73; 95% CI, 1.02-2.94]; P = .044) were independent predictors for the presence of LIPV triggers or drivers. A risk score model was established to predict the probability of LIPV triggers or drivers with persistent AF (10.2%), Dao-LIPV distance ≤2.5 mm (11.4%), and both (15.0%).

    CONCLUSION: The proximity of the Dao-LIPV was correlated to the presence of LIPV triggers or drivers. We developed a risk score model indicating that persistent AF and Dao-LIPV distances ≤2.5 mm significantly increase the risk of LIPV triggers or drivers, aiding electrophysiologists in preparing for and performing catheter ablation more effectively.

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