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Importance: Cardiovascular health outcomes associated with noncigarette tobacco products (cigar, pipe, and smokeless tobacco) remain unclear, yet such data are required for evidence-based regulation.

Objective: To investigate the association of noncigarette tobacco products with cardiovascular health outcomes.

Design, Setting, And Participants: This cohort study was conducted within the Cross Cohort Collaboration Tobacco Working Group by harmonizing tobacco-related data and conducting a pooled analysis from 15 US-based prospective cohorts with data on the use of at least 1 noncigarette tobacco product ranging between 1948 and 2015.

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To investigate if progression of coronary artery calcification (CAC) in patients with systemic lupus erythematosus (SLE) is associated with renal and traditional cardiovascular risk factors as well as incidence of myocardial infarctions. CAC progression was evaluated by cardiac computed tomography (CT) at baseline and after 5 years. Multivariable Poisson regression was applied to investigate associations between CAC progression and baseline values for traditional cardiovascular risk factors, CAC, SLE disease duration, lupus nephritis, and renal function.

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Background: Patients on long-term dialysis for end-stage kidney disease have a high mortality rate, predominantly due to sudden cardiac death (SCD), which is associated with an increased risk of arrhythmias compared to the general population. Thus, the current systematic review and meta-analysis aimed to investigate the incidence of SCD among dialysis patients at risk of arrhythmia.

Methods: This systematic review and meta-analysis followed the PRISMA guidelines.

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Purpose: This study aimed to investigate the alterations in sleep quality and sleep patterns among military personnel at altitudes ranging from 1500 to 4500 m, as well as the associated factors influencing their sleep.

Methods: This study employed a longitudinal prospective survey conducted over a period of six months, from November 2023 to June 2024. A total of 90 soldiers were recruited for participation.

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Background And Aims: Current heart failure (HF) risk stratification strategies require comprehensive clinical evaluation. In this study, artificial intelligence (AI) applied to electrocardiogram (ECG) images was examined as a strategy to predict HF risk.

Methods: Across multinational cohorts in the Yale New Haven Health System (YNHHS), UK Biobank (UKB), and Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), individuals without baseline HF were followed for the first HF hospitalization.

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