Hypertension

Feasibility of Free-breathing Deep Learning-reconstructed Single-Shot Cine MRI in Participants with Arrhythmia: Comparison with Conventional Segmented Cine MRI.

Purpose To evaluate the feasibility of retrospective electrocardiographically (ECG) gated single-shot cine using deep learning-enhanced compressed sensing (AI-CS) versus conventional balanced steady-state free precession (bSSFP) cine, focusing on left ventricular (LV) structure and function. Materials and Methods Between September 1, 2023, and September 28, 2024, participants (including those with...

Pre-heart failure in early chronic kidney disease: clinical epidemiology and treatment.

Chronic kidney disease (CKD), defined per the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines by persistent (≥3 months) abnormalities of kidney structure or function, including reduced estimated glomerular filtration rate (eGFR) and/or albuminuria, affects 10%-15% of adults worldwide and is a powerful, independent risk factor for cardiovascular diseases, including heart failure (HF). ...

Predictive accuracy of a perioperative hemodynamic indices-based prediction model for moderate-to-severe acute kidney injury after orthotopic heart transplantation.

BACKGROUND: Acute kidney injury is a common complication after orthotopic heart transplantation. Previous models have failed to consider the impact of...

Personalized mapping of body homeostasis using whole-body PET connectomics and routine FDG PET imaging.

BACKGROUND: Immuno-inflammation and systemic alterations are key features of chronic diseases. While PET molecular imaging is widely used in precision...

A machine learning approach using echocardiographic and hematological parameters to classify cerebral small vessel disease burden.

BACKGROUND: Cerebral small vessel disease (CSVD) is a leading cause of stroke and dementia and is associated with cardiac and hematological biomarkers...

Effect of SnapShot Freeze 2 on Reducing Pulsation Artifacts in Coronary Artery Imaging of Patients With High Heart Rates.

BACKGROUND This study aimed to evaluate the effect of SnapShot Freeze 2 (SSF2) on reducing pulsation artifacts in coronary artery imaging of patients ...

Artificial Intelligence in Cardiovascular Medicine: Focus on Hypertension.

Hypertension remains the most prevalent modifiable risk factor for cardiovascular morbidity and mortality worldwide, yet rates of effective blood pres...

Machine-learning approach on echocardiography to improve the detection of transthyretin amyloid cardiomyopathy: GRAAL algorithm.

AIMS: Transthyretin amyloid cardiomyopathy (ATTR-CM) is an increasingly recognized cause of heart failure, yet detection remains challenging due to it...

Explainable machine learning for long-term cardiovascular disease risk prediction in Chinese middle-aged and older adults: a 9-year longitudinal cohort study with web-based risk calculator.

Cardiovascular disease represents the leading cause of mortality in China, accounting for over 40% of all deaths. Existing risk prediction models pred...

Metagenomic profiling and predictive modeling of the gut microbiome reveal signatures of gestational disease.

The gut microbiome plays a vital role in maternal health and pregnancy outcomes, yet its impact on conditions like gestational hypertension (GH) and g...

Enhancing few-shot personalized cuffless blood pressure estimation with self-supervised learning.

Objective.Individual differences across subjects reduce the accuracy of physiological signal-based cuffless blood pressure (BP) estimation. However, t...

Artificial Intelligence in Neurocritical Care : Multimodal Biosignal Analysis for Prognosis, Monitoring, and Future Pediatric Applications.

Neurocritical care relies on continuous assessment of neurological function and physiology under time pressure, yet bedside teams must interpret high-...

Epidemiology of Peripheral Artery Disease, Risk Factors, and Trends.

Peripheral artery disease (PAD) affects more than 230 million people worldwide, with a disproportionate burden in low- and middle-income countries. PA...

Machine learning model for predicting improvement in left ventricular systolic function in patients with heart failure and reduced ejection fraction.

BACKGROUND: About one-third of patients with heart failure (HF) with reduced ejection fraction (HFrEF) may demonstrate left ventricular ejection fract...

Cross-sectional evaluation of cardiovascular biological age using point-of-care ultrasound.

AIMS: Biological age is increasingly recognized as a superior predictor of morbidity, mortality, compared with chronological age. Artificial intellige...

Deep-Learning-Based Image Reconstruction to Improve End-Diastolic and Systolic Cardiac T1 Mapping.

PURPOSE: To develop an image reconstruction method that enables increased spatial resolution cardiac T1 mapping in both the end-diastolic and systolic...

Machine Learning-Based Risk Prediction for Coronary Heart Disease Complicated by Hyperhomocysteinemia: Retrospective Study.

BACKGROUND: Hyperhomocysteinemia (HHcy) is recognized as an independent risk factor for coronary heart disease (CHD), yet accurately predicting CHD ri...

The Burden, Outcomes, and Management of Patients with Aldosterone Dysregulation: A Targeted Literature Review.

INTRODUCTION: Aldosterone dysregulation (excess aldosterone production at the source within the adrenal glands) in the absence of primary aldosteronis...

Artificial Intelligence-Driven Electrocardiogram Screening for Asymptomatic Left Ventricular Systolic Dysfunction in the General Population.

BACKGROUND: Asymptomatic left ventricular systolic dysfunction (LVSD) is a well-established precursor of overt heart failure (HF), yet it often remain...

Artificial Intelligence and the Left Atrial Filling Index (Mitral E/LA Strain Ratio) as Novel Tools for the Evaluation of Left Ventricular Diastolic Dysfunction: An Editorial Commentary and Systematic Review.