Congestive Heart Failure

Evaluation of new vectorcardiography algorithms for identifying left ventricular hypertrophy and impaired systolic function.

BACKGROUND: Timely diagnosis of impaired systolic function and left ventricular hypertrophy (LVH) remains a clinical challenge. Routine electrocardiography provides limited diagnostic accuracy for detecting early or subtle structural abnormalities. Vectorcardiography (VCG), which captures the spatial and temporal characteristics of cardiac electrical activation and repolarization, may offer a rapi...

OCT biomarkers in patients with diabetic macular edema treated with dexamethasone implant.

Beyond conventional OCT-based morphological classifications of diabetic macular edema (DME), an expanding range of OCT-derived biomarkers has been identified that reflect distinct pathophysiological mechanisms and may carry diagnostic, prognostic, and therapeutic relevance. This review summarizes current evidence on potential OCT biomarkers in DME, with a particular focus on their role in patients...

Extraction of Acoustic Features via Empirical Wavelet Transform to Determine Stenosis Degree of the Left Anterior Descending Artery Based on the Diastolic Heart Sounds of 75 Participants.

OBJECTIVES: This study aimed to develop a method for extracting acoustic features to assess left anterior descending artery (LAD) stenosis severity. M...

Lp(a), Artificial Intelligence, Hypertrophic Cardiomyopathy….

Exploring the mechanisms and management of sepsis-related cardiac dysfunction.

Sepsis-related cardiac dysfunction (SRCD) represents a critical determinant of both acute mortality and long-term cardiovascular morbidity in sepsis s...

The evolving role of artificial intelligence in optimizing treatment and patient selection in diabetic macular edema.

Anti-vascular endothelial growth factor (anti-VEGF) therapy is the mainstay of management for diabetic macular edema (DME), but marked variability in ...

Early emergency department decision support for heart failure hospitalization using triage-level unstructured and structured data: a retrospective cohort study.

BACKGROUND: Early identification of patients at risk for heart failure (HF) hospitalization in the emergency department (ED) is challenging because de...

Artificial Intelligence-Based Analysis of Right Ventricular Work Is Associated with Outcomes after Transcatheter Tricuspid Valve Intervention.

AIMS: In tricuspid regurgitation (TR), conventional parameters of right ventricular (RV) function have limited prognostic utility. Our aim was to eval...

Artificial Intelligence-Enabled ECG for Elevated E/e' on Echocardiography: Hemodynamic Relevance and Prognostic Value.

BACKGROUND: Left ventricular filling pressure is associated with heart failure symptoms and a key prognostic marker and therapeutic target, but a scal...

MIMIC-III-Ext-PPG, a PPG-based Benchmark Dataset for Cardiovascular and Respiratory Signal Analysis.

We present MIMIC-III-Ext-PPG, a large-scale, quality-assessed photoplethysmography (PPG) dataset derived from the matched waveform subset of MIMIC-III...

External validation of ECG artificial intelligence for emergency and cardiac assessment across a large-scale U.S. healthcare system.

An ECG-based artificial intelligence (AI) model was previously developed to generate ten digital biomarkers for emergency and cardiac assessment and i...

Predicting Acute Myocardial Infarction in the Absence of Detectable Atherosclerotic Plaque With Perivascular Coronary Inflammation.

BACKGROUND: Coronary computed tomography angiography (CTA) with analysis by artificial intelligence (AI) can personalize coronary artery disease risk ...

Systems Biology Identifies TARS2 as a Cardiomyocyte Regulator of Mitochondrial Oxidative Stress in Dilated Cardiomyopathy.

Dilated cardiomyopathy (DCM), a leading cause of heart failure, is characterized by progressive cardiomyocyte (CM) loss and mitochondrial dysfunction;...

Artificial intelligence for detecting acute heart failure on chest CT: prospective clinical proof-of-concept validation.

OBJECTIVE: Acute heart failure (AHF) is a common but underrecognized cause of dyspnea. Chest computed tomography (CT) can accurately assess pulmonary ...

Lactate-albumin ratio predicts in-hospital mortality in critically Ill patients with congestive heart failure and diabetes.

OBJECTIVE: To evaluate the predictive utility of the initial lactate-to-albumin ratio (LAR) measured within 24 h of admission for in-hospital all-caus...

Deep Learning Model Using Transfer Learning for Detecting Left Ventricular Systolic Dysfunction: Retrospective Algorithm Development and Validation Study.

BACKGROUND: Artificial intelligence-augmented electrocardiogram (AI-ECG) models for detecting left ventricular systolic dysfunction (LVSD) often exhib...

Transferability of a US claims-based machine learning model for ATTRwt-CM identification: a retrospective evaluation in a German setting.

Cardiac amyloidosis (CA), a fatal and progressive cardiomyopathy is characterized by amyloid deposition within the myocardium. The main forms of CA in...

An interpretable machine learning model for predicting stroke in patients with hypertension: insights from the SPRINT.

Stroke is a leading cause of mortality worldwide, with hypertension being its most significant risk factor. However, few studies have specifically dev...

Adapting the REVEAL Lite 2 score to the pediatric population through machine learning: insights from the REHIPED registry for pediatric pulmonary hypertension.

INTRODUCTION AND OBJECTIVES: Risk scores for pulmonary hypertension (PH) have been proven useful in adults. However, no risk score has been validated ...

Large Language Models for Cardiac MRI Diagnosis Based on Standardized Text Descriptions.

BACKGROUND: MRI is important for cardiac disease evaluation, but accurate diagnosis remains challenging in less experienced centers. Although large la...