Hypertension

AI-assisted multimodal assessment for right ventricular function from echocardiography predicts mortality in patients with pulmonary hypertension and right heart failure.

Right ventricular (RV) strain is an important factor in evaluating RV function. This study aimed to predict mortality in patients with pulmonary hypertension (PH) and right heart failure (RHF) using an artificial intelligence (AI)-assisted multimodal echocardiography approach. A total of 586 patients with PH and RHF were enrolled. Transthoracic echocardiography (TTE) was performed either before ho...

A Deep Learning Model for Dynamic Prediction of Acute Kidney Injury in Heart Failure Patientss.

BACKGROUND: This study aimed to develop and validate a dynamic prediction model for acute kidney injury (AKI) in heart failure (HF) patients. METHODS: Using data from 7,636 HF patients in the MIMIC-IV v3.1 database, we constructed a Long Short-Term Memory (LSTM) model with dynamic focal loss to handle class imbalance. The study designed two prediction perspectives: short-term prediction utilized d...

Machine Learning Insights into Age-Related Sex Differences in Blood Pressure: Influence of Diabetes and Body Mass Index.

INTRODUCTION: The age-related dynamics of blood pressure (BP) arise from complex, often concurrent interactions among multiple factors (e.g., sex, typ...

Old Criteria, New Intelligence: The Evolution of ECG in Pulmonary Hypertension Diagnosis.

BACKGROUND: Pulmonary hypertension (PH) carries a significant mortality risk, highlighting the need for improved early detection strategies. This revi...

Machine Learning-Based Clusters of Vital Signs and Lactate Levels Predict Vasopressor Use in Sepsis.

OBJECTIVE: Sepsis remains a major clinical challenge because of its complex, heterogeneous, and multidimensional clustering patterns. This study aimed...

A clinical dataset on type-2 diabetes including demographic, anthropometric, and biochemical parameters from Bangladesh.

Type-2 diabetes is a major public health concern in Bangladesh, and this dataset provides 1065 curated patient records with demographic, anthropometri...

Preliminary insights into artificial intelligence guided dosing in hypertension and diabetes: challenges and lessons learnt in a pilot feasibility study.

OBJECTIVE: CURATE.AI is an artificial intelligence platform enabling personalised drug dosing. Aims:1) Determine the feasibility of using CURATE.AI in...

Impact of continuing renin-angiotensin-aldosterone system inhibitors before surgery on intraoperative hypotensive events: a secondary analysis of the STOP-or-NOT Trial.

BACKGROUND: The multicentre STOP-or-NOT trial has shown that continuation of renin-angiotensin-aldosterone inhibitors (RAASis) before major noncardiac...

HeartUnloadNet: A cycle-consistent graph network with reduced supervision for predicting unloaded cardiac geometry from diastolic states.

BACKGROUND AND OBJECTIVE: The unloaded cardiac geometry, representing the zero-stress and zero-strain reference state of the heart, is fundamental for...

The role of artificial intelligence in hypertension management.

PURPOSE OF REVIEW: Hypertension remains a leading modifiable risk factor for cardiovascular and renal conditions and dementia. Given its rising global...

Design and rationale of the WARRIOR ancillary study for coronary CT angiographic analysis.

BACKGROUND: Over 50% of women evaluated for suspected ischemia have no obstructive coronary artery disease (INOCA). Statins, angiotensin converting en...

UDV-Net: A hybrid CNN and transformer vein segmentation network with vascular prior and spatial awareness.

CNNs handling multi-scale variations and Transformers modeling long-range dependencies are crucial for vascular segmentation. The fusion of these two ...

Integrating AI-ECG and point-of-care cardiac ultrasound for screening structural heart disease: A proof-of-concept study.

BACKGROUND: Early structural heart disease (SHD) detection is crucial for improving prognostic outcomes, but widely accessible screening methods are l...

Performance of an automated Korotkoff sound BP monitor in cardiovascular patients.

OBJECTIVES: Accurate blood pressure measurement is essential for cardiovascular risk management, but conventional oscillometric devices are unreliable...

Factors Impacting the Performance of Deep Learning Detection of Pulmonary Emboli.

OBJECTIVE: AI models are increasingly adopted in clinical practice, yet their generalizability outside controlled validation settings remains unclear....

Utilizing machine learning in echocardiographic analysis to distinguish obstructive and non-obstructive coronary artery disease.

BACKGROUND: Research on echocardiographic prognostication in non-obstructive coronary artery disease (CAD) is limited, mainly accompanied by different...

Development and validation of a machine learning model to predict functional outcomes in patients with recent small subcortical infarction.

OBJECTIVE: A substantial proportion of patients (12 %-25 %) with recent small subcortical infarction (RSSI) suffer poor functional outcomes at 3 month...

Clinical decision support system for detecting right ventricular dysfunction in acute pulmonary embolism: Explainable a new Binary Rule Search (BRS) ensembles and robustness evaluation.

BACKGROUND: Right-ventricular dysfunction (RVD) in acute pulmonary embolism (PE) carries excess short-term mortality; fast, transparent risk stratific...

Exploring Patients' Profiles Associated With the Resolution of Acute Calcium Pyrophosphate Arthritis Treated With Colchicine and Prednisone: Post Hoc Analysis of a Randomized Controlled Trial.

OBJECTIVE: The objective was to identify factors determining acute arthritis resolution and safety with colchicine and prednisone in acute calcium pyr...

Progress in constitutive modeling of arterial wall tissue mechanics: from theoretical frameworks to clinical application.

Cardiovascular disease (CVD) is a leading cause of mortality worldwide, and the mechanical behavior of arterial wall tissue (AWT) is central to its in...