Hypertension

Predicting atrial fibrillation recurrence after radiofrequency ablation using the AIFV system: a prospective observational study.

BACKGROUND: Pulmonary vein isolation (PVI) has become the cornerstone of atrial fibrillation (AF) treatment. Nevertheless, the efficacy of radiofrequency ablation remains limited by a substantial rate of recurrence. The selection of anesthesia, the surgeon's operative experience and medical expertise, as well as the ablation surgery strategy, all have an impact on the recurrence after atrial fibri...

Intracranial compliance monitoring using pulse shape index in traumatic brain injury: relation to cerebral physiology and clinical outcome.

BACKGROUND: The intracranial pressure (ICP) pulse waveform reflects intracranial compliance. The pulse shape index (PSI), an artificial intelligence (AI)-based metric ranging from 1 (normal) to 4 (disturbed), quantifies morphological waveform pathologies. Early findings in smaller cohorts indicate that elevated PSI is associated with mass lesions, aging, higher ICP, and worse outcome. This study e...

SPISE index and ensemble machine learning refine cardiovascular risk stratification in stage 0-3 CKM syndrome.

BACKGROUND: While the single-point insulin sensitivity estimator (SPISE) shows promise as an insulin resistance biomarker, its association with cardio...

Deep learning prediction of nocturnal hypertension for patients intolerant to ambulatory blood pressure monitoring.

BACKGROUND: Ambulatory blood pressure monitoring (ABPM) plays an irreplaceable role in the diagnosis and management of hypertension. However, more tha...

Development and external validation of an interpretable machine-learning model for HFpEF comorbidity risk in COPD patients.

BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) and Heart Failure with preserved Ejection Fraction (HFpEF) frequently coexist, leading to inc...

Validation of a machine learning model for predicting early deterioration in the emergency department.

Early recognition of patients at risk for deterioration in the emergency department (ED) is critical for patient safety. Traditional early warning sco...

Plasma proteomic profiles reveal proteins and characteristic patterns associated with hypertension: A prospective cohort study.

BACKGROUND: Longitudinal proteomic studies on hypertension remain scarce. We evaluated the epidemiological associations of circulating proteins with h...

Advancements and challenges in blood pressure monitoring using pulse wave propagation: a comprehensive review and ISO 81060-2 based statistical analysis.

Cardiovascular diseases, particularly hypertension, remain a major global health burden, highlighting the need for accurate and accessible blood press...

Early prediction of in-hospital mortality in ICU patients with heart failure using an interpretable machine learning model: a retrospective study based on MIMIC-IV.

BACKGROUND: Heart failure (HF) remains a major cause of morbidity and mortality worldwide, and acute decompensation frequently necessitates intensive ...

Hybrid model based on fuzzy logic and classification trees for the prediction of mortality of critical trauma patients: Pre-hospital variables from the RETRAUCI registry.

BACKGROUND: In critically injured trauma patients, tools that stratify injury severity and estimate mortality are essential. Fuzzy logic (FL) enables ...

Artificial Intelligence Electrocardiogram and Left Ventricular Systolic Dysfunction in Kenya.

IMPORTANCE: Early detection of risk of heart failure with reduced ejection fraction remains challenging in resource-limited settings due to limited ac...

Use of Machine-Learning Models to Identify Clinical Features Associated With A Future Clinical Worsening Event in Patients With Pulmonary Arterial Hypertension.

Clinical worsening events are increasingly recognized as a meaningful outcome in pulmonary arterial hypertension (PAH). We applied machine-learning mo...

Diuretic Ultrasound Evaluation of Surgical Necessity in Pediatric Ureteropelvic Junction Obstruction.

RATIONALE AND OBJECTIVES: This study aimed to develop an interpretable machine learning (ML) model using diuretic ultrasonography to predict the neces...

Prognostic significance of right ventricular myocardial features derived from echocardiography using a deep learning framework in pulmonary arterial hypertension.

BACKGROUND: The function and myocardial characteristics of the right ventricle (RV) are linked to RV dysfunction and prognosis in pulmonary arterial h...

Artificial intelligence-assisted peri-operative echocardiography: a multicentre observational study.

INTRODUCTION: Point-of-care transthoracic echocardiography performed by anaesthetists can influence peri-operative management but is constrained by ti...

Neutrophil extracellular traps-related biomarkers in idiopathic pulmonary arterial hypertension: A machine learning-based identification and experimental validation study.

Neutrophil extracellular traps (NETs) are increasingly recognized as critical mediators in vascular inflammation and remodeling, yet their molecular m...

Prognostic Modeling Based on Post-Endovascular Thrombectomy Systolic Blood Pressure Trajectories Using Explainable Artificial Intelligence: A Secondary Analysis of the OPTIMAL-BP Trial.

Blood pressure (BP) management following successful reperfusion after endovascular thrombectomy (EVT) is critical in achieving favorable clinical outc...

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 electrocardiog...

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...

IN-HUMAN FEASIBILITY AND SAFETY OF SUBRETINAL DRUG INJECTION THROUGH ATTACHED RETINA USING A ROBOTIC COMANIPULATION SYSTEM.

PURPOSE: To evaluate feasibility and safety of robot-assisted subretinal injections through attached retina using the comanipulated Mynutia system in ...