Acute Coronary Syndrome

Detection of Antithrombotic-Related Bleeding in Older Inpatients: Multicenter Retrospective Study Using Structured and Unstructured Electronic Health Record Data.

BACKGROUND: Bleeding complications are a major contributor to adverse drug events among older inpatients, particularly in those treated with antithrombotic agents. Timely and accurate detection of bleeding events is essential for improving drug safety surveillance and clinical risk management. OBJECTIVE: The study aimed to develop and validate automated algorithms for detecting major bleeding (MB)...

Mechanisms, precision therapies, and technological frontiers in coronary atherosclerosis: a comprehensive review.

Coronary atherosclerosis is a leading cause of morbidity and mortality worldwide and is characterized by complex molecular and cellular mechanisms involving lipid dysregulation, endothelial dysfunction, immune-inflammatory processes, and vascular remodeling. Despite advancements in conventional therapies, including statins and antiplatelet agents, significant residual risk persists, particularly i...

Derivation and validation of a clinical prediction score for ICU utilization at trauma intake.

BACKGROUND: Delayed admission to the intensive care unit (ICU) after trauma can lead to tripling of in-hospital mortality. Accurate ICU resource predi...

Lung scintigraphy for the diagnosis of acute pulmonary embolism.

Pulmonary embolism (PE) remains a major diagnostic challenge due to its potentially life-threatening nature and the clinical burden associated with an...

Integrated multi-omics and machine learning identify an interaction between SLC39A11 and phosphoinositide metabolism in deep vein thrombosis.

OCT-Derived Virtual Fractional Flow Reserve Associated With 1-Year Outcomes After PCI in ACS Patients.

BACKGROUND: Despite PCI, many acute coronary syndrome (ACS) patients experience major adverse cardiovascular events (MACE). Angiography is limited, an...

Association of depressive symptoms with systemic immune-inflammation index and platelet parameters among survivors of myocardial infarction: a cross-sectional NHANES study enhanced by machine learning and SHAP analysis.

BACKGROUND: Inflammation is implicated in the elevated risk of depressive disorder following myocardial infarction (MI), with platelets serving as a k...

Association between retinal AV ratio and coronary artery disease severity in acute coronary syndrome and chronic coronary syndrome Patients: A prospective study.

BACKGROUND: Early, non-invasive detection of coronary artery disease (CAD) is a significant challenge. Given the anatomical and pathophysiological par...

Dynamic Ensemble Selection for Early Detection of Deep Vein Thrombosis in Fracture Patients.

Deep vein thrombosis (DVT) in fracture patients is often clinically silent, with a high incidence of thrombosis and associated mortality. Static machi...

[Artificial intelligence in risk stratification of acute coronary syndrome : Future vision or already reality?].

Artificial intelligence (AI) in cardiology has evolved from rule-based expert systems to data-driven, learning models that can support diagnostic and ...

Initial diagnosis and management of acute ischemic stroke: recent update and future direction.

Acute ischemic stroke (AIS) outcomes depend critically on rapid, accurate early diagnosis in the emergency department. Traditional prehospital tools a...

Predicting Occlusion Myocardial Infarctions in the Emergency Department Using Artificial Intelligence.

OBJECTIVES: The objective was to develop an artificial intelligence (AI) model for predicting acute coronary occlusion myocardial infarction (OMI) in ...

Large language models for predicting one-year major adverse cardiovascular events in acute coronary syndrome.

Effective risk stratification is crucial for managing acute coronary syndrome (ACS). This study evaluated whether general-purpose large language model...

Physical exercise protects cardiovascular fitness in long-term spaceflight: what have we learned?

As space exploration advances into the era of deep space exploration, humanity faces unprecedented challenges in maintaining astronaut health, not onl...

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...

Advances in occult cancer screening for patients with unprovoked venous thromboembolism: A narrative review of epidemiology, risk, and clinical strategies.

BACKGROUND: Venous thromboembolism (VTE) and cancer exhibit a bidirectional correlation. The probability of detecting occult cancer in unprovoked VTE ...

Predicting postoperative length of stay: a feature selection approach to predictive modeling in lumbar fusion surgery.

BACKGROUND: Predictive modeling has the potential to improve preoperative planning and resource allocation in lumbar fusion surgery. This study aimed ...

Artificial Intelligence in detection of acute coronary occlusion in NSTEMI patients.

The prognosis of patients with MI has improved significantly with the recognition that early reperfusion is critical, particularly since timely percut...

Establishment and validation of an electrocardiogram vector-based machine learning model for the conversion of prone position electrocardiograms into standard electrocardiograms.

AIMS: The prone electrocardiogram (ECG) presents challenges in detecting anterior ST-segment elevated myocardial infarction (STEMI). This study aims t...

Artificial intelligence and machine learning in thrombosis and hemostasis: a scoping review of clinical and laboratory applications, challenges, and future directions.

This scoping review followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guideli...