Clinical Research Directory

CTEPH Differential Diagnosis Assisted by Enhanced Large Language Model Support

This randomized controlled trial aims to evaluate whether a locked large language model (LLM)-based clinical decision support system improves the differential diagnosis of pulmonary artery filling defects among physicians who do not specialize in pulmonary vascular diseases. Participants will evaluate 30 de-identified clinical cases involving chronic thromboembolic pulmonary hypertension (CTEPH), acute pulmonary embolism (PE), and pulmonary artery sarcoma (PAS), with or without LLM assistance. The primary outcome is sensitivity for identifying CTEPH, while secondary outcomes include overall diagnostic accuracy, time to diagnosis, appropriateness of referral recommendations, and AI-related diagnostic errors.

Evaluating the Efficacy, Safety and Long Term Functional Outcomes of Percutaneous Mechanical Aspiration Thrombectomy for Treatment of Acute Pulmonary Embolism Using the AlphaVac Multipurpose Mechanical Aspiration (MMA) F1885 System

To evaluate the efficacy, safety, and long-term functional outcomes of percutaneous mechanical aspiration thrombectomy using the AlphaVac Multipurpose Mechanical Aspiration (MMA) F1885 System for the treatment of acute pulmonary embolism.

Assessment of Right Ventricular Function After Acute Pulmonary Embolism: a Comparison of Speckle Tracking Strain and Conventional Echocardiographic Parameters

Echocardiographic Assessment: Performed within 24h of PE diagnosis Conventional parameters: TAPSE, RV FAC, RV/LV ratio, tricuspid S', PASP STE parameters: RV free wall longitudinal strain (RVFWS), global longitudinal strain (GLS) if feasible All measurements averaged over 3 cardiac cycles (sinus) or 5 (AF) Follow-up data: ICU/hospital LOS Need for vasopressors/mechanical ventilation In-hospital and 30-day mortality

The Prognostic Value of Anion Gap in Predicting Mortality Among Patients With Acute Pulmonary Embolism

This study aims to evaluate the prognostic value of the anion gap in predicting mortality among patients with acute pulmonary embolism. Researchers will collect information based on hospital registry as secondary data of in patient who had diagnosed as acute pulmonary embolism by using computed tomography scan (CT scan). The data consist of demographic data, clinical presentation, laboratory, and CT scan were collected from hospital registry by reviewing medical record. Then, the data was analyzed by using IBM SPSS Statistics v26.