Clinical Research Directory

Clinical Characteristics, Frailty, and Prognostic Predictors in Patients Aged 75 and Older With Acute Coronary Syndrome

This study will evaluate clinical characteristics, frailty, and predictors of prognosis in patients aged 75 years and older who are hospitalized with acute coronary syndrome (ACS). The research includes both a retrospective and a prospective cohort. The aim is to determine whether frailty scores, combined with clinical and laboratory parameters available at admission, can improve risk prediction for complications and mortality compared with standard risk scores (TIMI, GRACE, Syntax). The study will also compare outcomes between patients treated with percutaneous coronary intervention (PCI) and those treated conservatively with medications. Patients will be followed during hospitalization and for six months after discharge. The results are expected to contribute to more personalized treatment strategies for elderly patients with ACS.

LA Strain in Predicting Early Complication in STEMI After PPCI

The goal of this observational study To evaluate the predictive value of left atrial strain for in-hospital outcomes in patients with ST-segment elevation myocardial infarction undergoing PPCI. The main questions it aims to answer are: Is low parameters of left atrial strain associated early complication ? What is the correlation between LA strain parameters and conventional echocardiographic indices of left ventricular systolic and diastolic function ? Is there more affection to LA strain in certain territory over the others ? What is the correlation between LA strain and LA volume index across infarct territories ? Does LA strain Correlate with TAPSE and PASP to evaluate right-heart interactions ?

Development and Validation of a Cardiac Magnetic Resonance-Based Multimodal Deep Learning Model for Long-Term Outcome Prediction in ST-Segment Elevation Myocardial Infarction

Objective: This study aims to develop and test a novel artificial intelligence-based prediction model. This model will integrate cardiac magnetic resonance imaging and clinical data to predict the long-term risk of major adverse cardiovascular events in patients who have undergone emergency percutaneous coronary intervention for ST-segment elevation myocardial infarction. Description: This study plans to enroll patients with STEMI who have received primary PCI. Approximately one week after the procedure, patients will undergo a cardiac magnetic resonance scan. Concurrently, we will collect patients' basic information, blood test results during treatment, and procedural records. Thereafter, patients will be followed up regularly (every six months) to record the occurrence of any major adverse cardiac events, such as cardiovascular death, recurrent myocardial infarction, hospitalization for heart failure, or unplanned repeat revascularization.All collected data, including clinical data and analyzed cardiac MR images, will be used to construct a multimodal deep learning model. The model will learn to identify features associated with future cardiac problems. The accuracy of the model will be tested and validated in different patient groups. Potential Impact: If successful, this prediction tool could assist physicians in identifying high-risk patients earlier and more accurately, enabling closer monitoring and more timely interventions, ultimately improving the long-term prognosis for these patients.

Bempedoic Acid in PPCI Impact on Clinical Outcome and Inflammatory Markers

Bempedoic acid in PPCI

High-Dose Rosuvastatin Preloading for Enhanced Outcomes in STEMI Patients Undergoing Primary PCI

To compare the efficacy of high dose rosuvastatin preloading vs placebo before primary PCI in terms of MACE at 30 days