The relationship of systemic and pulmonary arterial parameters with HFpEF scores (H2 FPEF, HFA-PEFF) and diastolic dysfunction parameters in heart failure patients with preserved ejection fraction.

OBJECTIVE: We aimed to show the relationship between pulmonary pulse wave transit time (pPTT), pulmonary artery stiffness (PAS), and aortic stiffness parameters measured by non-invasive methods, HFpEF patients, and HFpEF scores (H2 FPEF, HFA-PEFF). METHOD: A total of 101 patients were included in our study, 52 of whom were HFpEF patients and 49 were control groups without heart failure. Echocardiographic parameters for PAS and pPTT were calculated, along with diastolic parameters that support the diagnosis of HFpEF. Aortic stiffness was assessed using a PWA monitor. Demographic features, laboratory findings, aortic stiffness parameters, and echocardiographic findings including pulmonary artery parameters were compared with the control group. RESULTS: PAS, pPTT, PWV were significantly higher in the HFpEF group than in the control group (p < 0.001). PAS and pPTT correlated positively with HFpEF scores. In linear regression analysis for PAS, a directly positive correlation was found between E/e' and PAS, independent of aortic stiffness. CONCLUSION: These parameters can be used as a predictive value in the diagnosis process of patients with suspected HFpEF. A significant relationship between PAS and ventricular stiffness (E/e') was shown independently of aortic stiffness.

Evaluation of the prediagnosis and management of ChatGPT-4.0 in clinical cases in cardiology.

Aim: Evaluation of the performance of ChatGPT-4.0 in providing prediagnosis and treatment plans for cardiac clinical cases by expert cardiologists. Methods: 20 cardiology clinical cases developed by experienced cardiologists were divided into two groups according to preparation methods. Cases were reviewed and analyzed by the ChatGPT-4.0 program, and analyses of ChatGPT were then sent to cardiologists. Eighteen expert cardiologists evaluated the quality of ChatGPT-4.0 responses using Likert and Global quality scales. Results: Physicians rated case difficulty (median 2.00), revealing high ChatGPT-4.0 agreement to differential diagnoses (median 5.00). Management plans received a median score of 4, indicating good quality. Regardless of the difficulty of the cases, ChatGPT-4.0 showed similar performance in differential diagnosis (p: 0.256) and treatment plans (p: 0.951). Conclusion: ChatGPT-4.0 excels at delivering accurate management and demonstrates its potential as a valuable clinical decision support tool in cardiology.

Have you ever wondered if an artificial intelligence (AI) program could help doctors figure out what the problem is when someone has heart complaints? Our research examined this by testing an AI program called ChatGPT-4.0 on clinical cases. We wanted to see if it could help doctors by giving good advice on what might be wrong with patients who have heart issues and what should be done to help them. To test this, we used ChatGPT-4.0 to look at 20 different stories about patients with heart problems. These stories were made to cover a variety of common heart conditions faced by heart doctors. Then, we asked 18 heart doctors to check if the advice from ChatGPT-4.0 was good and made sense. What we found was quite interesting! Most of the time, the doctors agreed that the computer gave good advice on what might be wrong with the patients and how to help them. This means that this smart computer program could be a helpful tool for doctors, especially when they are trying to figure out tricky heart problems. But, it's important to say that computers like ChatGPT-4.0 are not ready to replace doctors. They are tools that can offer suggestions. Doctors still need to use their knowledge and experience to make the final call on what's best for their patients. In simple terms, our study shows that with more development and testing, AI like ChatGPT-4.0 could be a helpful assistant to doctors in treating heart disease, making sure patients get the best care possible.

Baseline Characteristics of a Patient Cohort and Predictors of In-hospital MORtality in CORonary Care Units (MORCOR-TURK) Trial in Türkiye.

OBJECTIVE: The MORtality in CORonary Care Units in Türkiye (MORCOR-TURK) trial is a national registry evaluating predictors and rates of in-hospital mortality in coronary care unit (CCU) patients in Türkiye. This report describes the baseline demographic characteristics of patients recruited for the MORCOR-TURK trial. METHODS: The study is a multicenter, cross-sectional, prospective national registry that included 50 centers capable of 24-hour CCU service, selected from all seven geographic regions of Türkiye. All consecutive patients admitted to CCUs with cardiovascular emergencies between September 1-30, 2022, were prospectively enrolled. Baseline demographic characteristics, admission diagnoses, laboratory data, and cardiovascular risk factors were recorded. RESULTS: A total of 3,157 patients with a mean age of 65 years (range: 56-73) and 2,087 (66.1%) males were included in the analysis. Patients with arterial hypertension [1,864 patients (59%)], diabetes mellitus (DM) [1,184 (37.5%)], hyperlipidemia [1,120 (35.5%)], and smoking [1,093 (34.6%)] were noted. Non-ST elevation myocardial infarction (NSTEMI) was the leading cause of admission [1,187 patients (37.6%)], followed by ST elevation myocardial infarction (STEMI) in 742 patients (23.5%). Other frequent diagnoses included decompensated heart failure (HF) [339 patients (10.7%)] and arrhythmia [272 patients (8.6%)], respectively. Atrial fibrillation (AF) was the most common pathological rhythm [442 patients (14%)], and chest pain was the most common primary complaint [2,173 patients (68.8%)]. CONCLUSION: The most common admission diagnosis was acute coronary syndrome (ACS), particularly NSTEMI. Hypertension and DM were found to be the two leading risk factors, and AF was the most commonly seen pathological rhythm in all hospitalized patients. These findings may be useful in understanding the characteristics of patients admitted to CCUs and thus in taking precautions to decrease CCU admissions.

Ranolazine improved left ventricular diastolic functions and ventricular repolarization indexes in patients with coronary slow flow.

Introduction: Coronary slow flow (CSF) is a condition commonly encountered during angiography. Recent studies have shown the adverse effects of CSF on left ventricular diastolic functions. CSF reportedly increases the novel ventricular repolarization parameters. Ranolazine is a preparation with a prominent anti-anginal activity that has positive effects on anti-arrhythmic and diastolic parameters. In this context, this study was carried out to investigate the effects of ranolazine on left ventricular diastolic functions and repolarization in patients with CSF. Material and methods: Forty-six patients with CSF and 29 control subjects were included in the patient and control groups, respectively. Both groups received ranolazine for one month and were evaluated using 12-lead electrocardiography, conventional echocardiography, and tissue Doppler imaging at the baseline and after one month of ranolazine treatment. Results: Corrected P, QT dispersion, and Tp-e interval values were significantly higher in the patient group than in the control group. There was a significant decrease in isovolumic relaxation time (IVRT) and deceleration time (DT) values after the ranolazine treatment compared to the baseline values in the patient group but not the control group. A significant increase was observed in the mean E and A velocities and the mean E/A ratio after the ranolazine treatment compared to the baseline values in the patient group. Additionally, there was a significant difference between the Tp-e interval and corrected P dispersion values measured after the ranolazine treatment compared to the baseline values in the patient group but not in the control group. Conclusion: This study's findings demonstrated that ranolazine positively affected impaired diastolic functions and repolarization parameters, particularly in patients with CSF.