Eltrombopag is a non-peptide thrombopoietin receptor agonist. Eltrombopag has originally been developed for conditions where therapy for thrombocytopenia is needed. Secondary to eltrombopag have been reported thrombotic events, chest pain, acute renal failure, neutropenia, ascites, retinal exudates, antiphospholipid syndrome. In this case, we present a 53 year-old patient who had diagnosis of Idiopathic Thrombocytopenic Purpura (ITP) for 30 years with splenectomy. He's still having low thrombocyte counts despite the classical ITP therapy. He was treated with eltrombopag for the last 2 months and had inferior myocardial infarction despite that having no additional risk factors for coronary heart disease.

Objective: The aim of our study is to investigate the relationship between microalbuminuria and flow-mediated dilatation in familial Mediterranean fever (FMF) patients. Material and Methods: In our study, there were two groups consisting of 54 patients who were out of the attack period (43 of whom had no microalbuminuria and 11 of whom had microalbuminuria) and 40 healthy controls (M/F: 12/28). Results: There was no statistically difference between patient and control groups’age (25.06±8.07, 22.89±6.00 years, respectively). Flow-mediated dilatation (FMD) percentages were significantly different between the three groups (p=0.01). It was observed that there was a correlation between microalbuminuria and FMD percentage. Conclusion: Endothelial dysfunction and renal damage occurred as a result of low-grade chronic inflammation. Microalbuminuria, which is the indicator of renal damage and endothelial dysfunction, and FMD show that endothelial functions can be used in the following of early detection of renal damage and endothelial functions in FMF patients.

Background/Objective. Intermittent claudication (IC) is the symptom of peripheral artery disease (PAD) and causes functional disability. Remote ischemic preconditioning (RIPC), is a phenomenon in which a short period of sub-critical ischemia, protects tissues against ischemia/reperfusion/injury. We considered to test the hypothesis that RIPC in PAD patients suffering from IC would increase muscle resistance to ischemia and thus improve walking-capacity. Materials/Methods. A total of 63 patients with proven-IC underwent two treadmill tests (graded treadmill protocol) with a 28-day interval in between. Patients were consecutively assigned for the non/RIPC-group and RIPC-group procedure one by one. Patients received 5-cycles of alternating 5-minute inflation and 5-minute deflation of blood-pressure cuffs on nondominant upper-limb every day for four weeks. Initial claudication distance (ICD), total walking distance (TWD) and time to relief of claudication (TRC) were recorded during procedure. Results. Patients receiving-RIPC exhibited a marked increase in ICD and TWD between basal and last tests: 209.1 ± 15.4 m vs. 226 ± 15.0 m and 368.8 ± 21.0 m vs. 394 ± 19.9 m, respectively (p<0.001). In addition, patients receiving-RIPC represented a significant decrease in TRC between basal and last tests: 7.8 ± 1.3 min vs. 6.4 ± 1.1 min, respectively (p<0.001). Patients not receiving-RIPC did not exhibit improvement in ICD, TWD, and TRC between basal and last tests: 205.2 ± 12.1 min vs. 207.4 ± 9.9 min, 366.5 ± 24.2 min vs. 369.4 ± 23.2 min and 7.9 ± 1.4 min vs. 7.7 ± 1.3 min, respectively (p>0.05). Conclusion. A significant increase in ICD and TWD were observed in last/treadmill test in RIPC-group. In addition, a significant decrease in TRC was observed in last/treadmill test in RIPC-group. In non/RIPC-group, no improvement was observed in ICD, TWD and TRC.

Aim: We aimed to evaluate the awareness of pneumococcal vaccination (PCV13, PPSV23) in general cardiology outpatient clinics and impact of physicians’ recommendations on vaccination rates. Methods: This was a multicenter, observational, prospective cohort study. Patients over the age of 18 from 40 hospitals in different regions of Turkey who applied to the cardiology outpatient clinic between September 2022 and August 2021 participated. The vaccination rates were calculated within three months of follow-up from the admitting of the patient to cardiology clinics. Results: The 403 (18.2%) patients with previous pneumococcal vaccination were excluded from the study. The mean age of study population (n = 1808) was 61.9 ± 12.1 years and 55.4% were male. The 58.7% had coronary artery disease, hypertension (74.1%) was the most common risk factor, and 32.7% of the patients had never been vaccinated although they had information about vaccination before. The main differences between vaccinated and unvaccinated patients were related to education level and ejection fraction. The physicians’ recommendations were positively correlated with vaccination intention and behavior in our participants. Multivariate logistic regression analysis showed a significant correlation between vaccination and female sex [OR = 1.55 (95% CI = 1.25–1.92), p < 0.001], higher education level [OR = 1.49 (95% CI = 1.15–1.92), p = 0.002] patients’ knowledge [OR = 1.93 (95% CI = 1.56–2.40), p < 0.001], and their physician’s recommendation [OR = 5.12 (95% CI = 1.92–13.68), p = 0.001]. Conclusion: To increase adult immunization rates, especially among those with or at risk of cardiovascular disease (CVD), it is essential to understand each of these factors. Even if during COVID-19 pandemic, there is an increased awareness about vaccination, the vaccine acceptance level is not enough, still. Further studies and interventions are needed to improve public vaccination rates.

An accurate diagnosis of pulmonary hypertension (PH) is crucial to ensure that patients receive timely treatment. One of the used imaging models to detect pulmonary hypertension is the X-ray. Therefore, a new automated PH-type classification model has been presented to depict the separation ability of deep learning for PH types. We retrospectively enrolled 6642 images of patients with PH and the control group. A new X-ray image dataset was collected from a multicentre in this work. A transfer learning-based image classification model has been presented in classifying PH types. Our proposed model was applied to the collected dataset, and this dataset contains six categories (five PH and a non-PH). The presented deep feature engineering (computer vision) model attained 86.14% accuracy on this dataset. According to the extracted ROC curve, the average area under the curve rate has been calculated at 0.945. Therefore, we believe that our proposed model can easily separate PH and non-PH X-ray images.