The Association between Exercise-Induced Ventricular Premature Contractions and Long-Term Mortality in Patients without Obstructive Coronary Artery Disease.

Background: The treadmill exercise test is widely used to determine cardiovascular risk and mortality. Premature ventricular complexes (PVCs) are frequently observed during exercise stress testing. The literature on the role of PVCs observed during treadmill exercise testing in predicting prognosis is controversial. Hence, we aimed to evaluate the clinical results of PVCs seen during exercise testing in patients without obstructive coronary artery disease confirmed by coronary angiography (CAG). Methods: The study population consisted of 1624 consecutive patients who were considered high risk according to the Duke treadmill risk score and had no significant stenosis on CAG from January 2016 to April 2021. The primary endpoints of the study were long-term all-cause mortality of patients who had PVCs during the exercise test or during the resting phase. Results: Long-term mortality was observed in 53 of the 1624 patients after a mean follow-up of 47 months. PVCs were observed in 293 (18.7%) patients without long-term mortality, and in 24 (45.3%) patients with long-term mortality (p < 0.001). The model adjusted for all covariates showed that the presence of PVCs in the recovery phase [p < 0.007, hazard ratio (HR) (95% confidence interval (CI)) 2.244 (1.244-4.047)] and advanced age [p < 0.001, HR (95% CI) 1.194 (1.143-1.247)] were associated with long-term all-cause mortality. Conclusions: PVCs observed during treadmill exercise testing and the recovery phase were related to long-term mortality in patients without obstructive coronary artery disease.

Turkish Real Life Atrial Fibrillation in Clinical Practice: TRAFFIC Study.

BACKGROUND: Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia worldwide and is associated with an increased risk of thromboembolism, ischemic stroke, impaired quality of life, and mortality. The latest research that shows the prevalence and incidence of AF patients in Türkiye was the Turkish Adults' Heart Disease and Risk Factors study, which included 3,450 patients and collected data until 2006/07.The Turkish Real Life Atrial Fibrillation in Clinical Practice (TRAFFIC) study is planned to present current prevalence data, reveal the reflection of new treatment and risk approaches in our country, and develop new prediction models in terms of outcomes. METHODS: The TRAFFIC study is a national, prospective, multicenter, observational registry. The study aims to collect data from at least 1900 patients diagnosed with atrial fibrillation, with the participation of 40 centers from Türkiye. The following data will be collected from patients: baseline demographic characteristics, medical history, vital signs, symptoms of AF, ECG and echocardiographic findings, CHADS2-VASC2 and HAS-BLED (1-year risk of major bleeding) risk scores, interventional treatments, antithrombotic and antiarrhythmic medications, or other medications used by the patients. For patients who use warfarin, international normalized ratio levels will be monitored. Follow-up data will be collected at 6, 12, 18, and 24 months. Primary endpoints are defined as systemic embolism or major safety endpoints (major bleeding, clinically relevant nonmajor bleeding, and minor bleeding as defined by the International Society on Thrombosis and Hemostasis). The main secondary endpoints include major adverse cardiovascular events (systemic embolism, myocardial infarction, and cardiovascular death), all-cause mortality, and hospitalizations due to all causes or specific reasons. RESULTS: The results of the 12-month follow-up of the study are planned to be shared by the end of 2023. CONCLUSION: The TRAFFIC study will reveal the prevalence and incidence, demographic characteristics, and risk profiles of AF patients in Türkiye. Additionally, it will provide insights into how current treatments are reflected in this population. Furthermore, risk prediction modeling and risk scoring can be conducted for patients with AF.

Which Diastolic Pressure Should Be Used to Assess Diastolic Function?

BACKGROUND: Although high left ventricular filling pressures [left ventricular (LV) end-diastolic pressure or pulmonary capillary wedge pressure (PCWP)] are widely taken as surrogates for LV diastolic dysfunction, the actual distending pressure that governs LV diastolic stretch is transmural pressure difference (∆PTM). Clinically, preferring ∆PTM over PCWP may improve diagnostic and therapeutic decision-making. We aimed to compare the clinical implications of diastolic function characterization based on PCWP or ∆PTM. METHODS: We retrospectively screened our hospital database for adult patients with a clinical diagnosis of heart failure who underwent right heart catheterization. Echocardiographic diastolic dysfunction was graded according to the current guidelines. LV end-diastolic properties were assessed with construction of complete end-diastolic pressure-volume relationship (EDPVR) curves using the single-beat method. Survival status was checked via the electronic national health-care system. RESULTS: A total of 693 cases were identified in our database; the final study population comprised 621 cases. ∆PTM-based, but not PCWP-based, EDPVR diastolic stiffness constants were significantly predictive of advanced diastolic dysfunction. PCWP-based diastolic stiffness constants were not able to predict 5-year mortality, whereas ∆PTM-based EDPVR stiffness constants and volumes all turned out to have significant predictive power for 5-year mortality. CONCLUSION: Left ventricular diastolic function assessment can be improved using ∆PTM instead of PCWP. As ∆PTM ultimately linked to right-sided functions, this approach emphasizes the limitations of taking LV diastolic function as an isolated phenomenon and underlines the need for a complete hemodynamic assessment involving the right heart in therapeutic and prognostic decision-making processes.

Is Pulmonary Capillary Wedge Pressure a Reliable Indicator of Postcapillary Pulmonary Hypertension?

Although current pulmonary hypertension (PH) guidelines recommend a pulmonary capillary wedge pressure (PCWP) >15 mm Hg for the detection of a postcapillary component, the rationale of this recommendation may not be quite compatible with the peculiar hemodynamics of PH. We hypothesize that a high PCWP alone does not necessarily indicate left-sided disease, and this diagnosis can be improved using left ventricle transmural pressure difference (∆ PTM). In this 2-center, retrospective, observational study, we enrolled 1,070 patients with PH who underwent heart catheterization, with the final study population comprising 961 cases. ∆ PTM was calculated as PCWP minus right atrial pressure. The patients with group II PH had significantly higher ∆ PTM values (12.6 ± 6.6 mm Hg) compared with the other groups (1.1 ± 4.8 in group I, 12.4 ± 6.6 in group II, 2.5 ± 6.4 in group III, and 0.8 ± 8.0 in group IV, p <0.001) despite overlapping PCWP values. A ∆ PTM cutoff of 7 mm Hg identifies left heart disease when PCWP is >15 (area under curve 0.825, 95% confidence interval 0.784 to 0.866, p <0.001). Five-year mortality was significantly higher in patients with high ∆ PTM and PCWP subgroups compared with low ∆ PTM plus high PCWP (26.1% vs 18.5%, p = 0.027) and low ∆ PTM and PCWP subgroups (26.1% vs 15.6%, p <0.001). ∆ PTM has supplementary discriminatory power in distinguishing patients with and without postcapillary PH. In conclusion, a new approach utilizing ∆ PTM may improve our understanding of PH pathophysiology and may identify a subpopulation that may potentially benefit from PH-specific treatments.

Predictors of Long-Term Mortality in Patients with Stable Angina Pectoris and Coronary Slow Flow.

Background and Objectives: Coronary slow flow (CSF) is an angiographic phenomenon characterized by the slow progression of an injected contrast agent during diagnostic coronary angiography in the absence of significant stenosis. Although CSF is a common angiographic finding, the long-term outcomes and mortality rates are still unknown. This study aimed to investigate the underlying causes of mortality over a 10-year period in patients diagnosed with stable angina pectoris (SAP) and CSF. Materials and Methods: This study included patients with SAP who underwent coronary angiography from 1 January 2012 to 31 December 2012. All patients displayed CSF despite having angiographically normal coronary arteries. Hypertension (HT), diabetes mellitus (DM), hyperlipidaemia, medication compliance, comorbidities, and laboratory data were recorded at the time of angiography. Thrombolysis in myocardial infarction (TIMI) frame count (TFC) was calculated for each patient. The cardiovascular (CV) and non-CV causes of long-term mortality were assessed. Results: A total of 137 patients with CSF (93 males; mean age: 52.2 ± 9.36 years) were included in this study. Twenty-one patients (15.3%) died within 10 years of follow-up. Nine (7.2%) and 12 (9.4%) patients died of non-CV and CV causes, respectively. Total mortality in patients with CSF was associated with age, HT, discontinuation of medications, and high-density lipoprotein cholesterol (HDL-C) levels. The mean TFC was associated with CV mortality. Conclusion: Patients with CSF exhibited a notable increase in cardiovascular-related and overall mortality rates after 10 years of follow-up. HT, discontinuation of medications, HDL-C levels, and mean TFC were associated with mortality in patients with CSF.

Automated Bird Counting with Deep Learning for Regional Bird Distribution Mapping.

A challenging problem in the field of avian ecology is deriving information on bird population movement trends. This necessitates the regular counting of birds which is usually not an easily-achievable task. A promising attempt towards solving the bird counting problem in a more consistent and fast way is to predict the number of birds in different regions from their photos. For this purpose, we exploit the ability of computers to learn from past data through deep learning which has been a leading sub-field of AI for image understanding. Our data source is a collection of on-ground photos taken during our long run of birding activity. We employ several state-of-the-art generic object-detection algorithms to learn to detect birds, each being a member of one of the 38 identified species, in natural scenes. The experiments revealed that computer-aided counting outperformed the manual counting with respect to both accuracy and time. As a real-world application of image-based bird counting, we prepared the spatial bird order distribution and species diversity maps of Turkey by utilizing the geographic information system (GIS) technology. Our results suggested that deep learning can assist humans in bird monitoring activities and increase citizen scientists' participation in large-scale bird surveys.