The assessment of right ventricular (RV) function still remains a challenge. Two-dimensional (2D) speckle tracking has recently been proposed to evaluate right ventricular function by analyzing myocardial deformation. The aim of this study was to evaluate the role of 2D systolic strain measures of RV in predicting mortality in patients with chronic heart failure (HF). We enrolled 332 outpatients in a stable clinical condition and in conventional therapy. A right ventricular-focused four-chamber view was analyzed by 2D speckle tracking to evaluate the global longitudinal strain of RV (RV-GLS) and the strain of RV free wall (RV-fwLS). During a mean follow-up of 36 AE 26 months, 64 patients died. Both RV-GLS and RV-fwLS were associated with all-cause mortality in univariate (HR: 1.16; 95% CI: 1.10-1.23; P < 0.001; C-index: 0.72; and HR: 1.10; 95% CI: 1.06-1.15; P < 0.001; C-index: 0.68, respectively) as well as multivariate analysis (HR: 1.13; 95% CI: 1.05-1.21; P:0.001; C-index: 0.85; and HR: 1.07; 95% CI: 1.02-1.12; P:0.004; C-index: 0.84, respectively). In conclusion, our findings demonstrate the role of RV 2D strain measures to independently predict mortality. These data highlight the clinical usefulness of this echocardiographic approach in the daily management of HF outpatients. (Echocardiography 2016;33:992-1000)
Ventricular repolarization is a complex electrical phenomenon which represents a crucial stage in electrical cardiac activity. It is expressed on the surface electrocardiogram by the interval between the start of the QRS complex and the end of the T wave or U wave (QT). Several physiological, pathological and iatrogenic factors can influence ventricular repolarization. It has been demonstrated that small perturbations in this process can be a potential trigger of malignant arrhythmias, therefore the analysis of ventricular repolarization represents an interesting tool to implement risk stratification of arrhythmic events in different clinical settings. The aim of this review is to critically revise the traditional methods of static analysis of ventricular repolarization as well as those for dynamic evaluation, their prognostic significance and the possible application in daily clinical practice.
Aim of the study: In chronic heart failure (CHF) patients, renal congestion plays a key role in determining the progression of renal dysfunction and a worse prognosis. The aim of this study was to define the role of Doppler venous patterns reflecting renal congestion that predict heart failure progression. Methods: We enrolled outpatients affected by CHF, in stable clinical conditions and in conventional therapy. All patients underwent a clinical evaluation, routine chemistry, an echocardiogram and a renal echo-Doppler. Pulsed Doppler flow recording was performed at the level of interlobular renal right veins in the tele-expiratory phase. The venous flow patterns were divided into five groups according to the fluctuations of the flow. Type A and B were characterized by a continuous flow, whereas type C was characterized by a short interruption or reversal flow during the end-diastolic or protosystolic phase. Type D and E were characterized by a wide interruption and/or reversal flow. The occurrence of death and/or of heart transplantation and/or of hospitalization due to heart failure worsening was considered an event during follow-up. Results: During a median follow-up of 38 months, 126 patients experienced the considered end-point. Venous pattern C (HR 4.04; 95% CI: 2.14–7.65; p < 0.001), pattern D (HR 7.16; 95% CI: 3.69–13.9; p < 0.001) and pattern E (HR 8.94; 95% CI: 4.65–17.2; p < 0.001) were all associated with events using an univariate Cox regression analysis. Moreover, both the presence of pattern C (HR: 1.79; 95% CI: 1.09–2.97; p: 0) and of pattern D or E (HR: 1.90; 95% CI: 1.16–3.12; p: 0.011) remained significantly associated to events using a multivariate Cox regression analysis after correction for a reference model with an improvement of the overall net reclassification index (0.46; 95% CI 0.24–0.68; p < 0.001). Conclusions: Our findings demonstrate the independent and incremental role of Doppler venous patterns reflecting renal congestion in predicting HF progression among CHF patients, thus suggesting its possible utility in daily clinical practice to better characterize patients with cardio-renal syndrome.
Galectin-3 and ST2 are emerging biomarkers involved in myocardial fibrosis. We evaluate the relevance of a multiparametric biomarker approach based on increased serum levels of NT-proBNP, galectin-3, and ST2 in stratifying the prognosis of chronic heart failure (CHF) outpatients. In 315 CHF outpatients in stable clinical condition clinical and echocardiographic evaluations were performed. Routine chemistry and serum levels of NT-proBNP, galectin-3, and ST2 were also assessed. During a 12 month follow-up, cardiovascular death, and/or heart failure (HF) occurred in 64 patients. The presence of NT-proBNP, galectin-3, and ST2 were higher than the recommended cutoffs and were all associated with events at univariate Cox regression analysis, as well as in a multivariate analysis including the three biomarkers. When a score based on the number of biomarkers above the recommended cut-offs was used (in a range of 0–3), it was associated with events both with respect to the univariate (HR 2.96, 95% CI 2.21–3.95, p < 0.001, C-index 0.78) and the multivariate (HR 1.52, 95% CI 1.06–2.17, p: 0.023, C-index 0.87) analyses, after correction for the variables of a reference model. Our results suggest that an easy prognostic approach based on the combination of three biomarkers, although with partially-overlapping pathophysiological mechanisms, is able to identify patients with the highest risk of heart failure progression.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.