Left atrial dilatation and ST-T changes predict cardiovascular outcome in chronic hemodialysis patients

Non-specific electrocardiographic ST-T abnormalities predict mortality in patients on peritoneal dialysis

Background

This study aimed to evaluate the predictive value of non-specific ST-segment and/or T-wave abnormalities in electrocardiography (ECG) for all-cause and cardiovascular mortality (CVM) in peritoneal dialysis (PD) patients.

Methods

All patients who started PD between November 1, 2005, and February 28, 2017, at the First Affiliated Hospital of Nanchang University were enrolled. The primary outcomes were all-cause mortality and CVM. The Kaplan-Meier method and a log-rank test were used for the survival analysis. Multivariate Cox proportional hazards models were used to investigate the risk factors for all-cause mortality and CVM.

Results

A total of 724 eligible PD patients were enrolled, including 401 (55.4%) men. In total, 153 (21.1%) patients died during a mean follow-up period of 27 (interquartile range, 13-41) months, and cardiovascular death was responsible for 84 of these deaths. The patients with non-specific ST-T abnormalities (NSSTTAs) had lower overall and cardiovascular survival rates compared to those free from any ECG abnormalities. According to the multivariate Cox proportional hazards models, (NSSTTAs) are independent risk factors for all-cause mortality and CVM, the hazard ratios are 1.81 (95% confidence interval, 1.11-2.95; p = 0.017) and 2.86 (95% confidence interval, 1.52-5.37; p = 0.001), respectively.

Conclusion

Non-specific ST-T abnormalities can serve as risk markers of all-cause and CVM in PD patients.

Left atrial strain: A novel "biomarker" for chronic kidney disease patients?

Cardiovascular disease and chronic kidney disease are frequently inter-connected and this association leads to an exponential growth of cardiovascular risk. This risk is currently underestimated by the existing algorithms and there is a constant need for new markers to predict adverse outcomes in this special population. In general population left atrial strain has emerged as an important tool for both the diagnosis and prognostic stratification, but data regarding its role in chronic kidney disease patients is scarce. The purpose of this review is to summarize the current evidence regarding this matter. Left atrial size and function mirror the duration and severity of increased left ventricular filling pressures. Increased left atrial volume index and impaired left atrial strain parameters are independent predictors for adverse cardiovascular events. Left atrial strain is impaired before changes in volume appear, thus being able to predict both diastolic and systolic function in chronic kidney disease patients. Finally, left atrial strain can identify renal patients with impaired exercise capacity and this could have clinical applications in the rehabilitation of this patients.

Electrocardiographic changes before and after successful kidney transplantation and associations with cardiovascular and mortality outcomes

INTRODUCTION

Electrocardiographic (ECG) changes before and after kidney transplantation are not well-defined. Our aim was to describe the evolution of ECG in patients on dialysis before and after successful kidney transplantation and to explore the association between ECG findings and major cardiovascular (CV) events and mortality after kidney transplantation.

PATIENTS AND METHODS

Electrocardiographics were collected retrospectively 3 times: at entry to the transplantation waiting list, at transplantation, and 1 year after the transplantation from 212 kidney transplantation recipients. Altogether 19 ECG variables were analyzed.

RESULTS

Left ventricular hypertrophy was present in 10.2% by the Cornell voltage-duration product criteria and 10.7% by the Sokolow-Lyon voltage criteria before kidney transplantation. The presence of ST depression (OR 3.12, 95% CI 1.12 -8.7 and P = .03) at entry to the waiting list and Q wave at the time of transplantation (OR 3.28, 95% CI 1.06-10.10 and P = .04) were both independently associated with major CV events after the transplantation. In addition, the presence of Q wave at entry to the waiting list was a risk factor of premature death after the transplantation (OR 2.92, 95% CI 1.06-8.05 and P = .04).

DISCUSSION

Careful analysis of the ECG before transplantation can be used to estimate cardiovascular events and mortality risk after kidney transplantation.

The prognostic value of positive T-wave in lead aVR in hemodialysis patients

BACKGROUND

Given that cardiac disease is the leading cause of mortality in hemodialysis (HD) patients, identification of patients at risk for cardiac mortality is crucial. The aim of this study was to determine if positive T-wave amplitude in lead aVR (TaVR) was predictive of cardiovascular (CV) mortality and sudden cardiac death (SCD) in a group of HD patients.

METHODS AND RESULTS

After exclusion, 223 HD patients were prospectively followed-up for 25.43 ± 3.56 months. Patients were divided into TaVR negative (n = 186) and TaVR positive (n = 37) groups. Myocardial infarction, diabetes and beta-blocker therapy were more frequent in positive TaVR patients. Patients with upright TaVR were older, had higher left ventricular mass index, lower ejection fraction, higher calcium × phosphate product, higher troponin T level, higher prevalence of ST-T abnormalities, and increased width of QRS complex and QT interval, compared with patients with negative TaVR. A Kaplan-Meier analysis showed that the cumulative incidences of CV mortality as well as SCD were higher in patients with positive TaVR compared with those with negative TaVR (log-rank, p < 0.001 in both cases). A multivariate analysis selected age [hazard ratio (HR) 1.71, p < 0.001], heart rate (HR 1.42, p = 0.016), and positive TaVR (HR 2.21, p = 0.001) as well as age (HR 1.88, p < 0.001), and positive TaVR (HR 1.53, p = 0.014) as independent predictors of CV mortality and SCD, respectively.

CONCLUSION

In HD patients, positive TaVR is an independent and powerful predictor of CV mortality as well as SCD. This simple ECG parameter provides additional information beyond what is available with other known traditional risk factors and allows the identification of patients most at risk of CV events.