One-point carotid wave intensity predicts cardiac mortality in patients with congestive heart failure and reduced ejection fraction

Measures of wave intensity as a non-invasive surrogate for cardiac function predicts mortality in haemodialysis patients

Background

Risk prediction in haemodialysis (HD) patients is challenging due to the impact of the dialysis regime on the patient's volume status and the complex interplay with cardiac function, comorbidities and hypertension. Cardiac function as a key predictor of cardiovascular (CV) mortality in HD patients is challenging to assess in daily routine. Thus the aim of this study was to investigate the association of a novel, non-invasive relative index of systolic function with mortality and to assess its interplay with volume removal.

Methods

A total of 558 (373 male/185 female) HD patients with a median age of 66 years were included in this analysis. They underwent 24-hour ambulatory blood pressure monitoring, including wave intensity analysis [i.e. S:D ratio (SDR)]. All-cause and CV mortality served as endpoints and multivariate proportional hazards models were used for risk prediction. Intradialytic changes were analysed in tertiles according to ultrafiltration volume. During a follow-up of 37.8 months, 193 patients died (92 due to CV reasons).

Results

The SDR was significantly associated with all-cause {univariate hazard ratio [HR] 1.36 [95% confidence interval (CI) 1.20-1.54], P < .001} and CV [univariate HR 1.41 (95% CI 1.20-1.67), P < .001] mortality. The associations remained significant in multivariate analysis accounting for possible confounders. Changes in the SDR from pre-/early- to post-dialytic averages were significantly different for the three ultrafiltration volume groups.

Conclusion

This study provides well-powered evidence for the independent association of a novel index of systolic function with mortality. Furthermore, it revealed a significant association between intradialytic changes of the measure and intradialytic volume removal.

Wave Intensity Analysis Combined With Machine Learning can Detect Impaired Stroke Volume in Simulations of Heart Failure

Heart failure is treatable, but in the United Kingdom, the 1-, 5- and 10-year mortality rates are 24.1, 54.5 and 75.5%, respectively. The poor prognosis reflects, in part, the lack of specific, simple and affordable diagnostic techniques; the disease is often advanced by the time a diagnosis is made. Previous studies have demonstrated that certain metrics derived from pressure-velocity-based wave intensity analysis are significantly altered in the presence of impaired heart performance when averaged over groups, but to date, no study has examined the diagnostic potential of wave intensity on an individual basis, and, additionally, the pressure waveform can only be obtained accurately using invasive methods, which has inhibited clinical adoption. Here, we investigate whether a new form of wave intensity based on noninvasive measurements of arterial diameter and velocity can detect impaired heart performance in an individual. To do so, we have generated a virtual population of two-thousand elderly subjects, modelling half as healthy controls and half with an impaired stroke volume. All metrics derived from the diameter-velocity-based wave intensity waveforms in the carotid, brachial and radial arteries showed significant crossover between groups-no one metric in any artery could reliably indicate whether a subject's stroke volume was normal or impaired. However, after applying machine learning to the metrics, we found that a support vector classifier could simultaneously achieve up to 99% recall and 95% precision. We conclude that noninvasive wave intensity analysis has significant potential to improve heart failure screening and diagnosis.

Noninvasive Assessment of Ventricular-Arterial Coupling in Heart Failure

The heart and the arterial system are anatomically and functionally linked together. Noninvasive assessment of ventricular-arterial coupling (VAC) can be done using different methods that are promising tools to assess individual hemodynamics and tailor treatment in patients with heart failure (HF). Moreover, different methods available can be appropriately used in different settings such as acute and chronic HF. VAC parameters also can add incremental value over the conventional risk factors in predicting cardiac outcome.

Comparison of arterial wave intensity analysis by pressure-velocity and diameter-velocity methods in a virtual population of adult subjects

Pressure-velocity-based analysis of arterial wave intensity gives clinically relevant information about the performance of the heart and vessels, but its utility is limited because accurate pressure measurements can only be obtained invasively. Diameter-velocity-based wave intensity can be obtained noninvasively using ultrasound; however, due to the nonlinear relationship between blood pressure and arterial diameter, the two wave intensities might give disparate clinical indications. To test the magnitude of the disagreement, we have generated an age-stratified virtual population to investigate how the two dominant nonlinearities viscoelasticity and strain-stiffening cause the two formulations to differ. We found strong agreement between the pressure-velocity and diameter-velocity methods, particularly for the systolic wave energy, the ratio between systolic and diastolic wave heights, and older subjects. The results are promising regarding the introduction of noninvasive wave intensities in the clinic.

Ultrasonographic assessment of organs other than the heart in patients with heart failure

The number of patients with heart failure has been dramatically increasing in Japan in association with aging of the society. This phenomenon is referred to as a heart failure pandemic. The fundamental origin of heart failure is cardiac dysfunction. Echocardiography is widely used to assess cardiac function, as well as to diagnose heart diseases that cause cardiac dysfunction. However, the severity of heart failure is not necessarily correlated with that of cardiac dysfunction. This is partly explained by the fact that heart failure induces dysfunction of organs other than the heart through hemodynamic deterioration and neurohumoral changes. In addition, one of the characteristics of patients with heart failure, particularly elderly patients, is the presence of numerous comorbidities. Symptoms of heart failure are not specific, and assessment of cardiac function, particularly left ventricular diastolic function, has not been established. Thus, ultrasonographic assessment of organs other than the heart helps the diagnosis of heart failure, assessment of the severity of heart failure, and development of our understanding of the pathophysiology in each patient. This review summarizes current knowledge about the usefulness of ultrasonographic assessment of organs other than the heart in heart failure.