A novel single-beat approach to assess right ventricular systolic function.
Alessandro BellofioreRebecca VanderpoolMelanie J BrewisAndrew J PeacockNaomi C CheslerPublished in: Journal of applied physiology (Bethesda, Md. : 1985) (2017)
Clinical assessment of right ventricular (RV) contractility in diseases such as pulmonary arterial hypertension (PAH) has been hindered by the lack of a robust methodology. Here, a novel, clinically viable, single-beat method was developed to assess end-systolic elastance (Ees), a measure of right ventricular (RV) contractility. We hypothesized that this novel approach reduces uncertainty and interobserver variability in the estimation of the maximum isovolumic pressure (Piso), the key step in single-beat methods. The new method was designed to include a larger portion of the RV pressure data and minimize subjective adjustments by the operator. Data were obtained from right heart catheterization of PAH patients in a multicenter prospective study ( data set 1) and a single-center retrospective study ( data set 2). To obtain Piso, three independent observers used an established single-beat method (based on the first derivative of the pressure waveform) and the novel method (based on the second derivative). Interobserver variability analysis included paired t-test, one-way ANOVA, interclass correlation (ICC) analysis, and a modified Bland-Altman analysis. The Piso values obtained from the two methods were linearly correlated for both data set 1 ( R2 = 0.74) and data set 2 ( R2 = 0.91). Compared with the established method, the novel method resulted in smaller interobserver variability ( P < 0.001), nonsignificant differences between observers, and a narrower confidence interval. By reducing uncertainty and interobserved variability, this novel approach may pave the way for more effective clinical management of PAH. NEW & NOTEWORTHY A novel methodology to assess right ventricular contractility from clinical data is demonstrated. This approach significantly reduces interobserver variability in the analysis of ventricular pressure data, as demonstrated in a relatively large population of subjects with pulmonary hypertension. This study may enable more accurate clinical monitoring of systolic function in subjects with pulmonary hypertension.
Keyphrases
- pulmonary hypertension
- electronic health record
- pulmonary arterial hypertension
- heart failure
- big data
- blood pressure
- left ventricular
- mycobacterium tuberculosis
- heart rate
- end stage renal disease
- pulmonary artery
- chronic kidney disease
- ejection fraction
- peritoneal dialysis
- cross sectional
- newly diagnosed
- double blind
- artificial intelligence