ESC Heart Failure (Apr 2022)

Pressure‐based estimation of right ventricular ejection fraction

  • Paul M. Heerdt,
  • Inderjit Singh,
  • Ahmed Elassal,
  • Vitaly Kheyfets,
  • Manuel J. Richter,
  • Khodr Tello

DOI
https://doi.org/10.1002/ehf2.13839
Journal volume & issue
Vol. 9, no. 2
pp. 1436 – 1443

Abstract

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Abstract Aims A method for estimating right ventricular ejection fraction (RVEF) from RV pressure waveforms was recently validated in an experimental model. Currently, cardiac magnetic resonance imaging (MRI) is the clinical reference standard for measurement of RVEF in pulmonary arterial hypertension (PAH). The present study was designed to test the hypothesis that the pressure‐based method can detect clinically significant reductions in RVEF as determined by cardiac MRI in patients with PAH. Methods and results RVEF estimates derived from analysis of RV pressure waveforms recorded during right heart catheterization (RHC) in 25 patients were compared with cardiac MRI measurements of RVEF obtained within 24 h. Three investigators blinded to cardiac MRI results independently performed pressure‐based RVEF estimation with the mean of their results used for comparison. Linear regression was used to assess correlation, and a receiver operator characteristic (ROC) curve was derived to define ability of the pressure‐based method to detect a maladaptive RV response, defined as RVEF <35% on cardiac MRI. In 23 patients, an automated adaptation of the pressure‐based RVEF method was also applied as proof of concept for beat‐to‐beat RVEF monitoring. The study cohort was comprised of 16 female and 9 male PAH patients with an average age of 53 ± 13 years. RVEF measured by cardiac MRI ranged from 16% to 57% (mean 37.7 ± 11.6%), and estimated RVEF from 15% to 54% (mean 36.2 ± 11.2%; P = 0.6). Measured and estimated RVEF were significantly correlated (r2 = 0.78; P < 0.0001). ROC curve analysis demonstrated an area under the curve of 0.94 ± 0.04 with a sensitivity of 81% and specificity of 85% for predicting a maladaptive RV response. As a secondary outcome, with the recognized limitation of non‐coincident measures, Bland–Altman analysis was performed and indicated minimal bias for estimated RVEF (−1.5%) with limits of agreement of ± 10.9%. Adaptation of the pressure‐based estimation method to provide beat‐to‐beat RVEF also demonstrated significant correlation between the median beat‐to‐beat value over 10 s with cardiac MRI (r2 = 0.66; P < 0.001), and an area under the ROC curve of 0.94 ± 0.04 (CI = 0.86 to 1.00) with sensitivity and specificity of 78% and 86%, respectively, for predicting a maladaptive RV response. Conclusions Pressure‐based estimation of RVEF correlates with cardiac MRI and detects clinically significant reductions in RVEF. Study results support potential utility of pressure‐based RVEF estimation for assessing the response to diagnostic or therapeutic interventions during RHC.

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