Key result
Peripheral arterial waveforms differentiate preload, contractility, and afterload deficits, explaining 99% of variance.
Why the study?
Hemodynamic instability is common in critically ill patients, and whether peripheral arterial blood pressure waveforms can differentiate between decreased preload, contractility, and afterload is uncertain.
Do peripheral arterial blood pressure waveforms allow differentiation between preload-, contractility-, and afterload-deficient hemodynamic instability in a computational model?
Do peripheral arterial blood pressure waveforms allow differentiation between preload-, contractility-, and afterload-deficient hemodynamic instability in a computational model?
In silico simulations demonstrate that peripheral arterial waveform morphologies can differentiate between preload, contractility, and afterload deficits causing hemodynamic instability.
Should not yet change clinical hemodynamic assessment; leaves open in vivo validation of waveform-based differentiation.
Hemodynamic instability is frequently present in critically ill patients, primarily caused by a decreased preload, contractility, and/or afterload. We hypothesized that peripheral arterial blood pressure waveforms allow to differentiate between these underlying causes. In this in-silico experimental study, a computational cardiovascular model was used to simulate hemodynamic instability by decreasing blood volume, left ventricular contractility or systemic vascular resistance, and additionally adaptive and compensatory mechanisms. From the arterial pressure waveforms, 45 features describing the morphology were discerned and a sensitivity analysis and principal component analysis were performed, to quantitatively investigate their discriminative power. During hemodynamic instability, the arterial waveform morphology changed distinctively, for example, the slope of the systolic upstroke having a sensitivity of 2.02 for reduced preload, 0.80 for reduced contractility, and -0.02 for reduced afterload. It was possible to differentiate between the three underlying causes based on the derived features, as demonstrated by the first two principal components explaining 99% of the variance in waveforms. The features with a high correlation coefficient (>0.25) to these principal components are describing the systolic up- and downstroke, and the anacrotic and dicrotic notches of the waveforms. In this study, characteristic peripheral arterial waveform morphologies were identified that allow differentiation between deficits in preload, contractility, and afterload causing hemodynamic instability. These findings are confined to an in silico simulation and warrant further experimental and clinical research in order to prove clinical usability in daily practice.
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Mulder et al. (2022) studied Hemodynamic instability. Peripheral arterial blood pressure waveform analysis was evaluated on Discriminative power of arterial waveform morphology features to differentiate underlying causes of hemodynamic instability. Peripheral arterial waveform morphologies allowed differentiation between deficits in preload, contractility, and afterload, with the first two principal components explaining 99% of the variance.
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