Improved pressure contour analysis for estimating cardiac stroke volume using pulse wave velocity measurement

Abstract

BackgroundPressure contour analysis is commonly used to estimate cardiac performance for patients suffering from cardiovascular dysfunction in the intensive care unit. However, the existing techniques for continuous estimation of stroke volume (SV) from pressure measurement can be unreliable during hemodynamic instability, which is inevitable for patients requiring significant treatment. For this reason, pressure contour methods must be improved to capture changes in vascular properties and thus provide accurate conversion from pressure to flow.MethodsThis paper presents a novel pressure contour method utilizing pulse wave velocity (PWV) measurement to capture vascular properties. A three-element Windkessel model combined with the reservoir–wave concept are used to decompose the pressure contour into components related to storage and flow. The model parameters are identified beat-to-beat from the water-hammer equation using measured PWV, wave component of the pressure, and an estimate of subject-specific aortic dimension. SV is then calculated by converting pressure to flow using identified model parameters. The accuracy of this novel method is investigated using data from porcine experiments (N = 4 Pietrain pigs, 20–24.5 kg), where hemodynamic properties were significantly altered using dobutamine, fluid administration, and mechanical ventilation. In the experiment, left ventricular volume was measured using admittance catheter, and aortic pressure waveforms were measured at two locations, the aortic arch and abdominal aorta.ResultsBland–Altman analysis comparing gold-standard SV measured by the admittance catheter and estimated SV from the novel method showed average limits of agreement of ±26% across significant hemodynamic alterations. This result shows the method is capable of estimating clinically acceptable absolute SV values according to Critchely and Critchely.ConclusionThe novel pressure contour method presented can accurately estimate and track SV even when hemodynamic properties are significantly altered. Integrating PWV measurements into pressure contour analysis improves identification of beat-to-beat changes in Windkessel model parameters, and thus, provides accurate estimate of blood flow from measured pressure contour. The method has great potential for overcoming weaknesses associated with current pressure contour methods for estimating SV.

Astragalus mongholicus (Fisch.) Bge Improves Peripheral Treg Cell Immunity Imbalance in the Children With Viral Myocarditis by Reducing the Levels of miR-146b and miR-155

“…EF (ejection fraction) was detected by using a noninvasive method ( 25 ). SV (stroke volume) was examined by using a modified method ( 26 ).…”

Model-based management of cardiovascular failure: Where medicine and control systems converge

“…The model requires a dual pressure measurement of arterial pressure at one of the aortic, sub-aortic, or femoral arteries to assess pressure and pulse wave velocity to enable identification [125], and requires only a single, initial calibration via echocardiography or similar imaging. More specifically, it is a model-based measurement or sensor, and can provide real-time values with limited computation wellwithin current computing and signal processing capability.…”

“…Hence, an effective single compartment model has been used with clinical data to provide a real-time SV measure [125]. The model is identifiable and recent improvements [126] have begun to optimise its implementation to ensure identification is robust.…”

“…The model is identifiable and recent improvements [126] have begun to optimise its implementation to ensure identification is robust. It has been validated in animal studies of sepsis, inotrope therapy and fluid resuscitation, both alone and in sepsis induced by endotoxin infusion [125].…”

Blood pressure waveform contour analysis for assessing peripheral resistance changes in sepsis

“…One of the leading worldwide causes of intensive care unit (ICU) admission and mortality is cardiovascular disease and dysfunction (CVD), which costs an estimated $863 billion USD per annum (2010), and is the cause of roughly 31% of global deaths (2013) [ 1 ]. Thus, research into mitigating these large human and economic costs is a significant and ongoing field, ranging from work on less invasively estimating useful, but difficult to measure, clinical metrics [ 2 – 5 ], or a lumped model of the cardiovascular system [ 6 , 7 ], in an ICU environment, to work on investigating, selecting or estimating metrics of preclinical risk of cardiovascular [ 8 , 9 ] and arterial disease [ 10 , 11 ].…”