Aortic Pulse Wave Velocity Derivation From Arterial Waveforms in Critically Ill Infants and Children

Abstract

Methods Hemodynamically stable pre-pubertal children with an indwelling arterial catheter were enrolled. Applanation tonometry was used to measure aPWV, which was derived from the transit distance and pulse transit time. The carotid and femoral arteries were used as preferential sites and transit distance was measured relative to the suprasternal notch, an anatomical landmark for the aortic valve. Pulse transit time was derived from the time delay between the two pulse waveforms from the ECG-R wave. Peripheral arterial line waveforms were converted into ascending aortic waveforms by Hemolab software. Forward and backward wave forms were derived from the ascending aortic waveforms. Time delays were calculated between forward and backward wave forms. Effective reflecting distance (EfRD) was calculated from the equation 0.173*age+0.661*BMI+ 34.548. Estimated aPWV was derived from EfRD and the time delays. Measured aPWV and estimated aPWVs were compared. Results Aortic pulse wave velocity and arterial pressure waveforms were obtained in 33 infants and children (50% female). 66% (22) patients had history of congenital heart disease. 54% (18) patients were on mechanical ventilation. 39% (13) patients were on vasoactive medications. 0-1 year aged infants (n=18) had aPWV 0.49-15.91 m/s. aPWV in 1-5-year-old patients (n=5) was 1.82-3.72 m/s, and in 6-10-year-old patients (n=6) was 1.27-4.09 m/s. 10-12-year-old patients (n=4) had aPWV 1.7-7.02 m/s. We identified artifacts from ventilators, nasogastric lines, and pacifiers in some patients that necessitated the use of the brachial artery instead of the carotid artery for the measurement of aPWV. Measured and estimated (from arterial waveforms) aPWVs were similar in 6 patients. Estimated aPWV from arterial waveforms by using Effective reflecting distance (EfRD) correlated well with the patients' age, weight, and length. Conclusions Aortic pulse wave velocity can be feasibly measured in a critical care setting, although patient monitoring and instrumentation may make uniform measurement protocols not feasible. Future derivations of aPWV from arterial waveforms will need to take this into account. Calculating aPWV from arterial waveforms can help us to include a larger sample size of the patient population with arterial waveform data, eliminating the need for tonometry.