• J Clin Monit Comput · Feb 2017

    Heart period and blood pressure characteristics in splanchnic arterial occlusion shock-induced collapse.

    • Federico Aletti, Nicolò Gambarotta, Alexander H Penn, Manuela Ferrario, and Geert W Schmid-Schönbein.
    • Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Piazza Leonardo da Vinci, 32, 20133, Milan, Italy. federico.aletti@polimi.it.
    • J Clin Monit Comput. 2017 Feb 1; 31 (1): 167-175.

    AbstractThe nature of hemodynamic instability typical of circulatory shock is not well understood, but an improved interpretation of its dynamic features could help in the management of critically ill patients. The objective of this work was to introduce new metrics for the analysis of arterial blood pressure (ABP) in order to characterize the risk of catastrophic outcome in splanchnic arterial occlusion (SAO) shock. Continuous ABP (fs = 1 kHz) was measured in rats during experimental SAO shock, which induced a fatal pressure drop (FPD) in ABP. The FPD could either be slow (SFPD) or fast (FFPD), with the latter causing cardiovascular collapse. Time series of mean arterial pressure, systolic blood pressure and heart period were derived from ABP. The sample asymmetry-based algorithm Heart Rate Characteristics was adapted to compute the Heart Period Characteristics (HPC) and the Blood Pressure Characteristics (BPC). Baroreflex sensitivity (BRS) was assessed by means of a bivariate model. The approach to FPD of the animals who collapsed (FFPD) was characterized by higher BRS in the low frequency band versus SFPD animals (0.36 ± 0.15 vs. 0.19 ± 0.12 ms/mmHg, p value = 0.0196), bradycardia as indicated by the HPC (0.76 ± 0.57 vs. 1.94 ± 1.27, p value = 0.0179) and higher but unstable blood pressure as indicated by BPC (3.02 ± 2.87 vs. 1.47 ± 1.29, p value = 0.0773). The HPC and BPC indices demonstrated promise as potential clinical markers of hemodynamic instability and impending cardiovascular collapse, and this animal study suggests their test in data from intensive care patients.

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