Abstract:Physiological compensatory mechanisms can mask the extent of hemorrhage in conscious mammals, which can be further complicated by individual tolerance and variations in hemorrhage onset and duration. We assessed the effect of hemorrhage rate on tolerance and early physiologic responses to hemorrhage in conscious sheep. Eight Merino ewes (37.4 ± 1.1 kg) were subjected to fast (1.25 mL/kg/min) and slow (0.25 mL/kg/min) hemorrhages separated by at least 3 days. Blood was withdrawn until a drop in mean arterial pr… Show more
“…To demonstrate the proposed framework we compare two configurations of a warning index applied to predict a hemorrhage-induced drop in blood pressure in conscious sheep from a previously reported study [20]. Experiments were performed at the University of Texas Medical Branch under a protocol reviewed and approved by the Institutional Animal Care and Use Committee and conducted in compliance with the guidelines of the National Institutes of Health and the American Physiological Society for the care and use of laboratory animals.…”
Section: Experimental Methods For Case Examplementioning
confidence: 99%
“…t event was defined by the stopping point of hemorrhage in the previously reported study as the time mean arterial pressure decreased during hemorrhage 30 mmHg mean arterial pressure from baseline [20]. For this demonstration, we defined T min and T max as 1 and 14 min before t event , respectively.…”
Section: Experimental Methods For Case Examplementioning
Patient monitoring algorithms that analyze multiple features from physiological signals can produce an index that serves as a predictive or prognostic measure for a specific critical health event or physiological instability. Classical detection metrics such as sensitivity and positive predictive value are often used to evaluate new patient monitoring indices for such purposes, but since these metrics do not take into account the continuous nature of monitoring, the assessment of a warning system to notify a user of a critical health event remains incomplete. In this article, we present challenges of assessing the performance of new warning indices and propose a framework that provides a more complete characterization of warning index performance predicting a critical event that includes the timeliness of the warning. The framework considers 1) an assessment of the sensitivity to provide a notification within a meaningful time window, 2) the cumulative sensitivity leading up to an event, 3) characteristics on if the warning stays on until the event occurs once a warning has been activated, and 4) the distribution of warning times and the burden of additional warnings (e.g., false-alarm rate) throughout monitoring that may or may not be associated with the event of interest. Using an example from an experimental study of hemorrhage, we examine how this characterization can differentiate two warning systems in terms of timeliness of warnings and warning burden.
“…To demonstrate the proposed framework we compare two configurations of a warning index applied to predict a hemorrhage-induced drop in blood pressure in conscious sheep from a previously reported study [20]. Experiments were performed at the University of Texas Medical Branch under a protocol reviewed and approved by the Institutional Animal Care and Use Committee and conducted in compliance with the guidelines of the National Institutes of Health and the American Physiological Society for the care and use of laboratory animals.…”
Section: Experimental Methods For Case Examplementioning
confidence: 99%
“…t event was defined by the stopping point of hemorrhage in the previously reported study as the time mean arterial pressure decreased during hemorrhage 30 mmHg mean arterial pressure from baseline [20]. For this demonstration, we defined T min and T max as 1 and 14 min before t event , respectively.…”
Section: Experimental Methods For Case Examplementioning
Patient monitoring algorithms that analyze multiple features from physiological signals can produce an index that serves as a predictive or prognostic measure for a specific critical health event or physiological instability. Classical detection metrics such as sensitivity and positive predictive value are often used to evaluate new patient monitoring indices for such purposes, but since these metrics do not take into account the continuous nature of monitoring, the assessment of a warning system to notify a user of a critical health event remains incomplete. In this article, we present challenges of assessing the performance of new warning indices and propose a framework that provides a more complete characterization of warning index performance predicting a critical event that includes the timeliness of the warning. The framework considers 1) an assessment of the sensitivity to provide a notification within a meaningful time window, 2) the cumulative sensitivity leading up to an event, 3) characteristics on if the warning stays on until the event occurs once a warning has been activated, and 4) the distribution of warning times and the burden of additional warnings (e.g., false-alarm rate) throughout monitoring that may or may not be associated with the event of interest. Using an example from an experimental study of hemorrhage, we examine how this characterization can differentiate two warning systems in terms of timeliness of warnings and warning burden.
“…The compensatory mechanisms to hypovolemia include an early sympathetic response characterized by increased heart rate and systemic increments in vascular resistance, which are mostly mediated by the action of catecholamines, especially noradrenaline, in cardiac muscle and in arteriolar smooth muscle cells. 27,28 In addition, this compensatory vasoconstriction is mediated by thromboxane A2-triggered signaling in smooth muscle cells. 29 It has been demonstrated that plasma levels of thromboxane A2 are significantly lower in dengue shock syndrome patients than in healthy populations and patients with dengue hemorrhagic fever but without shock.…”
Dengue virus (DENV) infection of humans is presently the most important arthropod-borne viral global threat, for which no suitable or reliable animal model exists. Reports addressing the effect of DENV on vascular components other than endothelial cells are lacking. Dengue virus infection of vascular smooth muscle cells, which play a physiological compensatory response to hypotension in arteries and arterioles, has not been characterized, thus precluding our understanding of the role of these vascular components in dengue pathogenesis. Therefore, we studied the permissiveness of primary human umbilical artery smooth muscle cells (HUASMC) to DENV 1-4 infection and compared with the infection in the previously reported primary human umbilical vein endothelial cells (HUVEC) and the classically used, non-transformed, and highly permissive Lilly Laboratories Cell-Monkey Kidney 2 cells. Our results show that HUASMC are susceptible and productive to infection with the four DENV serotypes, although to a lesser extent when compared with the other cell lines. This is the first report of DENV permissiveness in human smooth muscle cells, which might represent an unexplored pathophysiological contributor to the vascular collapse observed in severe human dengue infection.
“…Following the post-transfusion period (after data recording ended) on the first day of experiment the remaining blood was reinfused. Three (or more) days later, the experiment was repeated on each animal at the alternate hemorrhage rate of the first day [1] . Fig.…”
Section: Experimental Design Materials and Methodsmentioning
confidence: 99%
“…The data set comprises experimental information (e.g., hemorrhage rate, animal weight, event times), physiological waveforms (arterial and central venous blood pressure, electrocardiogram), time-series records of non-invasive physiological measurements (SpO 2 , tissue oximetry), intermittent arterial and venous blood gas analyses (e.g., hemoglobin, lactate, SaO 2 , SvO 2 ) and intermittent thermodilution cardiac output measurements. A detailed explanation of the hemodynamic and pulmonary changes during hemorrhage is available in a previous publication (Scully et al, 2016) [1] .…”
In this paper we describe a data set of multivariate physiological measurements recorded from conscious sheep (N = 8; 37.4 ± 1.1 kg) during hemorrhage. Hemorrhage was experimentally induced in each animal by withdrawing blood from a femoral artery at two different rates (fast: 1.25 mL/kg/min; and slow: 0.25 mL/kg/min). Data, including physiological waveforms and continuous/intermittent measurements, were transformed to digital file formats (European Data Format [EDF] for waveforms and Comma-Separated Values [CSV] for continuous and intermittent measurements) as a comprehensive data set and stored and publicly shared here (Appendix A). The data set comprises experimental information (e.g., hemorrhage rate, animal weight, event times), physiological waveforms (arterial and central venous blood pressure, electrocardiogram), time-series records of non-invasive physiological measurements (SpO2, tissue oximetry), intermittent arterial and venous blood gas analyses (e.g., hemoglobin, lactate, SaO2, SvO2) and intermittent thermodilution cardiac output measurements. A detailed explanation of the hemodynamic and pulmonary changes during hemorrhage is available in a previous publication (Scully et al., 2016) [1].
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