Determining hemodynamic performance

Abstract

A method for determining haemodynamic performance in a human or animal subject comprises receiving at a processor data representing haemodynamic variables measured from the subject over time. The haemodynamic variables comprise at least two of Systemic Perfusion Pressure (SPP), Systemic Vascular Resistance (SVR), Cardiac Output (CO), Heart Rate (HR) and Stroke Volume (SV). The data are processed to produce a display signal for causing a display device to present a visual mapping relating the haemodynamic variables according to the relationship SPP=CO H SVR and the visual mapping is displayed on a display device. The visual mapping may be corrected Heart Rate (HR) or include a second mapping which facilitates an adjustment to take account of HR.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS [0001] This application is a U.S. National Phase of International Application No. PCT / AU2010 / 000748, filed Jun. 17, 2010, designating the U.S. and published in English on Dec. 23, 2010 as WO 2010 / 1449961, which claims the benefit of U.S. Provisional Patent Application 61 / 218,053 filed Jun. 17, 2009.BACKGROUND OF THE INVENTION [0002] 1. Field of the Invention [0003] The present invention relates to a method, system and software product for determining haemodynamic performance in a human or animal subject. It relates particularly but not exclusively to a computer-implemented method, system and software product for generating a visual mapping of haemodynamic variables obtained from the subject, preferably in real time, for use in monitoring and improvement of therapeutic treatment. [0004] 2. Description of the Related Art [0005] In a normal state of health, the human or animal body system continuously maintains physiological balance. Even during ...

AI Technical Summary

Benefits of technology

[0017] In one embodiment, the processor processes the data to produce a second display signal causing the display device to present simultaneously a second visual mapping. The visual mapping produced by the second display signal plots data according to the relationship CO=HR H SV. This mapping can provide insight into the elderly circulation.

[0019] It is to be understood, however, that an autoregulation zone to which a subject's therapy may be directed during resuscitation need not be unique to that subject. For example, in ambulatory or emergency scenarios there may be no data available which represents that subject's haemodynamic performance when in a state of health at rest and so that subject's unique autoregulation zone may not be known. Thus, the autoregulation zone referred to during resuscitation may be obtained from mapped data collected from a range of representative subjects having similar demographic characterisation. Indeed this approach may achieve significant improvements in clinical outcomes. Demographic characterisation may include matching one or more of e.g. age, gender, body mass index, body surface area and the like.

Problems solved by technology

In a non-optimal state of haemodynamic performance and where autoregulation has become impaired, the subject will often enter a state of shock manifesting in low blood pressure.

Failure to administer appropriate therapy leads to worsening of the patient's condition, ultimately leading to heart failure.

Given the complexity and interaction of the organs of circulatory system, it is difficult for physicians to determine appropriate treatment when the subject's haemodynamic performance is being monitored using a variety of distinct variables viewed subjectively and individually.

The principal obstacle to improving outcomes arises from the lack of a consensus about the appropriate haemodynamic goals in patient management.

There is broad agreement that all patients require the same haemodynamic goals, but there is disagreement about which goals (in blood pressure, cardiac output, oxygenation) are critically important.

However, these curves do not describe the subject having high output hypotension (as occurs in sepsis).

The Guyton model devised in the 1970s relied on the study of small numbers of laboratory animals and now inferior measurement techniques to explain how blood pressure and cardiac output were controlled, in order to devise treatments.

Although the Guyton model intuitively matches clinical observations in a steady state situation, it does not adequately explain shock states and fails to account for physiological differences in e.g. the fit versus obese individual and the young versus elderly adult.

Further, its use has prompted unproven theories that have been applied in the clinical setting, perhaps to the detriment of patients being treated.

Images