Determining hemodynamic performance

• US 9,173,575 B2
• Filed: 06/17/2010
• Issued: 11/03/2015
• Est. Priority Date: 06/17/2009
• Status: Active Grant

• Current Assignee: Human Chimp Pty Limited
• Original Assignee: Stephen Woodford
• Inventors: Woodford, Stephen
• Primary Examiner(s): NEGIN, RUSSELL SCOTT
• Application Number:
  US13/378,353
• Publication Number:
  US 20120130697A1
• Time in Patent Office: 1,965 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: A61B 5/02028 Determining haemodynamic parameters not otherwise provided for, e.g. cardiac contractility or left ventricular ejection fraction
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/029 Measuring or recording blood output from the heart, e.g. minute volume A61B8/065 takes precedence
• CPC Class Codes: A61B 5/412 Detecting or monitoring sepsis
• CPC Class Codes: A61B 5/743 Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• CPC Class Codes: G06F 17/10 Complex mathematical operations function generation by table look-up G06F1/03; evaluation of elementary functions by calculation G06F7/544
• CPC Class Codes: G16B 45/00 ICT specially adapted for bioinformatics-related data visualisation, e.g. displaying of maps or networks
• CPC Class Codes: G16B 5/00 ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 40/60 for the operation of medical equipment or devices
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

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×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.

Claims

1. A computer-implemented method for generating visual representations of data related to hemodynamic performance in a human or animal subject comprising:

receiving at a data mapping computer processor, first received data measured from the subject over time, from which at least two hemodynamic variables selected from the group including Systemic Perfusion Pressure (SPP), Systemic Vascular Resistance (SVR), Cardiac Output (CO), Heart Rate (HR) and Stroke Volume (SV) are derivable either directly or indirectly or using the equation CO=HR×

SV;

operating the data mapping computer processor to transform the first received data corresponding to SVR in such a way that there is an adjustment for pulsatile blood flow caused by left ventricular contractions of the subject, whereby the adjustment produces a new hemodynamic variable referred to as actual Systemic Vascular Resistance (aSVR), where aSVR is calculated as the product of SVR and HR as derived from the first received data;

further operating the data mapping computer processor to process the new hemodynamic variable, aSVR, and the first received data to produce a display signal, the display signal causing a display device to present a visual mapping relating at least two hemodynamic variables according to the new relationship SPP=SV×

aSVR; and

displaying the visual mapping on a display device;

wherein the visual mapping presented on the display illustrates trends in the subject'"'"'s hemodynamic performance over time, as determined from the first received data measured from the subject over time, and transformed by the data mapping computer processor.

2. A method according to claim 1 wherein the visual mapping plots one of:

(i) SPP in a first dimension and SV in a second dimension;

(ii) aSVR in a first dimension and SPP in a second dimension; and

(iii) SV in a first dimension and aSVR in a second dimension.

3. A method according to claim 1 wherein the data mapping computer processor:

processes the first received data to produce a second display signal; and

causes the display device to present simultaneously a second visual mapping based on the second display signal according to the relationship CO=HR×

SV.

4. A method according to claim 1 wherein the visual mapping includes one or more markers representing a scale for determining a value of a third hemodynamic variable.

5. A method according to claim 1 including the step of color coding in the visual mapping to indicate one or more features in the data selected from the group including:

time elapsed;

an intervention;

gender; and

age.

6. A method according claim 1 wherein the data mapping computer processor is programmed to approximate and present on the display, one or more of:

an autoregulation zone unique to the subject based on the received data or a portion thereof; and

an autoregulation zone based on a population of subjects having similar physiological profiles.

7. A method according to claim 1 wherein the data mapping computer processor is further programmed to identify in the data one or more patterns associated with a physiological syndrome.

8. A method according to claim 7 wherein the physiological syndrome is shock, and the data mapping computer processor is programmed to classify the shock syndrome into one of type 1, type 2, type 3 or a combination thereof based on the one or more identified patterns.

9. A method according claim 1 wherein the data mapping computer processor is further programmed to quantify a deficit in one or more hemodynamic variables measured from the subject.

10. A method according to claim 1 wherein the data mapping computer processor is programmed to quantify a deficit by:

(i) determining a difference between the data and a pre-determined autoregulation zone unique to the subject;

or

(ii) determining a difference between the data and a pre-determined autoregulation zone representative of a population of individuals;

or

(iii) extrapolating data values to a point of intersection representing a notional autoregulation zone unique to the subject.

11. A method according to claim 1 wherein the data mapping computer processor is programmed to perform one or more of:

(a) identifying automatically non-optimal hemodynamic function in the subject;

(b) recommending a therapeutic action to restore optimal hemodynamic function in the subject;

(c) controlling delivery of therapy to a subject, where titration of the therapy under the control of the processor is directed to restoring hemodynamic performance toward an autoregulatory zone applicable to the subject; and

(d) evaluating the effectiveness of a therapy in an individual subject or a population of individuals.

12. A method according to claim 1 wherein the data is obtained and processed in real-time.

26. A computer program product embodied on a non-transitory memory device containing instructions according to the computer-implemented method of claim 1 and causing the data-mapping computer processor to perform the computer implemented method for determining hemodynamic performance in a human, according to claim 1.

13. A system for generating visual representations of data related to hemodynamic function in a human or animal subject, the system comprising:

one or more transducers for monitoring continuously over time, at least two hemodynamic variables of the subject selected from the group including Systemic Perfusion Pressure (SPP), Systemic Vascular Resistance (SVR) Cardiac Output (CO), Heart Rate (HR) and Stroke Volume (SV) and generating one or more corresponding first data signals, wherein the hemodynamic variables are obtained from the subject directly or indirectly or using the equation CO=HR×

SV;

a data mapping computer processor receiving the one or more first data signals and configured to transform the first data signals corresponding to SVR to adjust for pulsatile blood flow caused by left ventricular contractions of the subject, whereby the adjustment produces a new hemodynamic variable referred to as actual Systemic Vascular Resistance (aSVR), where aSVR is calculated as the product of SVR and HR as obtained from the subject, the data mapping computer processor being further configured to process the new hemodynamic variable, aSVR and the first data signals to generate a display signal for a visual representation comprising a mapping of at least two hemodynamic variables according to the new relationship SPP=SV×

aSVR; and

a display device receiving the display signal and generating the visual representation;

wherein the visual mapping presented on the display illustrates trends in the subject'"'"'s hemodynamic performance over time, as determined from the first received data measured from the subject over time and transformed by the data mapping computer processor, and the subject'"'"'s hemodynamic function is determinable upon inspection of the trends shown on the display device.

14. A system according to claim 13 wherein the visual representation comprises one or more markers representing a scale for determining a value of a third hemodynamic variable.

15. A system according to claim 13 further including a mode selector for selecting a mode of visual representation of the data;

wherein the mode is selected from;

SPP in a first dimension and SV in a second dimension;

aSVR in a first dimension and SPP in a second dimension;

CO in a first dimension and SPP in a second dimension;

and

SV in a first dimension and HR aSVR in a second dimension.

16. A system according to claim 15 wherein the data mapping computer processor produces a second display signal for causing the display to present a second visual mapping of variables according to the relationship CO=HR×

SV, and the modes selectable by the mode selector include simultaneous display of the second visual mapping.

17. A system according to claim 13 comprising an analysis module for approximating an autoregulation zone unique to the subject based on the received data or a portion thereof.

18. A system according to claim 13 comprising a diagnosis module for identifying one or more patterns in the data associated with a physiological syndrome.

19. A system according to claim 18 wherein the physiological syndrome is shock and the diagnosis module uses the one or more identified patterns to classify the shock syndrome into one of:

type 1, type 2, type 3 or a combination thereof.

20. A system according to claim 13 comprising an analysis module for quantifying a deficit in one or more of the monitored hemodynamic variables from the subject.

21. A system according to claim 20 wherein:

(a) the deficit is quantified by determining a difference between the data and a pre-determined autoregulation zone unique to the subject;

or

(b) the deficit is quantified by determining a difference between the data and a pre-determined autoregulation zone representative of a population of individuals;

or

(c) the deficit is quantified by extrapolating data values to a point of intersection representing a notional autoregulation zone unique to the subject.

22. A system according to claim 13 comprising a therapy titration module in communication with a therapy set attached to the subject, the therapy titration module controlling titration of therapy from the therapy set.

23. A system according to claim 13 comprising an evaluation module configured to assess hemodynamic data collected during administration of a therapy and to provide an evaluation of the effectiveness of the therapy in maintaining or restoring hemodynamic performance in the subject.

24. A system according to claim 23 wherein the evaluation module evaluates one or both of micro trends and macro trends in the hemodynamic data.

25. A system according to claim 13 comprising an alert module configured to activate an alert automatically when non-optimal hemodynamic performance is detected.

27. A method for generating visual representations of data related to hemodynamic performance in a human or animal subject or in a group of human or animal subjects, the method including the steps of:

receiving at a data mapping computer data representing two or more hemodynamic variables selected from the group including;

(i) Systemic Perfusion Pressure (SPP);

(ii) Systemic Vascular Resistance (SVR);

(iii) Cardiac Output (CO), (iv) Heart Rate (HR); and

(v) Cardiac Output (CO), wherein data representing said variables may be derived from the subject or the group of subjects directly or indirectly or using the equation CO=HR×

SV;

operating the data mapping computer to transform the received data to adjust for pulsatile blood flow caused by left ventricular contractions in the subject or group of subjects, whereby the adjustment produces a new hemodynamic variable referred to as actual Systemic Vascular Resistance (aSVR) where aSVR is calculated as the product of SVR and HR as derived directly or indirectly from the subject or group of subjects;

operating the data mapping computer to generate on a display operatively coupled to the data mapping computer, a visual representation of data representing hemodynamic variables; and

approximating from the visual representation the hemodynamic performance of the subject or group of subjects;

wherein the visual representation includes one or more markers for quantification by the data mapping computer of a third hemodynamic variable, wherein the visual representation comprises a visual mapping of the hemodynamic variables according to the new relationship;

SPP=SV×

aSVR.

28. A method according to claim 27 wherein the two variables selected for visual representation are:

SPP in a first dimension and SV in a second dimension;

aSVR in a first dimension and SPP in a second dimension; and

SV in a first dimension and aSVR in a second dimension.

29. A method according to claim 27 wherein the visual representation includes simultaneously a mapping of SV and HR.

30. A method according to claim 27 wherein the visual display data causes color coding of the visual mapping to indicate one or more features in the data selected from the group including:

time elapsed;

an intervention;

gender; and

age.

31. A method according to claim 27, comprising the step of approximating an autoregulation zone unique to the subject.

32. A method according to claim 27, wherein the hemodynamic data is obtained and used to generate the visual representation in real time.

33. A method according to claim 27, comprising the step of identifying in the data one or more patterns associated with a physiological syndrome.

34. A method according to claim 33, wherein the physiological syndrome is shock and the one or more identified patterns are used to classify the shock syndrome into one of type 1, type 2, type 3 or a combination thereof.

35. A method according to claim 34, wherein:

(a) the deficit is quantified by determining a difference between the data and a pre-determined autoregulation zone unique to the subject;

or

(b) the deficit is quantified by determining a difference between the data and a pre-determined autoregulation zone unique to the subject;

or

(c) the deficit is quantified by extrapolating data values to a point of intersection representing a notional autoregulation zone unique to the subject.

36. A method according to claim 27, further comprising the step of quantifying a deficit in one or more of the hemodynamic variables in the subject.

37. A method according to claim 27, comprising tailoring therapeutic treatment for the subject so as to restore hemodynamic performance toward the subject'"'"'s autoregulation zone.

38. A method according to claim 27, comprising the step of automatically identifying non-optimal hemodynamic performance in the subject.

39. A method according to claim 38 comprising the step of automatically activating an alert when the subject'"'"'s hemodynamic performance is non-optimal.

40. A method according to claim 27 used in a method of evaluating the effect of pharmacological therapy on hemodynamic function.

41. A method according to claim 40 comprising automatically devising a treatment plan or suggesting a therapy for restoring non-optimal hemodynamic performance toward an optimal state.

42. A method according to claim 27 wherein the visual representation provides a continuous mapping of hemodynamic performance in real time.