System and method for prediction and detection of circulatory shock

• US 8,262,579 B2
• Filed: 05/16/2008
• Issued: 09/11/2012
• Est. Priority Date: 05/16/2007
• Status: Active Grant

• Current Assignee: Massachusetts Institute of Technology
• Original Assignee: Massachusetts Institute of Technology
• Inventors: Parlikar, Tushar A., Heldt, Thomas, Verghese, George C., Mark, Roger G.
• Primary Examiner(s): VIVLEMORE, TRACY ANN
• Application Number:
  US12/122,247
• Publication Number:
  US 20080287753A1
• Time in Patent Office: 1,579 Days
• Field of Search: None
• US Class Current: 600/485
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes 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 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/33 specially adapted for cooperation with other devices
• CPC Class Codes: A61B 5/412 Detecting or monitoring sepsis
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

Systems and methods for prediction and detection of circulatory shock using estimates or measurements of arterial blood pressure, heart rate, stroke volume, cardiac output, total peripheral resistance, cardiac ejection fraction, cardiac contractility and ventricular end-diastolic volume are provided. These estimates and measurements are used to determine a type of circulatory shock. In some embodiments, the type of circulatory shock is determined to be one of septic shock, hypovolemic shock, anaphylactic shock, hemorrhagic shock, and cardiogenic shock.

Claims

1. A system for predicting or detecting circulatory shock, comprising:

a blood pressure measuring device;

a processor;

a display;

a user interface; and

a memory storing computer-executable instructions, which when executed by the processor cause the processor to;

receive measurements of arterial blood pressure from the blood pressure measuring device;

compute mean arterial blood pressure from the received arterial blood pressure measurements;

compute estimates, based on the received arterial blood pressure measurements, of heart rate, total peripheral resistance, cardiac output, ejection fraction, and ventricular end-diastolic volume; and

select a type of circulatory shock, from a plurality of types of circulatory shock, based on the computed mean arterial blood pressure and the computed estimates.

2. The system of claim 1, further comprising an electrocardiogram device, wherein selecting a type of circulatory shock is also based on measurements from the electrocardiogram device.

3. The system of claim 1, wherein the computer-executable instructions, when executed by the processor, cause the processor to display at least one of the received measurements and the computed estimates.

4. The system of claim 1, wherein the computer-executable instructions, when executed by the processor, cause the processor to display the selected type of circulatory shock.

5. The system of claim 1, wherein the type of circulatory shock is determined to be one of septic shock, hypovolemic shock, anaphylactic shock, and cardiogenic shock.

6. The system of claim 1, wherein the computed mean arterial blood pressure and the computed estimates are each classified as one of low, normal and high.

7. The system of claim 6, wherein the type of circulatory shock is determined to be one of septic shock, hypovolemic shock, anaphylactic shock, and cardiogenic shock.

8. The system of claim 7, wherein the type of circulatory shock is determined to be one or more of:

(A) septic shock if the mean arterial blood pressure is low, total peripheral resistance is low, heart rate is high, ejection fraction is normal or high, and cardiac output is low or high;

(B) hypovolemic shock if the mean arterial blood pressure is low, total peripheral resistance is high, heart rate is high, ejection fraction is normal or high, end-diastolic volume is low, and cardiac output is low or high;

(C) anaphylactic shock if the mean arterial blood pressure is low, total peripheral resistance is low, heart rate is high, ejection fraction is normal or high, and cardiac output is high; and

(D) cardiogenic shock if the mean arterial blood pressure is low, total peripheral resistance is high, ejection fraction is low, end-diastolic volume is high, and cardiac output is low.

9. The system of claim 1, 5, 7, or 8, wherein the selecting is done using a lookup table.

10. The system of claim 1, 5, 7, or 8, wherein the selecting is done using population-specific data.

11. The system of claim 1, 5, 7, or 8, wherein the selecting is done using patient-specific data.

12. The system of claim 1, 5, 7, or 8, wherein the selecting is done using a machine learning algorithm.

13. The system of claim 12, wherein the machine learning algorithm includes a Bayesian network.

14. The system of claim 12, wherein the machine learning algorithm includes a neural network.

15. The system of claim 12, wherein the machine learning algorithm includes a fuzzy logic model.

16. The system of claim 1, wherein the blood pressure measuring device is a noninvasive blood pressure measuring device.

17. The system of claim 16, wherein the noninvasive blood pressure measuring device is a photoplethysmographic blood pressure measuring device.

18. The system of claim 16, wherein the noninvasive blood pressure measuring device is a tonometric blood pressure measuring device.

19. The system of claim 1, wherein the arterial blood pressure is measured at a central artery of the cardiovascular system.

20. The system of claim 1, wherein the arterial blood pressure is measured at a peripheral artery of the cardiovascular system.

21. The system of claim 1, wherein the arterial blood pressure is measured at a pulmonary artery of the cardiovascular system.

22. The system of claim 1, wherein the computed estimates are uncalibrated estimates.

23. A method for predicting or detecting circulatory shock, the method comprising:

receiving measurements of arterial blood pressure;

computing mean arterial blood pressure from the received arterial blood pressure measurements;

computing estimates, based on the received arterial blood pressure measurements, of heart rate, total peripheral resistance, cardiac output, ejection fraction, and ventricular end-diastolic volume; and

selecting a type of circulatory shock, from a plurality of types of circulatory shock, based on the computed mean arterial blood pressure and the computed estimates.

24. The method of claim 23, further comprising receiving electrocardiograph measurements, wherein selecting a type of circulatory shock is also based on the electrocardiograph measurements.

25. The method of claim 23, further comprising displayed at least one of the received measurements and the computed estimates.

26. The method of claim 23, further comprising displaying the selected type of circulatory shock.

27. The method of claim 23, wherein the type of circulatory shock is determined to be one of septic shock, hypovolemic shock, anaphylactic shock, and cardiogenic shock.

28. The method of claim 23, wherein the computed mean arterial blood pressure and the computed estimates are each classified as one of low, normal and high.

29. The method of claim 28, wherein the type of circulatory shock is determined to be one of septic shock, hypovolemic shock, anaphylactic shock, and cardiogenic shock.

30. The method of claim 29, wherein the type of circulatory shock is determined to be one or more of:

(A) septic shock if the mean arterial blood pressure is low, total peripheral resistance is low, heart rate is high, ejection fraction is normal or high, and cardiac output is low or high;

(B) hypovolemic shock if the mean arterial blood pressure is low, total peripheral resistance is high, heart rate is high, ejection fraction is normal or high, end-diastolic volume is low, and cardiac output is low or high;

(C) anaphylactic shock if the mean arterial blood pressure is low, total peripheral resistance is low, heart rate is high, ejection fraction is normal or high, and cardiac output is high; and

(D) cardiogenic shock if the mean arterial blood pressure is low, total peripheral resistance is high, ejection fraction is low, end-diastolic volume is high, and cardiac output is low.

31. The method of claim 23, 27, 29, or 30, wherein the selecting is done using a lookup table.

32. The method of claim 23, 27, 29, or 30, wherein the selecting is done using population-specific data.

33. The method of claim 23, 27, 29, or 30, wherein the selecting is done using patient-specific data.

34. The method of claim 23, 27, 29, or 30, wherein the selecting is done using a machine learning algorithm.

35. The method of claim 34, wherein the machine learning algorithm includes a Bayesian network.

36. The method of claim 34, wherein the machine learning algorithm includes a neural network.

37. The method of claim 34, wherein the machine learning algorithm includes a fuzzy logic model.

38. The method of claim 23, wherein the arterial blood pressure is central arterial blood pressure.

39. The method of claim 23, wherein the arterial blood pressure is peripheral arterial blood pressure.

40. The method of claim 23, wherein the arterial blood pressure is pulmonary arterial blood pressure.

41. The method of claim 23, wherein the computed estimates are uncalibrated estimates.