Screening method and system to estimate the severity of injury in critically ill patients

• US 20070276275A1
• Filed: 05/23/2007
• Published: 11/29/2007
• Est. Priority Date: 05/24/2006
• Status: Abandoned Application

• Current Assignee: Miami University
• Original Assignee: University of Miami
• Inventors: Duncan, Robert C., Proctor, Kenneth G.
• Application Number:
  US11/802,472
• Publication Number:
  US 20070276275A1
• Time in Patent Office: Days
• US Class Current: 600/513
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/352 Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
• CPC Class Codes: A61B 5/4076 Diagnosing or monitoring particular conditions of the nervous system A61B5/4821, A61B5/4824 take precedence
• CPC Class Codes: A61B 5/7257 using Fourier transforms

Abstract

Estimated heart rate variability (HRV) may be used to determine a heart rate variability index. Based on a relationship between one or more variables and the HRV, a multiple regression analysis may be performed to reduce a confounding effect of the one or more variables on a relationship between the heart rate variability index and the one or more variables. This index may then be normalized from 0-100. A computer, or other suitable device, operatively connected to a field monitor capable of taking an EKG, may determine an HRV index, which can then be used to determine the likelihood of a variety of medical conditions. These conditions can include such things as the likelihood of an abnormality were a computed axial tomography scan to be performed, thus, in some cases, reducing or eliminating the need for performing such a scan.

Claims

1. A method of screening a patient comprising:

estimating a heart rate variability (HRV) based on an EKG signal;

determining one or more adjustment factors, including at least one of heart rate, presence/absence of sedation, age, gender, or blood pressure;

calculating an HRV index based at least in part on the estimated HRV and the one or more adjustment factors; and

determining an aspect of a patient'"'"'s condition based on the calculated HRV index.

2. The method of claim 1, wherein the determination includes determining at least a probability of whether one or more pathological medical conditions exists.

3. The method of claim 1, wherein the determination includes determining whether or not a medical procedure needs to be performed on the patient.

4. The method of claim 1, wherein the determination includes determining the probability of an abnormality were a computed axial tomography scan of the patient to be performed.

5. The method of claim 1, wherein estimating the HRV comprises determining a standard deviation of normal R-R intervals (SDNN) of the EKG signal.

6. The method of claim 1, wherein estimating the HRV comprises determining a root mean square of successive differences of R-R intervals (RMSSD) of the EKG signal.

7. The method of claim 1, wherein estimating the HRV comprises determining a Fast Fourier transform of the EKG signal.

8. The method of claim 1, further comprising normalizing the heart rate variability index to a scale of 0-100 and displaying the normalized heart rate variability index.

9. A system for screening a patient comprising:

an input that receives an EKG signal; and

a computer system that estimates a heart rate variability (HRV) based on the EKG signal, receives input related to at least one of heart rate, presence or absence of sedation, age, gender, systolic blood pressure or diastolic blood pressure, and calculates a heart rate variability index based at least in part on the estimated HRV and the received input.

10. The system of claim 9, wherein the computer system predicts a probability of a pathological medical condition in the patient, from whom the EKG signal originates, based on the heart rate variability index.

11. The system of claim 9, wherein the computer system determines a need for a medical procedure to be performed on the patient, from whom the EKG signal originates, based on the heart rate variability index.

12. The system of claim 9, wherein the computer system predicts a probability of an abnormality in a computed axial tomography scan of the patient, from whom the EKG signal originates, based on the heart rate variability index.

13. The system of claim 9, wherein the computer system normalizes the heart rate variability index to a scale of 0-100 and displays the normalized heart rate variability index.

14. The system of claim 9, wherein the computer system estimates the HRV by determining a standard deviation of normal R-R intervals (SDNN) of the EKG signal.

15. The system of claim 9, wherein the computer system estimates the HRV by determining a root mean square of successive differences of R-R intervals (RMSSD) of the EKG signal.

16. The system of claim 9, wherein the computer system estimates the HRV by determining a Fast Fourier transform of the EKG signal.

17. The system of claim 9, wherein the computer system displays patient care instructions care based on the heart rate variability index.

18. A method comprising:

estimating a heart rate variability (HRV) based on an EKG signal;

determining a heart rate based on the EKG signal; and

calculating a heart rate variability index based at least on the estimated HRV and the determined heart rate.

19. The method of claim 18, further comprising predicting a probability of a traumatic brain injury (TBI) in a patient, from whom the EKG signal originates, based on the heart rate variability index.

20. The method of claim 18, further comprising determining a need for a medical procedure to be performed on a patient, from whom the EKG signal originates, based on the heart rate variability index.

21. The method of claim 20, wherein the medical procedure is a CAT scan.

22. The method of claim 18, further comprising normalizing the heart rate variability index to a scale of 0-100 and displaying the normalized heart rate variability index.

23. The method of claim 18, wherein estimating the HRV comprises determining a standard deviation of normal R-R intervals (SDNN) of the EKG signal.

24. The method of claim 18, wherein estimating the HRV comprises determining a root mean square of successive differences of R-R intervals (RMSSD) of the EKG signal.

25. The method of claim 18, wherein estimating the HRV comprises determining a Fast Fourier transform of the EKG signal.

26. The method of claim 18, wherein, in addition to the estimated HRV and the determined heart rate, the heart rate variability index is calculated based on one or more of the presence or absence of sedation, age, gender, systolic blood pressure or diastolic blood pressure.

27. A system comprising:

an input which receives an EKG signal; and

a computer system which estimates a heart rate variability (HRV) based on the EKG signal, determines a heart rate based on the EKG signal, and calculates a heart rate variability index based at least on the estimated HRV and the determined heart rate.

28. The system of claim 27, wherein the computer system predicts a probability of a traumatic brain injury (TBI) in a patient, from whom the EKG signal originates, based on the heart rate variability index.

29. The system of claim 27, wherein the computer system determines a need for a medical procedure to be performed on a patient, from whom the EKG signal originates, based on the heart rate variability index.

30. The system of claim 29, wherein the medical procedure is a CAT scan.

31. The system of claim 27, wherein the computer system normalizes the heart rate variability index to a scale of 0-100.

32. The system of claim 27, wherein the computer system estimates the HRV by determining a standard deviation of normal R-R intervals (SDNN) of the EKG signal.

33. The system of claim 27, wherein the computer system estimates the HRV by determining a root mean square of successive differences of R-R intervals (RMSSD) of the EKG signal.

34. The system of claim 27, wherein the computer system estimates the HRV by determining a Fast Fourier transform of the EKG signal.

35. The system of claim 27, wherein, in addition to the estimated HRV and the determined heart rate, the computer system calculates the heart rate variability index based on one or more of presence or absence of sedation, age, gender, systolic blood pressure or diastolic blood pressure.

36. The system of claim 27, wherein the computer system displays patient care instructions care based on the heart rate variability index.

37. The system of claim 27, wherein the computer system displays both the HRV index and patient care instructions based on the HRV index.