ECG-based differentiation of LQT1 and LQT2 mutation

1. A method differentiating LQT1 mutation from LQT2 mutation, comprising:

obtaining an ECG signal for a patient;

determining at least a first ECG parameter and a second ECG parameter from the ECG signal; and

determining a probability that the patient is an LQT1 carrier or an LQT2 carrier based on a regression model which takes into account the first ECG parameter and the second ECG parameter.

2. The method of claim 1 , wherein the ECG signal is obtained from a database.

3. The method of claim 1 , wherein the ECG signal is obtained from an ECG capture device.

4. The method of claim 1 , wherein the first and second ECG parameters are selected from the group consisting of QT-peak interval, and Tpeak-to-Tend interval.

5. The method of claim 1 , wherein a probability that the patient is an LQT2 carrier is determined by the following formula:

log(odds)= K+C 1( P 1)+ C 2( P 2),

where K is a constant, C 1 is a first coefficient, C 2 is a second coefficient, P 1 is the first ECG parameter, and P 2 is the second ECG parameter.

6. The method of claim 5 , wherein:

K equals approximately −7.19;

C 1 equals approximately −15.70;

C 2 equals approximately 0.10;

P 1 is T-wave amplitude; and

P 2 is TpTe.

7. The method of claim 1 , further comprising determining a third ECG parameter, and wherein a probability that the patient is an LQT2 carrier is determined by the following formula:

log(odds)= K+C 1( P 1)+ C 2( P 2)+ C 3( P 3),

where K is a constant, C 1 is a first coefficient, C 2 is a second coefficient, C 3 is a third coefficient, P 1 is the first ECG parameter, P 2 is the second ECG parameter, and P 3 is the third ECG parameter.

8. The method of claim 7 , wherein:

K equals approximately 11.7;

C 1 equals approximately −1.35;

P 1 is RS T;

C 2 equals approximately −0.32;

P 2 is QTp;

C 3 equals approximately 0.25; and

P 3 is T-loop QT.

9. The method of claim 7 , wherein:

K equals approximately 11.73;

C 1 equals approximately −1352;

P 1 is a right slope of a Twave from ev 1 ;

C 2 equals approximately 0.2480;

P 2 is a QT loop offset;

C 3 equals approximately −0.3163; and

P 3 is a peak of a QT interval.

10. The method of claim 9 , wherein the peak of the QT interval is taken from Lead II on an ECG capture device.

11. The method of claim 1 , wherein obtaining the ECG signal comprises filtering the ECG signal.

12. The method of claim 11 , wherein filtering the ECG signal comprises low-pass FIR filtering the ECG signal.

13. The method of claim 11 , wherein filtering the ECG signal comprises removing a wandering baseline.

14. The method of claim 11 , wherein filtering the ECG signal comprises statistically combining multiple beats from the ECG signal.

15. The method of claim 14 , wherein statistically combining multiple beats from the ECG signal comprises creating a median beat.

16. The method of claim 11 , wherein filtering the ECG signal comprises discarding one or more leading beats from the ECG signal.

17. The method of claim 11 , wherein filtering the ECG signals comprises discarding one or more trailing beats from the ECG signal.

18. The method of claim 11 , wherein filtering the ECG signals comprises discarding beats which do not have a corresponding stable heart rate.

19. The method of claim 18 , wherein discarding beats which do not have a corresponding stable heart rate comprises discarding beats which have a heart rate that varies by more than a certain percentage in a previous arbitrary time frame.

20. The method of claim 19 , wherein the certain percentage is ten percent and the arbitrary time frame is two minutes.

21. The method of claim 11 , wherein filtering the ECO signal comprises sorting beats in the ECG signal into heart rate bins.

22. The method of claim 21 , wherein the first and second parameters are calculated only for a specific heart rate bin.

23. The method of claim 22 , wherein the specific heart rate bin comprises heart beats having a duration of approximately 775-800 milliseconds.

24. A computer readable medium having stored thereon instructions for differentiating between LQT1 and LQT2 mutations, which, when executed by a processor, causes the processor to perform the steps according to claim 1 .

25. A method of therapeutic decision making, comprising:

obtaining an ECG signal for a patient;

determining at least a first ECG parameter and a second ECG parameter from the ECG signal;

determining a probability that the patient is an LQT1 carrier or an LQT2 carrier based on a regression model which takes into account the first ECG parameter and the second ECG parameter; and

taking a therapeutic action based on the probability that the patient is an LQT1 carrier or an LQT2 carrier.

26. The method of claim 25 , wherein taking a therapeutic action based on the probability that the patient is an LQT1 carrier or an LQT2 carrier comprises:

prescribing a medication which has reduced or no interaction with an LQT1 condition if the patient has a probability of being an LQT1 carrier; or

prescribing a medication which has reduced or no interaction with an LQT2 condition if the patient has a probability of being an LQT2 carrier.

27. The method of claim 25 , wherein taking a therapeutic action based on the probability that the patient is an LQT1 carrier or an LQT2 carrier comprises prescribing genetic screening to confirm a genetic mutation.

28. The method of claim 25 , wherein taking a therapeutic action based on the probability that the patient is an LQT1 carrier or an LQT2 carrier comprises instructing the patient to stop taking a medication.