Systems and methods for monitoring physiologic changes using cardiac electrogram signals

1. A method for monitoring serum potassium in a patient comprising:

gathering cardiac electrogram data from the patient using an implantable medical device having two or more electrodes;

separating, using the implantable medical device comprising a control circuit configured to separate, the cardiac electrogram data into discrete subunits including a T-wave;

aligning, using the implantable medical device comprising a control circuit configured to align, T-waves to create aligned discrete subunits;

averaging, using the implantable medical device comprising a control circuit configured to average, the aligned discrete subunits to generate an average T-wave for the cardiac electrogram data;

determining, using the implantable medical device comprising a control circuit configured to determine, a serum potassium value using the average T-wave for the cardiac electrogram data and a predetermined model relating T-wave values with serum potassium magnitudes;

comparing the serum potassium value to a threshold value; and

sending a notification signal from the implantable medical device through a telemetry interface of the medical device to an external device based on the comparison of the serum potassium value with the threshold value;

wherein determining a serum potassium value using the average T-wave for the cardiac electrogram data and a predetermined model relating T-wave morphology with serum potassium values comprises:

calculating an average T-wave change of the patient by comparing the average T-wave for the cardiac electrogram data against a previously determined baseline average T-wave for the patient; and

determining a serum potassium value using the average T-wave change for the cardiac electrogram data and a predetermined model relating T-wave change values with serum potassium values.

2. The method of claim 1 , further comprising periodically updating the predetermined model by evaluating an average T-wave of the patient corresponding to a serum potassium concentration of the patient measured in vitro.

3. The method of claim 2 , wherein the predetermined model is only updated after at least two separate in vitro measurements are made.

4. The method of claim 2 , wherein the predetermined model is only updated after at least 21 days after a device implant.

5. The method of claim 1 , wherein gathering cardiac electrogram data from the patient using two or more electrodes is performed with an implanted device.

6. The method of claim 1 , wherein the predetermined model relating T-wave values with serum potassium values represents the output of at least one of a regression analysis and a machine learning analysis.

7. The method of claim 6 , wherein the inputs for the regression analysis or machine learning analysis include previous cardiac electrogram data for the patient.

8. The method of claim 1 , wherein each discrete subunit including a T-wave comprises cardiac electrogram data spanning a time span of at least 0.15 seconds.

9. The method of claim 1 , wherein each discrete subunit including a T-wave comprises cardiac electrogram data spanning a time span that is user programmable.

10. The method of claim 1 , wherein the number of discrete subunits that are averaged is at least about 10 subunits.

11. The method of claim 1 , wherein the cardiac electrogram data spans at least 10 minutes.

12. The method of claim 1 , wherein aligning T-waves is selected from the group consisting of aligning peaks of the T-waves, aligning starting points of the T-waves, aligning ending points of the T-waves, aligning midpoints of the T-waves, aligning a single point of the T-waves, or aligning two or more points of the T-waves.

13. The method of claim 1 , further comprising discarding discrete subunits representing statistical outliers.

14. The method of claim 13 , wherein statistical outliers are evaluated by evaluating at least one of R to R variability and R to T variability.

15. The method of claim 1 , further comprising sending a prompt to an external patient device through the telemetry interface, wherein the prompt directs the patient to take a specific action prior to gathering cardiac electrogram data from the patient.

16. The method of claim 1 , wherein gathering cardiac electrogram data from the patient starts based on at least one of

the patient assuming a particular posture;

a particular time of day; or

activity below a predefined threshold.

17. The method of claim 1 , further comprising storing a new baseline T-wave value of the patient if the T-wave is stable over at least a threshold period of time.

18. The method of claim 17 , the threshold period of time comprising at least 30 days.

19. An implantable medical device comprising:

a housing;

a control circuit disposed in the housing;

a telemetry interface in electrical communication with the control circuit;

an electric field sensor channel interface in electrical communication with the control circuit;

wherein the control circuit is configured to

separate cardiac electrogram data received from the electric field sensor into discrete subunits including a T-wave;

align the subunits using the T-waves thereof to create aligned discrete subunits;

average the aligned discrete subunits to generate an average T-wave for the cardiac electrogram data;

determine a serum potassium value using the average T-wave for the cardiac electrogram data and a predetermined model relating T-wave values with serum potassium values;

compare the serum potassium value to a threshold value; and

send a notification signal from the implantable medical device through the telemetry interface to an external device based on the comparison of the serum potassium value with the threshold value;

wherein determining a serum potassium value using the average T-wave for the cardiac electrogram data and a predetermined model relating T-wave morphology with serum potassium values comprises:

calculating an average T-wave change of the patient by comparing the average T-wave for the cardiac electrogram data against a previously determined baseline average T-wave for the patient; and

determining a serum potassium value using the average T-wave change for the cardiac electrogram data and a predetermined model relating T-wave change values with serum potassium values.

20. The method of claim 1 , further comprising:

in response to the comparison of the serum potassium value with the threshold value, performing a confirmation test to quantify a serum potassium concentration.