Method using trend analysis for cardiac treatment with calibrated and positionally corrected blood pressure watches, pressure-pace algorithms, artificial intelligence and thoracic electrical bioimpedance
A method of using thoracic electrical bioimpedance (TEB) as a component in a real-time closed-loop system to treat drug resistant hypertension (DRH) or diastolic heart failure (called HFpEF in patients with pacemakers using machine learning/AI and an algorithm (PressurePace—see the incorporated specifications) utilizing a “micro-interval” or continually updated trending method with the pacemaker's hardware/software as the source of the bioimpedance measurement, e.g. OptiVol. An apparatus for performing the method, and software instructions stored on a tangible medium for controlling a computer or processor to perform the method are included.
1 . A computing device, comprising at least one processor and at least one memory comprising instructions that, when executed by the at least one processor, cause the computing device to perform operations comprising:
determining, from a velocity of blood flow sensed by an optical sensor of a wearable device, a first blood pressure value and a subsequent blood pressure value of a patient;
receiving, via a wireless interface, the first blood pressure value and the subsequent second blood pressure value from the wearable device comprising an optical sensor;
receiving a first systemic vascular resistance (SVR) value and a subsequent second SVR value;
determining a change in blood pressure based on the first blood pressure value and the second blood pressure value;
determining a change in SVR based on the first SVR value and the second SVR value;
determining a pacing rate based on the change in blood pressure and the change in SVR;
administering a first initial micro-interval pacing rate to the patient via a pacing device based on the pacing rate;
receiving a third blood pressure value and a third SVR value in response to providing the first initial micro-interval pacing rate;
providing the third blood pressure value and third SVR to an artificial intelligence module trained to output a patient blood pressure category, wherein the artificial intelligence module is trained based on historical patient blood pressure data;
receiving an artificial intelligence module output from the artificial intelligence module, the artificial intelligence module output comprising a patient blood pressure category;
determining a pacing action based on the patient blood pressure category; and
administering the pacing action to the patient via the pacing device.
2 . The computing device of claim 1 , wherein determining the pacing rate is in response to identifying an adverse event based on the change in blood pressure and the change in SVR.
3 . The computing device of claim 2 , wherein identifying the adverse event comprises one of:
identifying a drop in blood pressure based on the change in blood pressure and identifying a rise in SVR based on the change in SVR;
identifying an increase in blood pressure based on the change in blood pressure and identifying the rise in SVR;
identifying a drop in blood pressure below a minimum blood pressure and identifying a stable SVR based on the change in SVR; or
identifying the increase in blood pressure and identifying the stable SVR.
4 . The computing device of claim 1 , wherein a micro-interval of the first initial micro-interval pacing rate is a fraction of the pacing rate.
5 . The computing device of claim 1 , wherein the patient blood pressure category is selected from one of a decrease in blood pressure by a successful amount, a decrease in blood pressure by an unacceptable amount, or a stable blood pressure.
6 . The computing device of claim 5 , wherein the determining the pacing action based on the patient blood pressure category being the decrease in blood pressure by a successful amount comprises:
receiving a third SVR; and
determining the pacing action is one of suspending the operations based on the third SVR meeting a target SVR, providing a second initial micro-interval pacing rate based on the third SVR not meeting the target SVR.
7 . The computing device of claim 5 , wherein the pacing action based on the patient blood pressure category being the decrease in blood pressure by an unacceptable amount comprises suspending the operations.
8 . The computing device of claim 5 , wherein determining the pacing action based on the patient blood pressure category being the stable blood pressure comprises:
receiving a third SVR; and
determining the pacing action is providing an updated micro-interval pacing rate based on the third SVR indicating a stable SVR.
9 . The computing device of claim 8 , wherein the updated micro-interval pacing rate is greater than the first initial micro-interval pacing rate.
10 . A method for cardiac pacing, the method comprising:
determining, from a velocity of blood flow sensed by an optical sensor of a wearable device, a first blood pressure value and a subsequent blood pressure value;
receiving, via a wireless interface, the first blood pressure value and the subsequent second blood pressure value from the wearable device;
receiving a first systemic vascular resistance (SVR) value and a subsequent second SVR value;
determining a change in blood pressure based on the first blood pressure value and the second blood pressure value;
determining a change in SVR based on the first SVR value and the second SVR value;
determining a pacing rate based on the change in blood pressure and the change in SVR;
administering a first initial micro-interval pacing rate based on the pacing rate;
receiving a third blood pressure value and a third SVR value in response to providing the first initial micro-interval pacing rate;
providing the third blood pressure value and third SVR to an artificial intelligence module trained to output a patient blood pressure category, wherein the artificial intelligence module is trained based on historical patient blood pressure data;
receiving an artificial intelligence module output from the artificial intelligence module, the artificial intelligence module output comprising a patient blood pressure category;
determining a pacing action based on the patient blood pressure category; and
administering the pacing action to the patient via the pacing device.
11 . The method of claim 10 , wherein the patient blood pressure category is selected from one of a decrease in blood pressure by a successful amount, a decrease in blood pressure by an unacceptable amount, or a stable blood pressure.
12 . The method of claim 11 , wherein the determining the pacing action based on the patient blood pressure category being the decrease in blood pressure by a successful amount comprises:
receiving a third SVR; and
determining the pacing action is one of suspending the cardiac pacing based on the third SVR meeting a target SVR, providing a second initial micro-interval pacing rate based on the third SVR not meeting the target SVR.
13 . The method of claim 11 , wherein the pacing action based on the patient blood pressure category being the decrease in blood pressure by an unacceptable amount comprises deactivating the cardiac pacing.
14 . The method of claim 11 , wherein determining the pacing action based on the patient blood pressure category being the stable blood pressure comprises:
receiving a third SVR; and
determining the pacing action is providing an updated micro-interval pacing rate based on the third SVR indicating a stable SVR.