System and a method for using a novel electrocardiographic screening algorithm for reduced left ventricular ejection fraction

Patent metadata

Field	Value
Publication number	US-11627906-B2
Application number	US-201816605726-A
Country	US
Kind code	B2
Filing date	Apr 17, 2018
Priority date	Apr 18, 2017
Publication date	Apr 18, 2023
Grant date	Apr 18, 2023

Abstract

A system and a method for identifying a patient with a threshold number of distinct ECG abnormalities. The system and the method include an ECG monitoring device; a server; a database; a network; a memory containing machine readable medium comprising a machine executable code having stored thereon instructions for identifying patients with a threshold number of distinct ECG abnormalities; and a processor coupled to the memory, the processor configured to execute the machine executable code to cause the processor to: receive an ECG data output from the ECG monitoring device; process the ECG data output to identify abnormalities in the ECG data; and analyze the abnormalities in the ECG data in order to output an indication of whether the patient has depressed LVEF, wherein the ECG monitoring device, the server, the database, the memory, and the processor are coupled to the network via communication links.

First claim

What is claimed is:

1. A system for identifying a patient with electrocardiogram (ECG) abnormalities comprising:
an ECG monitoring device;
a server;
a database;
a memory containing machine readable medium comprising a machine executable code having stored thereon instructions for analyzing ECG data; and
a processor coupled to the memory, the processor configured to execute the machine executable code to cause the processor to:
receive an ECG data output from the ECG monitoring device;
process the ECG data output to identify abnormalities in any combination of ECG parameters selected from at least: a resting heart rate, a global P-wave duration, a PR interval, a QRS duration, a QTc interval, a QRS-T angle, an intrinsicoid deflection, a QRS transition zone, a T-peak to T-end interval, and a left ventricular hypertrophy amount; and
analyze the abnormalities in the ECG parameters to determine whether the patient has at least a threshold number of abnormal ECG parameters,
wherein the ECG monitoring device, the server, the database, the memory, and the processor are coupled to a network via communication links,
wherein having at least the threshold number of abnormal ECG parameters indicates that the patient has reduced left ventricular ejection fraction (LVEF).

2. The system of claim 1 , wherein the ECG monitoring device comprises at least one of: a ECG machine to measure 12 lead ECG, an electrode that measures 3-lead ECG, combination of 4 electrodes and 3 lead ECG with an additional 5 th electrode located near or on the patient's chest to measure 5 lead ECG, a holter monitor test, a cardiac event recorder, a cardiac loop recorder, an implantable loop recorder, a stress ECG, a wearable device with heart monitoring capability, and a combination thereof.

3. The system of claim 1 , wherein the processing of the ECG data output comprises converting a raw data into a processed data.

4. The system of claim 1 , wherein analyzing the abnormalities in the ECG parameters comprises weighting certain abnormalities and outputting an abnormality score.

5. The system of claim 4 , wherein the abnormalities in the ECG parameters are detected by measuring a value of each of the ECG parameters and determining whether the value of each of the ECG parameters meets a threshold value.

6. The system of claim 1 , wherein the at least one ECG monitoring device is configured to be used by an authorized user of the patient to whom the at least one ECG monitoring device is being used.

7. The system of claim 1 , wherein the at least one ECG monitoring device collects ECG data from the patient and transfers the collected ECG data to at least one of the following: the monitor computer, the hosted server, or the database for screening to detect reduced LVEF in the patient when the patient is otherwise asymptomatic.

8. The system of claim 1 , wherein the at least one ECG device, the monitor computer, the hosted server, and the database are configured to each include a computer-readable medium including a computer program that may be executed to carry out the method comprising: collecting an ECG data output from the patient; processing the collected ECG data output to identify the abnormalities in the collected ECG data; and assign abnormality scores to the collected ECG data by comparing the collected ECG data to a predetermined or threshold measurement data for the abnormalities.

9. The system of claim 8 , wherein the computer-readable medium is configured to comprise a code section or code segment for performing each step disclosed in claim 8 .

10. The system of claim 9 , wherein the code section or code segment comprises an algorithm to screen or analyze asymptomatic patients for severally depressed LVEF using only ECG data.

11. The system of claim 10 , wherein the algorithm identifies patients as candidates for the primary prevention treatment of an implantable defibrillator (ICD).

12. The system of claim 10 , wherein the algorithm comprises at least one of: probability algorithm, machine learning algorithm, and a combination thereof.

13. The system of claim 10 , wherein the algorithm comprises a step-wise logistical regression to analyze a 12-lead ECG signal for specific abnormalities.

14. A method for identifying patients with electrocardiogram (ECG) abnormalities comprising:
receiving, at a controller, ECG data from a ECG monitoring device on a patient;
processing, by the controller, the ECG data to identify abnormalities in any combination of ECG parameters selected from at least: a resting heart rate, a global P-wave duration, a PR interval, a QRS duration, a QTc interval, a QRS-T angle, an intrinsicoid deflection, a QRS transition zone, a T-peak to T-end interval, and a left ventricular hypertrophy amount;
analyzing the abnormalities in the ECG parameters to determine whether the patient has at least a threshold number of abnormal ECG parameters, wherein having at least the threshold number of abnormal ECG parameters indicates that the patient has reduced left ventricular ejection fraction (LVEF) and
outputting an indication of whether the patient has reduced LVEF.

15. The method of claim 14 , wherein the ECG monitoring device is connected to a network, at least one monitoring device, a network, a monitor computer, a hosted server, and a database via communication links, wherein the ECG monitoring device, the at least one monitoring device, the monitor computer, the hosted server, and the database each comprise the controller.

16. The method of claim 15 , wherein the controller comprises a non-transitory machine readable medium having stored thereon instructions for performing a method comprising machine executable code which when executed by at least one machine, causes the machine to carry out the method of identifying patients with a threshold number of distinct ECG abnormalities.

17. The system of claim 1 , wherein the threshold number of abnormal ECG parameters is four.

18. The system of claim 1 , wherein the determination that the patient has reduced LVEF is based only on ECG data.

Assignees

• Cedars Sinai Medical Center

Inventors

• Chugh Sumeet S

Classifications

• G16H50/30

  for calculating health indices; for individual health risk assessment · CPC title

• A61B5/0245

  by using sensing means generating electric signals, {i.e. ECG signals} · CPC title

• A61B5/271

  Arrangements of electrodes with cords, cables or leads, e.g. single leads or patient cord assemblies · CPC title

• G16H50/70

  for mining of medical data, e.g. analysing previous cases of other patients · CPC title

• A61B5/02438

  with portable devices, e.g. worn by the patient · CPC title