ECG-Based AF Prediction System for Cardiac Surgery

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Solution Overview

Problem

Current methods fail to predict and prevent postoperative atrial fibrillation in cardiac surgery patients, leading to increased hospital costs, morbidity, and mortality, with no known methods for prediction or prevention.

Innovation Solution

A system that processes electrocardiogram (ECG) data to identify and characterize premature atrial contraction (PAC) activity, heart rate variability, and P-wave morphology, using signal processing components and classification models to calculate an AF probability index, predicting the likelihood of postoperative atrial fibrillation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If postoperative atrial fibrillation is treated with current methods (DCCV, pharmacologic agents, anticoagulation), then patient outcomes are managed, but hospital costs increase by $8000 per patient and morbidity/mortality rates remain high

Engineering Contradiction:

Improvepatient outcome managementVSAvoidhospital costs

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The system performs preliminary analysis of ECG data before postoperative AF occurs, identifying patients at high risk through automated detection of PAC activity, HRV parameters, and P-wave morphology abnormalities. This allows preventive measures to be taken before the condition develops, avoiding the high costs of treatment

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system continuously monitors ECG parameters and provides real-time feedback on AF risk probability, enabling dynamic adjustment of monitoring and preventive strategies based on changing patient status

Inventive Principle:

Principle #23Feedback

2Reliability

If postoperative atrial fibrillation is treated with urgent direct current cardioversion, then hemodynamic stability is restored, but the procedure requires airway management and procedural sedation increasing complexity

Engineering Contradiction:

Improvehemodynamic stabilityVSAvoidprocedural requirements

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system identifies patients at risk of pAF before surgery and during the postoperative period, enabling early intervention with less invasive measures such as pharmacologic prevention or elective cardioversion rather than urgent procedures requiring airway management

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system introduces an intermediate monitoring and risk stratification layer between surgical intervention and acute AF management, allowing for graduated responses based on risk level and clinical status

Inventive Principle:

Principle #24Intermediary (Mediator)

3Object-affected harmful factors

If long term anticoagulation therapy is administered to patients remaining in AF, then stroke and embolus risk is reduced, but bleeding risk increases in the brain and gastrointestinal tract

Engineering Contradiction:

Improvestroke and embolus preventionVSAvoidbleeding risk

Core Design Contradiction:

Object-affected harmful factorsVSObject-generated harmful factors

Solution Approach 1:

The system provides continuous monitoring of ECG parameters and dynamic risk assessment, enabling adjustment of anticoagulation therapy based on real-time AF risk rather than fixed long-term regimens, potentially reducing unnecessary anticoagulation and associated bleeding risks

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system changes the parameter of anticoagulation duration and intensity based on dynamic AF risk probability calculated from ECG features, transitioning from fixed long-term therapy to adaptive therapy based on actual physiological risk

Inventive Principle:

Principle #35Parameter changes

4Loss of information

If postoperative atrial fibrillation monitoring is performed manually, then clinical assessment is possible, but detection precision and prediction capability are insufficient

Engineering Contradiction:

Improveclinical assessment capabilityVSAvoidAF prediction accuracy

Core Design Contradiction:

Loss of informationVSMeasurement precision

Solution Approach 1:

The system replaces manual clinical assessment with automated computer-based analysis of ECG parameters, using algorithms to detect PAC activity, calculate HRV metrics, and analyze P-wave morphology with higher precision and objectivity than manual methods

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system adds a new dimension of quantitative risk probability assessment based on multiple ECG parameters (PAC rate, HRV frequency domain, time domain, and non-linear parameters) beyond traditional binary detection of AF presence

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

Data Source

PatentUS9636033B2Prediction and prevention of postoperative atrial fibrillation in cardiac surgery patients

Publication Date: 2017.05.02 THE CLEVELAND CLINIC FOUND

AI summary

Systems and methods are provided for predicting the onset of postoperative atrial fibrillation (AF) from electrocardiogram (ECG) data representing a patient. A signal processing component determines parameters representing the activity of the heart of the patient from the ECG data. A feature extraction component calculates a plurality of features useful in predicting postoperative AF from the determined parameters. A classification component determines an AF index for the patient from the calculated plurality of features. The AF index represents the likelihood that the patient will experience AF.