Genetic Polymorphism Integration in CABG Mortality Prediction

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Solution Overview

Problem

Current models, such as the European System for Cardiac Operative Risk Evaluation (EuroSCORE), are limited in their ability to predict mortality for specific individuals following coronary artery bypass graft (CABG) surgery, and there is a need for improved predictive accuracy.

Innovation Solution

Identification of specific genetic polymorphisms, particularly in apolipoprotein E (APOE) and thrombomodulin (THBD), which are associated with altered five-year mortality risk, enabling more precise risk stratification and personalized therapeutic strategies.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional clinical risk models (EuroSCORE) are used, then the models are simple to implement, but they have limited ability to predict mortality for specific individuals

Engineering Contradiction:

Improvemortality prediction accuracyVSAvoidpredictive model complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent combines traditional clinical risk factors from EuroSCORE with genetic polymorphism data to create a composite predictive model. This merging of clinical and genetic information enhances mortality prediction accuracy for individual patients while maintaining the structured framework of existing clinical models.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The patent introduces genetic polymorphism parameters (specific SNPs in genes like APOE, THBD, and F2) as additional variables to the traditional clinical model. By adding these genetic parameters, the model transitions from purely clinical observations to a hybrid clinico-genetic assessment, improving predictive precision.

Inventive Principle:

Principle #35Parameter changes

2Reliability

If genetic polymorphism analysis is added to improve prediction accuracy, then individual mortality risk prediction improves, but the complexity of the predictive model increases

Engineering Contradiction:

Improvemortality risk prediction reliabilityVSAvoidpredictive model structure

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent segments the predictive model into distinct modules: clinical risk assessment (EuroSCORE) and genetic risk assessment (polymorphism analysis). This segmentation allows each component to be evaluated and integrated systematically, managing complexity through structured organization of different data types and analytical approaches.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent performs preliminary genotyping for specific genetic polymorphisms before surgical decision-making. By obtaining genetic information in advance and integrating it with clinical data, the model enables more reliable preoperative risk stratification, allowing clinicians to make informed decisions about surgical candidacy and perioperative management.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS8105781B2Predictors of long-term mortality following coronary artery bypass graft surgery

Publication Date: 2012.01.31 DUKE UNIV

AI summary

The present invention relates, in general, to perioperative depression and, in particular, to methods of identifying individuals at risk of perioperative depression.