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Development and Validation of an Explainable Prediction Model to Assess the Risk of Coronary Artery Disease in Young
Haolin Shi1, Shanshan Zhao1, Yingshuai Wang1
1Institute of Medical Information/Library, Chinese Academy of Medical Sciences & Peking Union Medical College, 100020 Beijing, China.
Insights
A new risk assessment system aids early detection of coronary artery disease in young and middle-aged adults with hypertension. This tool uses blood, urine, and questionnaire data for improved cardiovascular health screening.
Area of Science:
- Cardiovascular disease research
- Public health screening
- Biomedical data analysis
Background:
- Coronary artery disease (CAD) risk assessment is inadequate for young and middle-aged adults (20-60).
- This demographic faces challenges in early disease identification due to limited symptoms and healthcare access.
- Hypertension is a significant risk factor for CAD in this population, increasing susceptibility to sudden cardiac death.
Purpose of the Study:
- To develop a tailored risk assessment system for coronary heart disease (CHD) in hypertensive young and middle-aged individuals.
- To leverage readily available data from blood tests, urine tests, and questionnaires for risk prediction.
- To improve early identification and management of cardiovascular risk in a vulnerable population.
Main Methods:
- Utilized data from the National Health and Nutrition Examination Survey (NHANES) database (2005-2019).
- Selected 26 pertinent features after iterative feature selection.
- Developed and evaluated five predictive models, employing SHapley Additive exPlanations (SHAP) for model interpretability.
Main Results:
- Included 709 patients with coronary artery disease and 6409 healthy controls in the analysis.
- The LightGBM model demonstrated superior performance with an area under the curve (AUC) of 0.93.
- SHAP analysis provided insights into individual feature contributions to risk prediction.
Conclusions:
- The developed risk assessment system shows potential for improved screening of coronary artery disease.
- A publicly accessible risk assessment tool has been created to aid healthcare providers and individuals.
- This system facilitates proactive cardiovascular health management in at-risk young and middle-aged adults.
Background:
There is currently a lack of adequate risk assessment for coronary artery disease in the young and middle-aged population (ages 20-60). This cohort is characterized by limited symptom presentation, low utilization of medical facilities, and challenges in accessing healthcare services. Consequently, these individuals experience difficulties in early disease identification, rendering them susceptible to sudden cardiac death and premature mortality upon the manifestation of symptoms. Data from regular blood and urine tests, as well as questionnaires, are readily available and well-documented across diverse healthcare environments. Hypertension is a notable risk for coronary artery disease within this population. In light of these challenges, we present a risk assessment system for coronary heart disease specifically tailored for young and middle-aged individuals with hypertension, utilizing data derived from blood and urine examinations in conjunction with a brief questionnaire.
Methods:
The dataset was sourced from the National Health and Nutrition Examination Survey (NHANES) database, covering the years 2005-2019. Following three iterations of feature selection, we identified 26 pertinent features. Subsequently, we developed five predictive models to facilitate large-scale screening for coronary heart disease risk. To enhance the interpretability of our models, we employed SHapley Additive exPlanations (SHAP) to evaluate the individual contributions of each feature.
Results:
We included 709 patients diagnosed with coronary artery disease and 6409 healthy individuals in our analysis. The results showed that LightGBM exhibited the highest performance (area under the curve (AUC) of 0.93).
Conclusions:
This study has the potential to facilitate the improved screening of patients with coronary artery disease; we have developed a risk assessment system that is freely accessible to the public: https://prediction-of-coronary-heart-disease-htn-young-adults.streamlit.app/.
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