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Developing a Stroke Risk Prediction Model Using Cardiovascular Risk Factors: The Suita Study
Ahmed Arafa1,2,3, Yoshihiro Kokubo1, Haytham A Sheerah1,2
1Department of Preventive Cardiology, National Cerebral and Cardiovascular Center, Suita, Japan.
Insights
A new stroke risk model was developed for urban Japanese adults using cardiovascular factors. This model accurately predicts stroke incidence, aiding in early detection and prevention strategies for high-risk individuals.
Area of Science:
- Cardiovascular epidemiology
- Public health research
- Preventive medicine
Background:
- Stroke is a leading cause of death and disability globally and in Japan.
- Early detection of high-risk individuals is crucial for implementing preventive measures.
- Existing stroke risk prediction models may not be optimized for the urban Japanese population.
Purpose of the Study:
- To develop and validate a stroke risk prediction model tailored for the urban Japanese population.
- To identify key cardiovascular risk factors contributing to stroke incidence in this demographic.
- To provide a tool for assessing individual stroke risk within the study cohort.
Main Methods:
- A cohort of 6,641 participants (aged 30-79) without prior stroke or coronary heart disease was followed.
- The Cox proportional hazard model was employed to estimate stroke incidence risk.
- Model performance was evaluated using receiver operating characteristic (ROC) curves and Hosmer-Lemeshow statistics.
- Internal validation was performed using derivation and validation samples.
Main Results:
- A total of 372 strokes occurred during a median follow-up of 17.1 years.
- The developed risk model, incorporating age, smoking, blood pressure, fasting glucose, diabetes, chronic kidney disease, and atrial fibrillation, achieved an area under the curve (AUC) of 0.76.
- The model demonstrated good internal validity with a non-significant p-value for the goodness-of-fit test in both derivation (p=0.21) and validation (p=0.64) samples.
- Stroke incidence increased progressively with higher risk scores, ranging from 1.1% to 18.6%.
Conclusions:
- A novel, internally validated stroke risk prediction model was successfully developed for the urban Japanese population.
- The model effectively utilizes common cardiovascular risk factors to predict stroke incidence.
- Further research is needed to assess the clinical utility and practical application of this risk model in broader public health settings.
Introduction:
Stroke remains a major cause of death and disability in Japan and worldwide. Detecting individuals at high risk for stroke to apply preventive approaches is recommended. This study aimed to develop a stroke risk prediction model among urban Japanese using cardiovascular risk factors.
Methods:
We followed 6,641 participants aged 30-79 years with neither a history of stroke nor coronary heart disease. The Cox proportional hazard model estimated the risk of stroke incidence adjusted for potential confounders at the baseline survey. The model's performance was assessed using the receiver operating characteristic curve and the Hosmer-Lemeshow statistics. The internal validity of the risk model was tested using derivation and validation samples. Regression coefficients were used for score calculation.
Results:
During a median follow-up duration of 17.1 years, 372 participants developed stroke. A risk model including older age, current smoking, increased blood pressure, impaired fasting blood glucose and diabetes, chronic kidney disease, and atrial fibrillation predicted stroke incidence with an area under the curve = 0.76 and p value of the goodness of fit = 0.21. This risk model was shown to be internally valid (p value of the goodness of fit in the validation sample = 0.64). On a risk score from 0 to 26, the incidence of stroke for the categories 0-5, 6-7, 8-9, 10-11, 12-13, 14-15, and 16-26 was 1.1%, 2.1%, 5.4%, 8.2%, 9.0%, 13.5%, and 18.6%, respectively.
Conclusion:
We developed a new stroke risk model for the urban general population in Japan. Further research to determine the clinical practicality of this model is required.
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