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Risk analysis of carotid stent from a population-based database in Taiwan
Chun-An Cheng1, Wu-Chien Chien, Chien-Yeh Hsu
1Graduate Institute of Biomedical Informatics, Taipei Medical University Department of Neurology, Tri-Service General Hospital, National Defense Medical Center Department of Medical Research, Tri-Service General Hospital, National Defense Medical Center School of Public Health, National Defense Medical Center Department of Information Management, National Taipei University of Nursing and Health Sciences, Taipei, Taiwan, ROC.
Insights
This study developed a nomogram to predict individual risks of major adverse cardiovascular events after carotid artery stenting (CAS). The tool helps clinicians and patients assess risks, guiding treatment decisions for stroke prevention.
Area of Science:
- Cardiovascular Medicine
- Medical Informatics
- Public Health
Background:
- Stroke is a leading cause of mortality globally, making prevention crucial.
- Carotid artery stenting (CAS) offers less invasive treatment for advanced carotid stenosis but carries post-procedure risks.
- Patients and families often lack information regarding CAS risks, causing anxiety.
Purpose of the Study:
- To develop a predictive model for individualizing the risk of major adverse cardiovascular events (MACE) after CAS.
- To create a user-friendly nomogram to aid clinical decision-making and patient communication.
- To identify key risk factors associated with post-CAS MACE.
Main Methods:
- Utilized a multivariable Cox proportional hazard regression model with forward stepwise selection.
- Constructed a nomogram based on the Cox model using data from Taiwan's National Health Insurance database and a validation dataset.
- Excluded patients under 18 years of age.
Main Results:
- Identified significant risk factors: older age, congestive heart failure, malignant disease, diabetes mellitus, and symptomatic status.
- The model demonstrated good discrimination in derivation data (concordance index 0.681) and acceptable performance in external validation (concordance index 0.66).
- Developed a visual nomogram for easy clinical application and communication.
Conclusions:
- The developed nomogram provides valuable prognostic information for patients undergoing CAS.
- The tool can facilitate informed discussions between clinicians and patients, potentially reducing pre-procedural anxiety.
- Older patients with multiple comorbidities may benefit from considering alternative medical therapy due to higher risks.
Abstract:
Because stroke is the third leading disease that causes mortality in the world, the prevention of stroke from advanced carotid stenosis is an important issue. The carotid stent (CAS) is a less invasive to treat advanced carotid stenosis, but for high-risk patients it may cause some events after the procedure that reduces the benefit of stroke prevention. Because patients and their families have less information about risk of events after CAS and are easy concerned, this study calculates the individual probability of major adverse cardiovascular events including any stroke, myocardial infarction, or death after procedure.The analyzed dataset was composed of patients undergoing CAS from the longitudinal National Health Insurance claim database in Taiwan. The validation dataset was composed of patients undergoing CAS from the Tri-Service General Hospital. We excluded patients under 18 years of age. The prediction model was constructed with a multivariable Cox proportional hazard regression and performed with forward stepwise selection. The nomogram construction was based on the multivariable Cox model.The risk factors were determined as follows: age with a hazard ratio (HR) of 1.027 (95% confidence interval [CI]: 1.002-1.053) for every 1 year older, congestive heart failure with a HR of 2.196 (95% CI: 1.368-3.524), malignant disease with a HR of 1.724 (95% CI: 1.009-2.944), diabetes mellitus with a HR of 1.722 (95% CI: 1.109-2.674), and symptomatic status with a HR of 1.604 (95% CI: 1.027-2.507). The model showed good discrimination with a P < 0.001 (concordance index, 0.681; bootstrap corrected, 0.661) in the derivation data. The concordance index of external validation was 0.66 (P = 0.048), which indicates acceptable performance.We developed a nomogram with a visual scale method and prognostic information, and it is easy to use in clinical practice. The integer-base method may support communication between clinicians and patients before CAS to reduce the anxiety about making a treatment decision. However, insofar as older patients with multiple comorbidities are at high risk, the option of an alternative treatment strategy with medical therapy should be suggested. In the future, prospective tests should be performed to validate whether this model helps patients to prevent events.
