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[The Risk of Developing Ischemic Stroke in Patients After Exacerbation of Ischemic Heart Disease]
V A Brazhnik1, L O Minushkina2, N R Khasanov3
1City clinical hospital №51 of State healthcare agency Moscow, Central State Medical Academy of Department of Presidential Affairs, Moscow.
Insights
This study developed a new clinical scale to predict stroke risk in acute coronary syndrome patients. The model offers improved accuracy in identifying high-risk individuals compared to existing methods.
Area of Science:
- Cardiology
- Neurology
- Public Health
Background:
- Acute coronary syndrome (ACS) exacerbations increase stroke risk in patients with ischemic heart disease.
- Accurate risk stratification is crucial for timely intervention and improved patient outcomes.
- Existing prognostic models may not fully capture stroke risk in this specific patient population.
Purpose of the Study:
- To develop and validate a novel clinical model for assessing stroke risk in patients post-ACS.
- To identify key clinical factors associated with stroke occurrence following ACS hospitalization.
- To compare the predictive performance of the new model against established risk scores.
Main Methods:
- A cohort of 1803 ACS patients from four Russian institutions was studied.
- Patients were followed for one year post-discharge to record stroke events.
- Regression analysis was used to develop the prognostic model; external validation was performed using the RECORD-3 study cohort.
Main Results:
- Identified risk factors for stroke include atrial fibrillation, diabetes mellitus, and chronic heart failure.
- Protective factors identified were high-density lipoprotein cholesterol >1 mmol/l, percutaneous coronary intervention, anticoagulant treatment, and achieving blood pressure goals.
- The developed model demonstrated good predictive value (AUC 0.780), outperforming GRACE (AUC 0.692) and CHA2DS2-VASc (AUC 0.708) scales.
Conclusions:
- A simple clinical scale was developed for more precise identification of stroke risk in ACS patients.
- The new model shows superior predictive accuracy compared to standard risk assessment tools.
- This scale can aid clinicians in stratifying patients and tailoring preventive strategies.
Abstract:
Aim To develop a model for evaluating the risk of stroke in patients after exacerbation of ischemic heart disease who were admitted to the hospitals included into a vascular program.Materials and methods This study included 1803 patients with acute coronary syndrome (ACS) from four institutions of Moscow, Kazan, Astrakhan, and Krasnodar where the vascular program was established. Mean age of patients was 64.9±12.78 years, 62,1 % of them were men. The patients were followed up for one year after the discharge from the hospital. External validation of the developed prognostic model was performed on a cohort of patients with ACS included into the RECORD-3 study.Results During the follow-up period, 42 cases of ischemic stroke were observed. The risk of ischemic stroke was associated with the presence of atrial fibrillation (odd ratio (OR) 2.640; р=0.037), diabetes mellitus (OR 2.718; р=0.041), and chronic heart failure (OR 7.049; р=0.011). Protective factors were high-density lipoprotein cholesterol >1 mmol/l (OR 0.629; р=0.041), percutaneous coronary intervention during an index hospitalization (OR 0.412; р=0.042), anticoagulant treatment (OR 0.670; р=0.049), and achieving the blood pressure goal (OR 0.604; р=0.023). The prognostic model developed on the basis of regression analysis showed a good predictive value (area under the ROC curve, 0.780), sensitivity of 80 %, and specificity of 64.6 %. The diagnostic value of other scales for risk assessment was somewhat lower. The area under the ROC curve was 0.692±0.0245 for the GRACE scale and 0.708±0.0334 for CHA2DS2‑VASc. In the external validation of the scale based on data of the RECORD-3 study, the diagnostic value was lower although satisfactory as well (area under the ROC curve, 0.651); sensitivity was 78.9 %, and specificity was 52.3 %.Conclusion The study resulted in development of a simple clinical scale, which will probably allow identifying groups at risk of stroke more precisely than with standard scales.
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