Comparative Prognostic Value of CHA2DS2-VASc Score and Atherogenic Plasma Index for One-year Mortality Prediction in Ischemic Stroke Patients
Objective: The CHA₂DS₂-VASc (congestive heart failure, hypertension, age ≥75 years, diabetes mellitus, stroke, vascular disease, age, female gender) score is significantly associated with poor outcomes after ischemic stroke. However, the impact of lipid parameters on prognosis remains unclear. This study aimed to investigate the association between lipid parameters and outcomes, and compare them to the CHA₂DS₂-VASc score. Method: A total of 583 ischemic stroke patients admitted between 2018 and 2022 were retrospectively analyzed. Demographic data, CHA₂DS₂-VASc scores, and lipid parameters, including ratio of triglyceride to high density lipoprotein (HDL-C), light density lipoprotein (LDL-C) to HDL and atherogenic plasma index (API) were recorded. Patients were followed for one year, with all-cause mortality as the primary endpoint. Predictors of mortality were determined using Cox regression analysis. Results: The mean age of the 583 patients was 71.05±11.83 years, with a one-year all-cause mortality rate of 17.3% (n=101). Total cholesterol, non-HDL-C, and API were significantly higher in patients with poor outcomes (p=0.003, p=0.031, p=0.019, respectively). Both API and CHA₂DS₂-VASc scores were strong mortality predictors [hazard ratio (HR): 1.062, 95% confidence interval (CI): 0.973-1.252, p=0.007] and (HR: 1.567, 95% CI: 1.003-2.174, p=0.004), respectively. Receiver operating curve analysis revealed higher predictive power for CHA₂DS₂-VASc score compared to API (area under the curve: 0.756; p=0.014 vs. 0.568; p=0.045). Conclusion: CHA₂DS₂-VASc and API are valuable predictors of one-year mortality after ischemic stroke. CHA2DS2-VASc score, which includes embolism risk factors, has stronger sensitivity and specificity for predicting poor outcomes compared to lipid parameters.
Authors
- Doğaç Okşen (ORCID: https://orcid.org/0000-0003-4548-9543)
- Muzaffer Aslan (ORCID: https://orcid.org/0000-0003-0670-137X)
- Yunus Emre Yavuz (ORCID: https://orcid.org/0000-0002-9901-8141)
Publication Details
- Journal
- Bagcilar Medical Bulletin
- Published
- 2025-03-18
- DOI
- https://doi.org/10.4274/bmb.galenos.2025.57966
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 2.94