Prospective study of lipid profiles, infarct volume, CIMT, and outcomes in acute ischemic stroke
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background. Stroke remains one of the leading causes of mortality and long-term disability worldwide. Dyslipidemia significantly contributes to atherosclerotic cerebrovascular disease; however, the relationship between fasting lipid profiles and clinical parameters in acute stroke remains inadequately defined. Objectives. This study aimed to evaluate the association between fasting lipid profiles and clinical variables such as infarct volume, stroke severity, carotid intima-media thickness (CIMT), and 90-day functional outcomes in patients with acute ischemic stroke. Materials and methods. This prospective observational study was conducted over 18 months at a tertiary care center in India and included 100 patients presenting within 24 hours of their first-ever acute ischemic stroke. Fasting lipid profiles were obtained upon admission. Stroke severity was assessed using the National Institutes of Health Stroke Scale (NIHSS), and infarct volume was measured using MRI or CT imaging. CIMT was evaluated via carotid Doppler ultrasonography. Logistic regression analysis was performed to identify lipid parameters independently associated with stroke severity, infarct volume, CIMT, and functional outcomes. Results. Elevated levels of LDL cholesterol and triglycerides were significantly associated with larger infarct volumes and higher NIHSS scores. Dyslipidemia correlated with increased CIMT and was predictive of poorer functional outcomes at 90 days. Conclusion. Abnormal fasting lipid profiles were associated with greater stroke severity, larger infarct volumes, vascular changes, and worse functional recovery. These findings underscore the importance of early lipid assessment for prognostication and guiding secondary prevention strategies in acute ischemic stroke patients, particularly in the Indian context.
Source: Romanian Journal of Neurology
Institution: Saveetha University
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4414453989
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