A cerebrovascular accident (CVA), also known as a stroke, is a medical condition where the blood supply to part of the brain is interrupted or reduced, depriving brain tissue of oxygen and nutrients. This leads to the death of brain cells within minutes, making Stroke a medical emergency that requires prompt treatment.^1,2 Stroke poses a significant global health burden, especially in low- and middle-income countries (LMICs), where 70% of cases occur. In India, rising life expectancy has increased the prevalence of age-related non-communicable diseases, making stroke the fourth leading cause of death and the fifth leading cause of disability.^3,4

Stroke is broadly classified into ischemic and hemorrhagic types, with causes including vascular blockage or rupture, influenced by risk factors like hypertension, diabetes, dyslipidemia, smoking, heart disease, and genetic or lifestyle factors.^5,6 Elevated serum uric acid levels are frequently observed in stroke patients and may reflect underlying oxidative stress or metabolic disturbances contributing to stroke pathogenesis. Higher levels have been associated with both ischemic and hemorrhagic strokes and may influence prognosis, highlighting the importance of uric acid monitoring in risk assessment and clinical management.^7-10

In stroke patients, lipid profile abnormalities—such as elevated LDL, total cholesterol, and triglycerides, along with reduced HDL—are common and significantly increase the risk of ischemic stroke by promoting atherosclerosis. These alterations are necessary for clinical assessment, and their management is essential for improving outcomes and preventing recurrent strokes.^11-14

Variations in stroke outcomes across observational studies may stem from the heterogeneity of stroke subtypes, as dyslipidemia may have limited influence on forms like lacunar or cardio-embolic strokes. In India, there is limited data on the role of serum uric acid and lipid profiles in acute ischemic stroke. Hence, this study aims to evaluate these biochemical parameters and their correlation with clinical outcomes in patients with acute ischemic stroke.

Study Design and Setting: This hospital-based observational cross-sectional study was conducted in the Department of General Medicine at GMERS Medical College and General Hospital, Himmatnagar. The study was conducted over twenty months, from October 2022 to May 2024.

 Study Participants: The study population included adult patients aged 18 years and above of either sex, diagnosed with ischemic cerebrovascular accident based on clinical and radiological evidence, specifically non-contrast computed tomography (NCCT) of the brain. Patients were enrolled purposively. Individuals with hemorrhagic stroke (including subarachnoid, subdural, extradural, and intracerebral haemorrhage), those taking medications known to elevate serum uric acid (e.g., loop diuretics, anti-cancer drugs like cyclophosphamide and cyclosporine, anti-tuberculosis therapy, aspirin, theophylline), patients with chronic renal insufficiency, inflammatory disorders, lymphoproliferative or myeloproliferative diseases, and those on steroid therapy were excluded. Patients who declined to give informed consent were also excluded.

Sample Size and Sampling Technique: The sample size was calculated using a hypothesis testing formula with a 95% confidence interval and a margin of error of 10% based on an estimated stroke prevalence of 0.3%. The minimum sample size computed was 81, and to account for possible non-responses, 90 patients were included. Participants were selected using a purposive sampling method.

Data Collection Tools and Procedure: Ethical approval was obtained from the Institutional Ethical Committee (IEC) before the commencement of the study. Data were collected using a predesigned and pretested structured proforma. This included sociodemographic details, clinical history, comorbid conditions, addiction history, anthropometric measurements, general and systemic examination findings, and laboratory investigations. Blood samples were obtained within 24 hours of hospital admission and analyzed for serum uric acid and lipid profile parameters.

Laboratory Investigations: Serum uric acid was measured using the Uricase-PAP method under standard laboratory protocols. Hyperuricemia was defined as serum uric acid ≥7 mg/dL in males and ≥6 mg/dL in females. The serum lipid profile, including total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), and triglycerides, were assessed colourimetrically. Abnormal values were defined as total cholesterol ≥200 mg/dL, LDL ≥150 mg/dL, HDL <40 mg/dL, and triglycerides ≥150 mg/dL.

Statistical Analysis: Data were entered and analyzed using Epi Info CDC version 7. Continuous variables were expressed as mean and standard deviation, while categorical variables were represented as proportions. The chi-square or Fisher's exact test was used to compare categorical variables. A p-value of <0.05 was considered statistically significant.

Table 1 revealed a predominantly elderly population (>50 years: 74.4%) with male predominance (57.8%), showing high rates of metabolic comorbidities, including hypertension (42.2%) and diabetes mellitus (38.9%), along with notable cardiovascular risk factors like ischemic heart disease (18.9%) and smoking (28.9%). The cohort demonstrated a relatively low prevalence of hypothyroidism (6.7%), prior stroke (6.7%), and substance use (alcohol: 20%; tobacco chewing: 12.2%), with favourable survival outcomes (mortality: 5.6%).

Table 1: Clinicosocial characteristics of study participants (n=90)

Table 2 revealed a high prevalence of dyslipidemia, with more than half showing abnormal total cholesterol (54.4%) and triglyceride levels (54.4%), along with elevated LDL cholesterol (52.2%). Notably, hyperuricemia was present in 37.8% of participants, while low HDL cholesterol - a potentially protective factor - was the least common abnormality (24.4%). These findings demonstrate a significant burden of atherogenic lipid abnormalities in this population, coupled with a substantial proportion showing elevated uric acid levels,

Table 2: Abnormal lipid profile and uric acid level among study participants (n=90)

Table 3: Association of Uric Acid with Clinical Variables

Table 3 showed that hypertension (OR=15.35, 95% CI:5.41-43.55, p<0.001), diabetes mellitus (OR=4.85, 95% CI:2.00-11.78, p<0.001), hypercholesterolemia (OR=6.00, 95% CI:2.25-16.02, p<0.001), elevated LDL (OR=3.44, 95% CI:1.38-8.59, p=0.008), and hypertriglyceridemia (OR=6.00, 95% CI:2.25-16.02, p<0.001) were significantly associated with high uric acid levels, while low HDL showed a borderline association (OR=2.51, 95% CI:0.94-6.84, p=0.07); no significant associations were found for age, sex, hypothyroidism, ischemic heart disease, smoking, or alcohol consumption (all p>0.05), suggesting that metabolic abnormalities rather than demographic or lifestyle factors are the primary correlates of hyperuricemia in this population.

Table 4: Relation of Uric Acid and Lipid Profile with Outcome Among Study Participants

Table 4 showed no significant differences in the prevalence of abnormal uric acid levels (60% vs 36.47%), elevated cholesterol (60% vs 54.12%), high LDL (60% vs 51.76%), low HDL (60% vs 77.65%), or high triglycerides (60% vs 54.12%) between deceased and surviving patients.  

A stroke (acute CVA) occurs when brain blood flow is suddenly blocked (ischemic) or ruptured (hemorrhagic), leading to rapid brain cell damage and symptoms like weakness, speech difficulties, or vision loss. Urgent treatment is vital to reduce disability. High uric acid levels may increase stroke risk, especially ischemic strokes, by worsening atherosclerosis, hypertension, and metabolic disorders. This study examines serum uric acid and lipid levels in ischemic stroke patients.

The present study found hyperuricemia in 37.8% of ischemic stroke patients, showing robust associations with metabolic comorbidities, including hypertension (OR=15.35) and diabetes (OR=4.85). These findings align with previous studies, including those by Sekhar AR16 and Patil T et al.,17 demonstrating consistent links between elevated uric acid and vascular risk factors. However, unlike some prior research, we found no significant associations with age or gender, contrasting with Shah H et al.,18 who reported age-related increases and Arora T et al.,19 who noted gender differences in uric acid levels. These discrepancies may reflect variations in study populations, sample sizes, or measurement protocols, suggesting that while hyperuricemia relates to metabolic syndrome components, its relationship with demographic factors may be more population-dependent.

Regarding clinical outcomes, our study showed a non-significant trend toward higher uric acid in non-survivors (60% vs 36.47%, p=0.29), which parallels but was less pronounced than findings by Patil T et al.17 and Behra BK et al.20 who reported statistically significant associations. This difference may stem from our smaller number of mortality events (n=5) or variations in follow-up duration. The consistent association between hyperuricemia and poor metabolic profiles across studies nevertheless suggests potential value in monitoring uric acid as part of comprehensive stroke risk assessment. However, its independent prognostic significance requires further investigation in larger, prospective cohorts with standardized measurement protocols.

The present study found a high prevalence of dyslipidemia among ischemic stroke patients, with abnormal total cholesterol (54.4%), elevated LDL (52.2%), and high triglycerides (54.4%) being ubiquitous. These findings align with Nirmala AC et al.,21 who similarly reported elevated LDL as the most frequent lipid abnormality in stroke patients. The strong association between dyslipidemia and hyperuricemia in our cohort (OR=3.44-6.00, p≤0.008) suggests shared metabolic pathways, consistent with Sekhar AR's16 demonstration of significant links between uric acid and lipid abnormalities. However, unlike Garg A et al.,22 who found substantial associations between hyperuricemia and low HDL (p=0.04), our study showed only borderline significance for HDL (p=0.07), possibly due to differences in population characteristics or laboratory methods.

Regarding outcomes, our study found no significant association between lipid abnormalities and mortality (p>0.36), contrasting with some previous research suggesting atherogenic dyslipidemia may worsen stroke prognosis. This discrepancy may reflect our limited mortality events (n=5) or differences in lipid parameter thresholds across studies. Nevertheless, the consistent finding of frequent dyslipidemia in stroke patients across multiple studies, including ours, underscores the importance of lipid profile evaluation in secondary stroke prevention. However, its exact prognostic value requires further investigation in larger cohorts with standardized follow-up protocols.

In conclusion, this study highlights the significant burden of metabolic risk factors, including hypertension, diabetes, and dyslipidemia, among ischemic stroke patients, with a notable prevalence of hyperuricemia (37.8%) demonstrating strong associations with these comorbidities. While age and gender distributions aligned with established stroke epidemiology patterns, uric acid levels showed no significant correlation with age, gender, or short-term mortality outcomes in our cohort. The high prevalence of atherogenic dyslipidemia (abnormal LDL in 52.2%, triglycerides in 54.4%) and its strong association with elevated uric acid levels suggest shared metabolic pathways that may contribute to stroke pathogenesis. These findings underscore the importance of comprehensive metabolic evaluation in stroke patients. However, further research with larger cohorts is needed to clarify the prognostic significance of uric acid in stroke outcomes and its potential role as a therapeutic target for risk modification.

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