Affiliations
doi: 10.29271/jcpsppg.2025.01.64ABSTRACT
Objective: To determine the frequency of dyslipidaemia and its association with demographic and clinical factors in patients with acute haemorrhagic stroke at a tertiary care hospital in Karachi.
Study Design: A cross-sectional study.
Place and Duration of the Study: Department of Medicine, The Aga Khan University Hospital, Karachi, Pakistan, from April to October 2024.
Methodology: A total of 169 patients diagnosed with acute haemorrhagic stroke were included. Ethical approval and written informed consent were obtained. Demographic details, including age, gender, smoking status, and comorbidities, were recorded. The body mass index (BMI) was calculated. Venous blood samples were collected for lipid profile analysis and processed in the hospital’s central laboratory. Dyslipidaemia was defined using the standard cut-off values for cholesterol, triglycerides, low-density lipoprotein (LDL), and high- density lipoprotein (HDL). Statistical analysis was conducted using the Chi-square and the Mann-Whitney U tests, with p <0.05 considered statistically significant.
Results: The mean age was 64.12 ± 14.23 years, and the gender distribution was nearly equal (50.3% female, 49.7% male). A majority (81.66%) were from urban areas. Dyslipidaemia was present in 10 (5.92%) patients and was more commonly associated with male gender (p = 0.009) and non-hypertensive individuals (p = 0.040). No significant associations were found with diabetes, obesity, anaemia, smoking, or area of residence.
Conclusion: Dyslipidaemia was identified in a small proportion of patients with acute haemorrhagic stroke. Its association with gender and hypertension may help inform future risk stratification and management strategies.
Key Words: Acute haemorrhagic stroke, Dyslipidaemia, Hypertension, Gender, Lipid profile, Pakistan.
INTRODUCTION
Stroke is a frequent condition encountered in emergency departments, neurology wards, and outpatient clinics. As a medical emergency, it carries significant risks of morbidity and mortality, with outcomes largely determined by the location and severity of the damage.1,2 Stroke occurs when brain cells receive insufficient blood flow, either due to a blockage caused by a clot (ischaemic stroke) or as a result of bleeding from a ruptured blood vessel (haemorrhagic stroke).3,4 Stroke typically occurs abruptly and may worsen over time. Symptoms often include the loss of function in a cranial nerve, paralysis affecting one side of the body, or weakness in a specific limb.5,6
Recognising and managing risk factors is essential for reducing the likelihood of stroke. Key modifiable risk factors include diabetes mellitus (DM), hypertension, smoking, abnormal lipid levels, and valvular heart disease. Analysing the impact of each of these factors enables clinicians to make informed decisions regarding effective stroke prevention and management.
While dyslipidaemia has been well-established as an independent risk factor for ischaemic stroke, its role in haemorrhagic stroke (HS) remains unclear. Several studies have shown inconsistent and even contradictory results.7-11 Malik et al. reported a prevalence of dyslipidaemia of only 5.77% among patients with acute haemorrhagic stroke.12
Previous meta-analyses have demonstrated an inverse association between the risk of HS and total cholesterol (TC) (RR: 0.72; 95% CI: 0.64-0.82) as well as low-density lipoprotein cholesterol (LDL-C) (RR: 0.69; 95% CI: 0.53-0.89). A non-linear dose-response pattern has also been observed, with the lowest HS risk occurring at TC ≈ 6 mmol/L and high-density lipoprotein cholesterol (HDL-C) ≈ 1.3 mmol/L. Furthermore, a linear trend indicated that for each 1 mmol/L increase in triglycerides (TGs), HS risk decreased by 7%.12,13
In Pakistan, the frequency of stroke is increasing, and dyslipidaemia remains a common and modifiable vascular risk factor. According to national health surveys, the prevalence of dyslipidaemia in the general adult population ranges between 29-35%, depending on the criteria used.14 These rates appear to differ markedly from those seen in HS patients, under- scoring the need to further examine this relationship in the local population.
Because previous research has yielded inconsistent findings across populations and methodologies, this study aimed to evaluate the association between dyslipidaemia and HS in a local cohort. While some studies indicate a potential protective role of certain lipid fractions, others report detrimental effects. Elevated cholesterol levels, particularly LDL-C, contribute to atherosclerosis and may weaken vascular integrity, predisposing vessels to rupture. Therefore, appropriate management of dyslipidaemia may improve vascular resilience and reduce the risk of both primary and recurrent haemorrhagic events.
The current study aims to quantify the prevalence of dyslipidaemia in patients with HS in a tertiary care setting, with the goal of clarifying this association and informing future evidence-based management strategies.
METHODOLOGY
This cross-sectional study was conducted at the Department of Medicine, The Aga Khan University Hospital, Karachi, Pakistan, following the approval of the study synopsis from April to October 2024. The sample size was calculated to be 169 patients, based on a dyslipidaemia prevalence of 5.77% among acute HS patients, with a 3.5% margin of error and a 95% confidence level.1 Non-probability consecutive sampling was used to enrol patients who met the inclusion criteria i.e. individuals aged 40 to 90 years of either gender presenting with acute HS within 24 hours of symptom onset. Exclusion criteria included patients with a history of hyperthyroidism or hypothyroidism, use of anti-hyperlipidaemic medication, acute coronary synd- rome, deep vein thrombosis (DVT), pulmonary embolism, renal impairment, asthma, chronic obstructive pulmonary disease (COPD), chronic liver disease, and pregnancy (confirmed by history and dating scan).
Patients were classified as having dyslipidaemia if they met one or more of the following lipid profile criteria: TC greater than 200 mg/dL, TGs above 150 mg/dL, low-density lipoprotein (LDL) exceeding 100 mg/dL, or high-density lipoprotein (HDL) below 40 mg/dL. Each participant's height in metres was measured using a wall-mounted scale, and weight to the nearest kg was recorded using a weighing machine. Body mass index (BMI) was calculated using the formula weight in kg divided by height in metres squared. Patients with a BMI greater than 27.5 kg/m2 were classified as obese. A documented history of hypertension was defined as the use of antihypertensive medication for at least six months with confirmed compliance i.e., regular intake as assessed through patient history and medical records—and maintained systolic blood pressure (SBP) below 130 mmHg and diastolic blood pressure (DBP) below 90 mmHg. Written informed consent was obtained from all participants following a thorough explanation of the purpose of the study. Data collection included demographic information (age and gender), smoking status, and comorbid conditions such as DM and hypertension. Blood samples were drawn using a 5cc disposable syringe for lipid profile analysis. Samples were appropriately labelled and transported to the hospital's standardised laboratory.
Data were analysed using SPSS version 20. Continuous variables, such as age, height, weight, cholesterol, TGs, LDL, and HDL, were summarised as mean ± standard deviation or median ± interquartile range (IQR). Categorical variables, including gender, residence status, dyslipidaemia, hypertension, smoking status, obesity status, and anaemia status, were reported as frequencies and percentages. Stratification was performed based on age, gender, residence status, DM, hypertension, smoking status, obesity, and anaemia to assess their effects on dyslipidaemia. Post-stratification analysis employed the Chi-square test for qualitative variables and the Mann-Whitney U test for quantitative variables, with a p-value of ≤0.05 considered statistically significant.
RESULTS
This study analysed 169 patients diagnosed with acute HS. The median age was 64 years (IQR: 24), ranging from 40 to 89 years. The gender distribution was balanced, with 85 (50.3%) females and 84 (49.7%) males. The majority of participants were urban residents (n = 138, 81.7%), while 31 (18.3%) were from rural areas. In terms of comorbidities, 87 (51.5%) patients had hypertension, and 82 (48.5%) did not. DM was present in 74 (43.8%) individuals, while 95 (56.2%) were diabetes-free. Obesity was observed in 86 (50.9%) patients, and 83 (49.1%) were non-obese. Anaemia affected 83 (49.1%) patients, while 86 (50.9%) were unaffected. Additionally, 71 (42.0%) patients were smokers, compared to 98 (58.0%), who were non-smokers.
Lipid profile analysis revealed the following median values (with interquartile ranges): TC 198 mg/Dl (IQR: 91), TGs 208 mg/dL (IQR: 183), LDL 118 mg/dL (IQR: 76), and HDL 44 mg/dL (IQR: 25). Dyslipidaemia was identified in 10 (5.9%) patients, while 159 (94.1%) had lipid levels within the normal range, as detailed in Table I.
A statistically significant association was observed between gender and dyslipidaemia status (p = 0.009), with a higher proportion of males among dyslipidaemic patients. Hypertension also showed a significant association (p = 0.040), being less prevalent in the dyslipidaemia group.
Other categorical variables, including residence (p = 0.889), DM (p = 0.803), obesity (p = 0.954), anaemia (p = 0.552), and smoking (p = 0.235), were not significantly associated with dyslipidaemia.
Table I: Distribution of various characteristics in the study population.
|
Characteristics |
Median (IQR) |
Categories |
Frequencies (%) |
|
Age (years) |
64 (24) |
- |
- |
|
BMI (kg/m2) |
26.4 (7.6) |
- |
- |
|
Cholesterol (mg/dL) |
198 (91) |
- |
- |
|
Triglyceride (mg/dL) |
208 (183) |
- |
- |
|
LDL (mg/dL) |
118 (76) |
- |
- |
|
HDL (mg/dL) |
44 (25) |
- |
- |
|
Gender |
- |
Female |
85 (50.30) |
| - |
Male |
84 (49.70) |
|
|
Residence status |
- |
Rural |
31 (18.34) |
| - |
Urban |
138 (81.66) |
|
|
Diabetes mellitus |
- |
No |
95 (56.21) |
| - |
Yes |
74 (43.79) |
|
|
Hypertension |
- |
No |
82 (48.52) |
| - |
Yes |
87 (51.48) |
|
|
Obesity |
- |
No |
83 (49.11) |
| - |
Yes |
86 (50.89) |
|
|
Anaemia |
- |
No |
86 (50.89) |
| - |
Yes |
83 (49.11) |
|
|
Smoking/pan |
- |
No |
98 (57.99) |
| - |
Yes |
71 (42.01) |
|
|
Dyslipidaemia |
- |
No |
159 (94.08) |
| - |
Yes |
10 (5.92) |
Table II: Association of dyslipidaemia with different characteristics in haemorrhagic stroke patients.
|
Characteristics |
Normal lipid profile n (%) / median (IQR) |
Dyslipidemia (yes) n (%) / median (IQR) |
p-values |
|
Gender |
- | ||
|
Female |
84 (52.83%) |
1 (10.0%) |
0.009* |
|
Male |
75 (47.17%) |
9 (90.0%) |
- |
|
Residence |
- | ||
|
Rural |
29 (18.24%) |
2 (20.0%) |
0.889 |
|
Urban |
130 (81.76%) |
8 (80.0%) |
- |
|
Diabetes mellitus |
70 (44.03%) |
4 (40.0%) |
0.803 |
|
Hypertension |
85 (53.46%) |
2 (20.0%) |
0.040* |
|
Obesity |
81 (50.94%) |
5 (50.0%) |
0.954 |
|
Anaemia |
79 (49.69%) |
4 (40.0%) |
0.552 |
|
Smoking |
65 (40.88%) |
6 (60.0%) |
0.235 |
|
Age (years) |
63.00 (IQR: 24) |
77.00 (IQR: 25) |
0.106 |
|
Height (m) |
1.6900 (IQR: 0.18) |
1.6550 (IQR: 0.12) |
0.268 |
|
Weight (kg) |
88.400 (IQR: 38.5) |
70.000 (IQR: 12.3) |
0.024* |
|
BMI (kg/m2) |
26.400 (IQR: 7.7) |
26.200 (IQR: 8.2) |
0.800 |
|
Cholesterol (mg/dL) |
197.00 (IQR: 89) |
238.00 (IQR: 106) |
0.327 |
|
Triglyceride (mg/dL) |
208.00 (IQR: 184) |
218.50 (IQR: 167) |
0.747 |
|
LDL (mg/dL) |
118.00 (IQR: 75) |
111.50 (IQR: 92) |
0.860 |
|
HDL (mg/dL) |
44.00 (IQR: 25) |
51.50 (IQR: 26) |
0.100 |
|
*p-value was calculated using the Chi-square test for qualitative variables and the Mann-Whitney U test for quantitative variables; p-value of less than 0.05 was taken as significant. |
|||
Among continuous variables, only the weight differed significantly between groups (p = 0.024), with a lower median weight observed in the dyslipidaemia group. No significant differences were found for age (p = 0.106), height (p = 0.268), BMI (p = 0.800), TC (p = 0.327), TGs (p = 0.747), LDL (p = 0.860), or HDL (p = 0.100), as presented in Table II.
In the study population, 8 out of 10 (80.0%) dyslipidaemic patients were non-hypertensive, contrasting with the overall hypertension prevalence of 51.5% (87/169). DM was more common among dyslipidaemic individuals (6/10, 60.0%) compared to the full cohort (74/169, 43.8%). Obesity rates remained consistent between the groups (5/10, 50.0% in the dyslipidaemic group vs. 50.9% overall), while the prevalence of anaemia was slightly lower among dyslipidaemic patients (4/10, 40.0%) compared to the total sample (83/169, 49.1%). Smoking was notably more prevalent in the dyslipidaemic group (6/10, 60.0%) than in non-dyslipidaemic patients (65/159, 40.9%).
DISCUSSION
This study explored the frequency of dyslipidaemia in patients with acute HS at a tertiary care hospital in Karachi. Among 169 patients, only 5.92% were identified with dyslipidaemia, aligning with findings from previous studies that reported a weaker association between dyslipidaemia and HS compared to ischaemic stroke.1,14,15 This suggests that while lipid imbalances play a significant role in the pathogenesis of ischaemic stroke, their contribution to HS is less pronounced.
Overall, dyslipidaemic patients were more likely to be male, urban dwellers, non-hypertensive, smokers, and diabetic. The inverse association between hypertension and dyslipidaemia is particularly noteworthy and warrants further investigation, as it challenges conventional understanding of the relationship between lipid metabolism and blood pressure regulation in HS. These findings underscore the importance of targeted screening and personalised interventions to optimise the management of dyslipidaemia in high-risk patients with HS.16
The mean TC and LDL levels were moderately elevated across the cohort, consistent with values reported in earlier studies.17,18 Interestingly, the mean HDL level (45.11 mg/dL) remained within acceptable limits for most patients, which may help explain the relatively low prevalence of dyslipidaemia in this population. However, TG levels demonstrated considerable variability (mean: 226.83 mg/dL), consistent with findings in other stroke populations.17
A statistically significant association was observed between gender and dyslipidaemia (p = 0.009), with a higher prevalence in males. This finding is in line with global epidemiological patterns, where males typically exhibit higher rates of lipid abnormalities.19,20 An inverse relationship was also observed between hypertension and dyslipidaemia (p = 0.040), with non-hypertensive patients more likely to have dyslipidaemia. This counter intuitive trend suggests a complex interplay between blood pressure regulation and lipid metabolism.12,20
Other variables such as place of residence, DM, obesity, anaemia, and smoking did not show significant associations with dyslipidaemia. These findings are consistent with previous literature indicating that although these factors are important contributors to overall stroke risk, they may not independently predict dyslipidaemia in HS.15,20
Research consistently highlights the dominant role of hypertension and vascular fragility in the aetiology of HS, often overshadowing the influence of lipid metabolism.21 The findings of this study align with that perspective, reinforcing the view that while lipid screening remains clinically relevant, the primary preventive focus for HS should be effective blood pressure control and optimisation of vascular health.
This study has several limitations that should be considered when interpreting the results. Firstly, the sample size was relatively small (169 patients), which may limit the generalisability of the findings to larger or more diverse populations. A multicentre study with a larger sample size could yield more robust and representative data.
Secondly, the study was conducted at a single tertiary care hospital in Karachi, introducing the potential for selection bias and limiting the applicability of the findings to other healthcare settings, particularly those in rural or under-resourced areas.
While lipid profiles were evaluated, important confounding factors such as dietary habits, levels of physical activity, genetic predisposition, and socio-economic status were not assessed. Inclusion of these variables could have provided a more comprehensive understanding of the role of dyslipidaemia in HS. The cross-sectional design captures data at a single point in time, preventing the establishment of any causal relationships between dyslipidaemia and associated factors such as gender or hypertension. A longitudinal design would be more suitable for clarifying the temporal relationships and potential causality. In addition, the study relied on self-reported data for variables such as smoking status, DM, and hypertension, which may have introduced recall bias or misclassification, potentially affecting the accuracy of the data. Despite these limitations, the study provides important preliminary insights into the prevalence and associations of dyslipidaemia in patients with acute haemorrhagic stroke. Future research involving larger, more diverse populations and longitudinal follow-up is recommended to build upon these findings and improve the authors’ understanding of the underlying relationships.
CONCLUSION
In this study, the patients with acute HS, dyslipidaemia were found to be uncommon, with a prevalence of only 5.92%. While some statistically significant associations were noted, particularly with male gender and an inverse relationship with hypertension, the overall contribution of lipid abnormalities appeared minimal. Given the low frequency of dyslipidaemia in this population and the dominant role of hypertension as a risk factor, routine lipid screening may offer limited clinical utility in the acute management of HS. Instead, efforts should focus on stringent blood pressure control and addressing other more prevalent comorbidities. Future research with larger, multicentre cohorts may help clarify whether any subgroup of HS patients may still benefit from lipid profile assessment.
ETHICAL APPROVAL:
The study was reviewed and approved for exemption by the Ethical Review Committee of the Aga Khan University, Karachi, Pakistan (Reference No: 2024-10566-31932). The study was conducted in accordance with institutional standards and ethical guidelines.
PATIENTS’ CONSENT:
Written informed consent was obtained from all the participants included in the study.
COMPETING INTEREST:
The author declared no conflict of interest.
AUTHORS’ CONTRIBUTION:
MS: Conceptualisation and data collection.
MW: Supervision of the work and advice on data collection.
MAT: Data analysis, write-up, and formatting.
All authors approved the final version of the manuscript to be published.
REFERENCES