Hypertension, or high blood pressure, is one of the most significant modifiable risk factors for stroke, contributing to approximately 54% of all strokes worldwide. ^[1] Stroke remains a leading cause of mortality and long-term disability, with significant economic and social burdens. ^[2] Antihypertensive medications are proven to reduce blood pressure and, consequently, the risk of stroke. ^[3] However, the effectiveness of these medications is highly dependent on patient compliance. ^[4]

Compliance, or adherence, to antihypertensive therapy refers to the extent to which patients take their medications as prescribed. Poor compliance is a widespread issue, with studies estimating that up to 50% of hypertensive patients do not adhere to their prescribed regimens. ^[5] This non-adherence can lead to uncontrolled blood pressure, increasing the risk of cardiovascular events, including stroke. ^[6]

The relationship between stroke and compliance with antihypertensive medication is complex and influenced by various factors, including socioeconomic status, medication side effects, and patient education. ^[7] Understanding this relationship is crucial for developing targeted interventions to improve adherence and reduce stroke incidence. ^[8]

This study aims to investigate the association between compliance with antihypertensive medication and the incidence of stroke in a cohort of 90 hypertensive patients. By analyzing compliance rates and stroke outcomes, we seek to identify risk factors and inform strategies for improving adherence. ^[9]

This study was a prospective cohort study conducted over a period of two years to evaluate the relationship between compliance with antihypertensive medication and the incidence of stroke among hypertensive patients. The study design was chosen to allow for the observation of temporal relationships between medication adherence and stroke outcomes. The study population consisted of 90 hypertensive patients recruited from outpatient clinics at a tertiary care hospital.  Patients were included if they met the following criteria:

Inclusion Criteria:

1. Diagnosis of primary hypertension (based on clinical guidelines).
2. Age ≥40 years.
3. Prescribed at least one antihypertensive medication.
4. No prior history of stroke or transient ischemic attack (TIA).
5. Willingness to provide informed consent and participate in follow-up visits.

Exclusion Criteria:

1. Secondary hypertension (e.g., due to renal disease, endocrine disorders, or medication-induced hypertension).
2. Severe comorbidities that could limit life expectancy or interfere with adherence (e.g., advanced cancer, end-stage renal disease).
3. Inability to provide informed consent due to cognitive impairment or language barriers.
4. Patients with a history of non-adherence to medical advice or treatment.

Data Collection

Baseline Data: Demographic information (age, sex, socioeconomic status), clinical characteristics (blood pressure, comorbidities, medication regimen), and lifestyle factors (smoking, alcohol use, physical activity) were collected at enrollment.

Compliance Measurement: Compliance was assessed using the Medication Possession Ratio (MPR), calculated as the proportion of days covered by medication supply over the study period. Patients with an MPR ≥80% were classified as compliant, while those with an MPR <80% were classified as non-compliant.

Stroke Incidence: Stroke events were confirmed through medical records, imaging studies (CT or MRI), and clinical evaluation by a neurologist. Stroke severity was classified as mild, moderate, or severe based on the National Institutes of Health Stroke Scale (NIHSS).

Follow-Up: Patients were followed for two years with quarterly visits to assess compliance, blood pressure control, and adverse events. Missed visits were followed up via phone calls or home visits to minimize loss to follow-up.

Statistical Analysis

Baseline characteristics were summarized using means and standard deviations for continuous variables and frequencies and percentages for categorical variables. Differences between compliant and non-compliant groups were assessed using chi-square tests for categorical variables and t-tests for continuous variables. Logistic regression was used to identify predictors of stroke, with non-compliance as the primary independent variable. Covariates included age, sex, socioeconomic status, comorbidities, and baseline blood pressure. The association between compliance and stroke severity was analyzed using ordinal logistic regression. Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to account for potential confounders.

Tale 1: Baseline Characteristics of the Study Population

In table 1, the study population consisted of 90 hypertensive patients, compared to non-compliant patients, compliant individuals were slightly younger (57.3 vs. 60.1 years) with lower systolic (142.3 vs. 152.4 mmHg) and diastolic blood

pressures (86.2 vs. 92.5 mmHg), had fewer comorbidities (40.0% vs. 56.7%), and were less likely to have low socioeconomic status (25.0% vs. 50.0%), while the gender distribution was relatively similar.

Table 2: Compliance Rates by Demographic Factors

In table 2, among the 90 individuals, while there were no significant differences in age (≥60 years: 58.3% vs. 66.7%), male gender (55.0% vs. 46.7%), or comorbidities (40.0% vs. 56.7%), those with low socioeconomic status were significantly more likely to be non-compliant (50.0% vs. 25.0%, p=0.01).

Table 3: Stroke Incidence in Compliant vs. Non-Compliant Patients

In table 3, Non-compliant patients had a significantly higher stroke incidence (40.0%) compared to compliant patients (10.0%).

Table 4: Risk Factors for Stroke in Non-Compliant Patients

In table 4, Non-compliance was the strongest predictor of stroke, with an adjusted odds ratio (OR) of 2.5 (95% CI: 1.8–3.4, p<0.001). Other significant risk factors included age ≥60 years (OR=1.8), low socioeconomic status (OR=2.1), and comorbidities (OR=1.9).

Table 5: Multivariate Analysis of Stroke Risk

In table 5, after adjusting for confounders, non-compliance remained the most significant predictor of stroke (OR=2.5, p<0.001). Age ≥60 years (OR=1.6), low socioeconomic status (OR=1.9), and comorbidities (OR=1.7) were also independently associated with increased stroke risk.

Table 6: Impact of Compliance on Stroke Severity

In table 6, the data suggest that as stroke severity increases, medication adherence declines; while mild stroke patients show a near balance between compliance (4) and non-compliance (3), moderate stroke patients exhibit lower compliance (2 compliant vs. 5 non-compliant), and none of the severe stroke patients meet the adherence threshold (0 compliant vs. 4 non-compliant).

The findings of this study align with and expand upon previous research investigating the relationship between antihypertensive medication compliance and stroke risk. The results demonstrate that non-compliance is a significant predictor of stroke, with non-compliant patients having a 2.5-fold higher risk compared to compliant patients. This finding is consistent with numerous studies that have highlighted the critical role of medication adherence in controlling hypertension and preventing cardiovascular events, including stroke. ^[10]

The strong association between non-compliance and increased stroke risk observed in this study is supported by prior research. For example, a study by Mazzaglia et al. (2009) found that poor adherence to antihypertensive therapy was associated with a 2.7-fold higher risk of stroke, which is nearly identical to the 2.5-fold increase observed in our study. ^[11] Similarly, a meta-analysis by Burnier and Egan (2019) concluded that non-adherence to antihypertensive medications significantly increases the risk of stroke and other cardiovascular events. ^[12] These consistent findings underscore the importance of adherence as a modifiable risk factor for stroke prevention.

Our study identified low socioeconomic status as a significant predictor of non-compliance, which is consistent with findings from other studies. For instance, Brown and Bussell (2011) reported that financial constraints and lack of access to healthcare resources are major barriers to medication adherence. ^[13] Similarly, a study by Krousel-Wood et al. (2009) found that patients with lower income and education levels were more likely to be non-compliant with antihypertensive therapy. ^[14] These findings highlight the need for interventions that address socioeconomic disparities to improve adherence and reduce stroke risk.

Older age and the presence of comorbidities were also associated with increased stroke risk in our study, which aligns with previous research. A study by Ho et al. (2006) found that older patients and those with multiple chronic conditions were more likely to experience poor adherence and adverse cardiovascular outcomes. ^[15] Additionally, a systematic review by Conn et al. (2009) emphasized that polypharmacy and complex medication regimens, common among older adults and those with comorbidities, contribute to non-compliance. ^[16] These findings suggest that simplifying treatment regimens and providing additional support to high-risk populations could improve adherence and outcomes.

Our study found that non-compliant patients were more likely to experience moderate to severe strokes compared to compliant patients. This finding is supported by research from Vrijens et al. (2012), who reported that poor adherence to antihypertensive therapy is associated with worse clinical outcomes, including more severe strokes and higher mortality rates. ^[17] This underscores the importance of early intervention to improve adherence and prevent severe complications.

Implications for Clinical Practice

Healthcare providers should prioritize educating patients about the importance of medication adherence and the risks of uncontrolled hypertension. Educational interventions have been shown to improve adherence and outcomes. Programs to reduce medication costs and improve access to healthcare resources could enhance compliance among low-income patients. For example, providing free or subsidized medications and offering transportation assistance for clinic visits could help overcome financial and logistical barriers. Routine follow-ups and monitoring of adherence could help identify non-compliant patients early and provide targeted support. Telemedicine and digital health tools, such as medication reminder apps, could also play a role in improving adherence. Reducing the complexity of medication regimens, such as using fixed-dose combinations or once-daily dosing, may improve adherence, particularly among older patients and those with comorbidities.

Strengths and Limitations

The strengths of this study include its prospective design, detailed assessment of compliance using the Medication Possession Ratio (MPR), and comprehensive analysis of risk factors. However, there are some limitations:

The study included only 90 patients, which may limit the generalizability of the findings. Larger studies are needed to confirm these results. While MPR is a widely used measure of adherence, it may not capture all aspects of medication-taking behavior. Future studies could incorporate additional measures, such as pill counts or electronic monitoring. The two-year follow-up period may not be sufficient to capture long-term outcomes. Longer studies are needed to assess the sustained impact of compliance on stroke risk.

Future Directions

Future research should focus on developing and evaluating interventions to improve adherence, particularly among high-risk populations. Studies could also explore the impact of specific strategies, such as patient education programs, financial assistance, and digital health tools, on adherence and stroke outcomes. Additionally, larger, multicenter studies with longer follow-up periods are needed to validate these findings and provide more robust eviden

This study adds to the growing body of evidence demonstrating the critical role of medication compliance in reducing stroke risk among hypertensive patients. Poor adherence to antihypertensive therapy significantly increases the likelihood of stroke and is associated with more severe outcomes. Addressing barriers to compliance, particularly socioeconomic challenges, is essential for improving patient outcomes and reducing the burden of stroke. Healthcare systems must prioritize patient education, access to affordable medications, and regular monitoring to enhance compliance and prevent stroke