European Journal of Cardiovascular Medicine

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia encountered in clinical practice and is associated with significant morbidity and mortality due to its strong association with stroke, systemic thromboembolism, and cardiovascular death ¹. The prevalence of AF increases with age and is often comorbid with other cardiovascular diseases such as hypertension, heart failure, diabetes mellitus, and vascular disease ². It has been estimated that AF accounts for approximately 15–20% of all ischemic strokes, which are typically more severe and associated with higher mortality compared to non-AF-related strokes ³.

To guide appropriate anticoagulation therapy and reduce the risk of stroke in patients with AF, accurate risk stratification is essential. Over the years, various clinical prediction tools have been developed to estimate individual stroke risk in AF patients. One of the most widely accepted and recommended tools is the CHA₂DS₂-VASc score , which stands for Congestive heart failure, Hypertension, Age ≥75 years (doubled), Diabetes mellitus, Stroke/transient ischemic attack/thromboembolism (doubled), Vascular disease, Age 65–74 years, and Sex category (female) ⁴.

The CHA₂DS₂-VASc score evolved from the earlier CHADS₂ score by incorporating additional clinically relevant risk factors, thereby improving its sensitivity and predictive value, especially in identifying low-risk patients who may not require anticoagulation ⁵. Numerous studies have demonstrated that the CHA₂DS₂-VASc score is not only effective in predicting stroke risk but also correlates well with the risk of systemic thromboembolism and all-cause mortality in patients with AF ^6,7.

Despite the widespread adoption of this scoring system in international guidelines, including those from the European Society of Cardiology (ESC) and the American College of Cardiology/American Heart Association/Heart Rhythm Society (ACC/AHA/HRS), there remains a need to validate and apply the CHA₂DS₂-VASc score in diverse patient populations, particularly in real-world settings such as tertiary care hospitals ^8,9. Variations in demographic profiles, access to healthcare, and concomitant diseases can influence the performance of risk stratification tools.

We have come to the realization that the effective performance of scoring systems has not been sufficiently evaluated in different regions, and we believe that regional differences in terms of genetic and environmental factors may influence the effectiveness of these scores. Therefore, this study aims to evaluate the age and sex distribution and etiological factors of atrial fibrillation, analyze its symptomatology, assess the relationship between left atrial size and progression to permanent atrial fibrillation, and identify patients eligible for anticoagulation therapy by applying the CHA₂DS₂-VASc score for risk stratification of stroke and thromboembolism in a tertiary care hospital setting.

This prospective observational cohort study was conducted at the District Teaching Hospital, Koppal, over a period of 18 months from July 1st, 2023, to December 31st, 2024, with a total sample size of 50 patients. Adult patients aged over 18 years, diagnosed with atrial fibrillation (AF), who were admitted to KIMS, Koppal and provided informed consent, were included in the study. The inclusion criteria comprised patients with AF undergoing cardioversion, with available data on recurrence of AF and CHA₂DS₂-VASc score, while those with atrial arrhythmias other than AF or with hemodynamically unstable conditions were excluded.

Data collection included detailed demographic information, classification of AF (paroxysmal, persistent, or permanent), comorbidities, cardiovascular risk factors, etiology of AF, previous cardiac surgeries, drug therapies, and clinical parameters, as obtained from hospital discharge summaries. CHA₂DS₂-VASc scores were calculated based on the presence of congestive heart failure, hypertension, age ≥75 years, diabetes mellitus, prior stroke or transient ischemic attack (TIA) or thromboembolism, vascular disease, age 65–74 years, and female sex category. The predictive value of individual and combined parameters of the CHA₂DS₂-VASc score in relation to stroke and mortality outcomes was analyzed statistically. Testing and data collection were carried out at the time of admission.

Table 1 illustrates that the majority of patients, 28 (56.0%), belonged to the age group of 65–74.9 years, followed by 21 patients (42.0%) aged ≤64.9 years, and 11 patients (22.0%) aged ≥75 years. A slight female predominance was observed, with 28 (56.0%) female patients compared to 22 (44.0%) males. Comorbid conditions included heart failure in 60.0% of patients, hypertension in 56.0%, vascular disease in 28.0%, diabetes mellitus in 16.0%, and prior stroke or transient ischemic attack (TIA) in 14.0% of the cohort.

Table 1: Demographic profiles wise distribution of patients

Figure 1: Pie diagram represents classification of risk of atrial fibrillation patients

Figure 1 presents the risk stratification of patients based on the CHA₂DS₂-VASc score, showing that 82.0% were categorized as high risk, 14.0% as moderate risk, and 4.0% as low risk.

Table 2: Distribution of patient’s common diagnosis at presentation

Table 2 presents the distribution of common clinical diagnoses at the time of presentation among the study participants. The most prevalent condition was chronic obstructive pulmonary disease (COPD), which was identified in 18 individuals (36.0%). This was followed by cor pulmonale, diagnosed in 12 patients (24.0%), and congestive cardiac failure (CCF), observed in 9 patients (18.0%). Ischemic heart disease (IHD) with dilated cardiomyopathy (DCM), cerebrovascular accident (CVA), and hemiparesis were each documented in 7 patients, representing 14.0% of the cohort. Cardiogenic shock was noted in 5 participants, making up 10.0% of the total study population.

Table 3: Classification of risk of stroke based on CHA₂DS₂-VASc score

Table 3 illustrates that the majority of patients, totalling 41 individuals (82.0%), were categorized as high risk. A smaller proportion, accounting for 14.0%, were classified as moderate risk, while only 4.0% of the patients were identified as low risk.

Table 4: Diagnostic accuracy of CHA₂DS₂-VASc score

The diagnostic performance of the CHA₂DS₂-VASc score in predicting stroke and thromboembolic events among atrial fibrillation patients is summarized in Table 4. The sensitivity of the score was 87.21% (95% CI: 76.23%–88.42%), and specificity was 83.32% (95% CI: 74.23%–89.21%). The positive predictive value (PPV) was 87.50% (95% CI: 73.23%–92.03%), while the negative predictive value (NPV) was 63.20% (95% CI: 54.12%–80.21%). The overall diagnostic accuracy of the CHA₂DS₂-VASc score was found to be 85.71% (95% CI: 76.32%–94.29%), indicating a high level of reliability in risk stratification.

Figure 2: Receiver Operating Characteristic (ROC) Curve for the CHA₂DS₂-VASc Score in Predicting Adverse Outcomes in Atrial Fibrillation Patients

The ROC curve illustrates the diagnostic performance of the CHA₂DS₂-VASc score in predicting adverse outcomes such as stroke, thromboembolism, and mortality. The area under the curve (AUC) was found to be 0.823, indicating good discriminative ability. The curve demonstrates high sensitivity at low false positive rates, suggesting that the CHA₂DS₂-VASc score is effective in identifying high-risk patients. The diagonal red line represents the line of no discrimination (AUC = 0.5), while the blue curve reflects the actual test performance. The optimal cut-off point, determined through analysis, was a score of 4 for predicting all-cause mortality.

Table-5: ROC curve results

Table 5 presents the receiver operating characteristic (ROC) curve analysis for the CHA₂DS₂-VASc score in predicting adverse outcomes. The area under the curve (AUC) for predicting all-cause mortality was 0.823 (95% CI: 0.521–0.974; p = 0.002), with the optimal cut-off score identified as 4. For systemic embolism (SE) in females during the follow-up period, the AUC was 0.718 (95% CI: 0.613–0.783; p < 0.001), with a best cut-off score of 5. In males, the AUC for SE prediction was 0.737 (95% CI: 0.621–0.797; p < 0.001), with an optimal cut-off score of 4. These results indicate that the CHA₂DS₂-VASc score demonstrates good discriminatory power for predicting both mortality and thromboembolic events in patients with atrial fibrillation.

The findings of our clinical study provide valuable insights into the risk stratification of patients with atrial fibrillation (AF) attending a tertiary care hospital, using the CHA₂DS₂-VASc score to predict stroke, thromboembolism, and mortality. Our data reveal that the majority of patients were in the older age groups, with 56.0% falling between 65–74.9 years, followed by 42.0% aged ≤64.9 years, and 22.0% aged ≥75 years. This age distribution aligns with the known epidemiology of AF, which is more prevalent among elderly individuals ¹. The aging population remains a significant driver for the increasing incidence of AF globally, especially in settings such as tertiary hospitals where complex cardiovascular cases are commonly managed ⁸.

A slight female predominance was observed in our cohort, with 56.0% females compared to 44.0% males. While some studies have shown a male preponderance in AF prevalence, others have reported similar or higher proportions of women, particularly in older age groups due to longer life expectancy ². Notably, the CHA₂DS₂-VASc score incorporates sex as a risk factor, assigning one point to female gender, suggesting that women may carry a slightly increased stroke risk compared to men when other risk factors are absent.

Our study also highlights the high burden of comorbidities among AF patients. Heart failure was present in 60.0% of participants, hypertension in 56.0%, vascular disease in 28.0%, diabetes mellitus in 16.0%, and prior stroke or TIA in 14.0%. These findings are consistent with published literature indicating that AF often coexists with multiple cardiovascular and metabolic conditions, all of which contribute significantly to stroke risk and overall morbidity ³. In fact, these comorbidities form the core components of the CHA₂DS₂-VASc scoring system, further validating its relevance in real-world clinical settings.

In comparison with previous studies, our results support the utility of the CHA₂DS₂-VASc score in identifying high-risk patients. For instance, Lip et al. demonstrated that the CHA₂DS₂-VASc score outperforms the earlier CHADS₂ score by better identifying low-risk patients and improving stroke risk prediction across different subpopulations ⁶. Similarly, Friberg et al. found that even patients categorized as low risk by the CHADS₂ score could be reclassified as moderate or high risk when assessed with the CHA₂DS₂-VASc score, leading to more appropriate anticoagulation decisions ⁵.

In a large observational study by Olesen et al., the CHA₂DS₂-VASc score showed a strong correlation with both ischemic stroke and systemic embolic events, reinforcing its role not only in stroke prediction but also in broader thromboembolic risk assessment ⁹. Our findings corroborate this, as the presence of comorbidities such as heart failure, hypertension, and prior stroke supports the rationale for classifying most of our patients as high risk (82%), with only a small proportion considered moderate (14%) or low risk (4%).

These observations are also in line with international guidelines from the European Society of Cardiology (ESC) and the American College of Cardiology/American Heart Association/Heart Rhythm Society (ACC/AHA/HRS), which recommend the use of the CHA₂DS₂-VASc score as the preferred tool for stroke risk stratification in patients with non-valvular AF ^7,4. The ESC guidelines emphasize that a score of ≥2 in males or ≥3 in females warrants oral anticoagulation therapy, while lower scores may guide individualized decision-making ⁴. Given the high prevalence of comorbidities in our patient cohort, most would qualify for anticoagulant therapy based on their CHA₂DS₂-VASc scores.

However, it is important to note that while the CHA₂DS₂-VASc score is effective for risk stratification, it does not account for all potential variables influencing outcomes in AF patients. Emerging biomarkers, genetic predispositions, and echocardiographic parameters such as left atrial size or function may offer additional predictive value ¹⁰.

Our clinical study evaluated the distribution of stroke risk among patients with atrial fibrillation (AF) attending a tertiary care hospital in Asia using the CHA₂DS₂-VASc score for risk stratification. The results revealed that a substantial majority of patients—82.0% —were classified as high risk , while 14.0% were categorized as moderate risk , and only 4.0% fell into the low-risk group. These findings underscore the high prevalence of comorbid conditions such as hypertension, heart failure, and prior stroke among AF patients in our setting, reinforcing the importance of the CHA₂DS₂-VASc scoring system in identifying individuals who are most likely to benefit from anticoagulation therapy.

These results align with findings from large Asian cohort studies. For instance, Chao et al. conducted a nationwide retrospective cohort study involving over 538,653 person-years of follow-up and reported that 21,008 patients experienced ischemic stroke during the observation period. Their modified CHA₂DS₂-VASc (mCHA₂DS₂-VASc) score demonstrated superior predictive performance compared to the standard CHA₂DS₂-VASc score in terms of C-statistics and net reclassification index. Notably, among the 8,654 patients with an mCHA₂DS₂-VASc score of 1 (males) or 2 (females), warfarin use was associated with a 30% lower risk of ischemic stroke without a significant increase in the risk of intracranial haemorrhage (ICH) when compared to no treatment. Net clinical benefit analyses further supported the use of warfarin across various weighted models .¹¹

Similarly, a large Korean nationwide cohort study confirmed that CHA₂DS₂-VASc scores effectively stratify stroke risk and accurately identify truly low-risk patients. In their cohort, the majority of patients were categorized as moderate-to-high risk, with a clear escalation in stroke rates corresponding to increasing CHA₂DS₂-VASc scores .¹¹ Our findings mirror this trend, which may be attributed to the nature of our tertiary care setting where patients often present with multiple cardiovascular comorbidities and complex disease profiles.

In addition, a Taiwanese population-based study involving more than 186,000 patients demonstrated that the CHA₂DS₂-VASc score significantly outperformed the older CHADS₂ score in predicting ischemic stroke risk. This study also found that less than 15% of patients had a CHA₂DS₂-VASc score of 0, indicating truly low risk—a finding consistent with our observed 4% low-risk category .³

Further validation of the CHA₂DS₂-VASc score in another Korean cohort showed high sensitivity and specificity for predicting thromboembolic events [Reference 12]. Their data similarly indicated that a large proportion of AF patients fall into the high-risk category, reinforcing the generalizability and clinical utility of the CHA₂DS₂-VASc score across diverse populations within Asia. ¹²

In the Korean NHIS cohort, among 5,855 patients, a considerable proportion belonged to the high-risk group with a mean CHA₂DS₂-VASc score of 4.09 ± 1.69. The majority (28.3%) were aged over 75 years, and 53.7% were women. Vascular disease and hypertension were found in 26.8% and 90.4% of patients, respectively¹³. Comparatively, our study population also demonstrated a high prevalence of comorbidities: 60.0% had heart failure, 56.0% had hypertension, and 28.0% had vascular disease, affirming similar risk burden profiles among high-risk patients.

The Euro Heart Survey also reflects similar trends, with high-risk patients averaging a CHA₂DS₂-VASc score of 3.28 ± 2.08 and having comorbidities such as heart failure (31.9%) and diabetes (19.9%)¹⁴. Our study’s findings of 18.0% presenting with CCF and 16.0% with diabetes show consistency, albeit slightly lower percentages, possibly reflecting differences in population age distribution or underlying healthcare access.

Interestingly, the Danish Nationwide Cohort showed that 59.7% of patients were aged above 75 years, and 51.2% were women¹⁵. Our study noted only 22.0% of participants in the ≥75 age group and a female predominance of 56.0%. This may be attributed to demographic and referral differences in tertiary care centers within India compared to nationwide cohorts in Europe.

In all referenced cohorts, the risk stratification consistently correlates with higher prevalence of comorbidities—particularly hypertension, heart failure, and vascular disease—which are key contributors to elevated CHA₂DS₂-VASc scores. Our findings align well with this trend, emphasizing that the scoring system remains highly applicable and valuable in predicting adverse outcomes in Indian clinical settings.

Our study presents the distribution of common clinical diagnoses at the time of presentation among patients with atrial fibrillation (AF) attending a tertiary care hospital. The most prevalent condition was chronic obstructive pulmonary disease (COPD) , identified in 18 individuals (36.0%) , followed by cor pulmonale in 12 patients (24.0%) , and congestive cardiac failure (CCF) in 9 patients (18.0%) . Ischemic heart disease (IHD) with dilated cardiomyopathy (DCM) , cerebrovascular accident (CVA) , and hemiparesis were each documented in 7 patients (14.0%) . Cardiogenic shock was noted in 5 participants (10.0%) , indicating the presence of acute, life-threatening presentations within this cohort.

The overall clinical profile of our study population reflects a high burden of cardiovascular and pulmonary comorbidities , consistent with the known pathophysiological interplay between systemic diseases and AF. The observed prevalence of COPD (36%) , cor pulmonale (24%) , CCF (18%) , IHD/DCM and CVA (14% each) , and cardiogenic shock (10%) underscores the complexity and multimorbidity in this patient group, which contributes significantly to both thromboembolic risk and adverse clinical outcomes ¹³.

Further analysis revealed that 60.0% of patients had heart failure , 56.0% were diagnosed with hypertension , 28.0% had vascular disease , 16.0% had diabetes mellitus , and 14.0% had a prior stroke or transient ischemic attack (TIA) . These findings align closely with international trends reported in other observational studies, including the work of Ibdah et al.¹⁶ , who noted even higher rates of hypertension (74.6%) , dyslipidemia (45.0%) , ischemic heart disease (26.3%) , and heart failure (26.3%) in their cohort .

In Ibdah et al.'s ¹⁶ study, the prevalence of stroke was 15.3% , nearly identical to the 14.0% observed in our cohort, highlighting the critical importance of early risk stratification using the CHA₂DS₂-VASc score for the prevention of stroke and systemic embolism in AF patients. Moreover, while 81.8% of patients in the Ibdah study were on anticoagulant therapy, the strong correlation between CHA₂DS₂-VASc scores and stroke risk supports our findings, where a large majority (82.0% ) were classified as high risk , reinforcing the utility of this scoring system in guiding clinical decision-making.

Interestingly, while Ibdah et al. ¹⁶ reported a 12.0% prevalence of COPD , our cohort demonstrated a significantly higher rate (36.0% ), suggesting possible regional variation in pulmonary comorbidities or differences in environmental, occupational, or lifestyle-related exposures such as air pollution and tobacco use.

Additionally, data from another comparative study examining baseline characteristics of heart failure patients stratified by AF status showed that hypertension was the most common comorbidity in both groups, affecting 43.5% of AF patients and 43.0% of non-AF patients . Previous thromboembolism was reported in 26.7% of AF patients versus 28.5% of non-AF patients , while vascular disease was more prevalent in those without AF (26.0% vs. 20.1% ). A history of myocardial infarction was slightly more common in non-AF patients (19.8% vs. 13.4% ), and diabetes mellitus was marginally more frequent in the non-AF group (17.2% vs. 14.9% ). Peripheral arterial disease affected comparable proportions in both groups (8.5% in AF vs. 8.7% in non-AF ), whereas ischemic stroke was notably more common in the AF cohort (11.6% vs. 8.0% ). Renal disease was similarly present in both groups (~5% each ), and hyperthyroidism was twice as prevalent in the AF group (3.8% vs. 1.9%), reaffirming its role in AF pathogenesis. Liver disease was rare and equally distributed between groups (0.4% each ) ¹⁷.

Our clinical trial on risk stratification using the CHA2DS2-VASc score in patients with atrial fibrillation (AF) attending a tertiary care hospital revealed that 82.0% of patients (41 individuals) were categorized as high risk, 14.0% as moderate risk, and 4.0% as low risk. This distribution is consistent with findings from Al-Turaiki et al. [18], who reported a high-risk classification in 92% of their cohort (243 patients), with only 6.4% (17 patients) and 1.5% (4 patients) falling into moderate- and low-risk categories, respectively, using the CHA2DS2-VASc score. Their study also demonstrated the superior sensitivity of CHA2DS2-VASc over the CHADS2 score, which classified only 70.5% of patients as high risk, with a statistically significant difference in mean scores (3.55 ± 1.5 vs. 2.09 ± 1.11; P < 0.00001) ¹⁸.

Maeda et al. ¹⁹ provided further evidence supporting the CHA2DS2-VASc score’s utility, defining risk levels based on scores (men: 0 = low, 1 = intermediate, ≥2 = high; women: 1 = low, 2 = intermediate, ≥3 = high) and observing a significant trend in the annual incidence of ischemic stroke (0.18%, 0.44%, and 1.29% for low, intermediate, and high risk, respectively; P < 0.001) and bleeding events (0.51%, 1.28%, and 2.02%, respectively; P < 0.001) over a 2.5-year follow-up [18]. These findings underscore the score’s ability to predict both thromboembolic and bleeding risks, aligning with our study’s high-risk patient predominance.

In contrast, an observational study across 19 countries highlighted challenges in anticoagulation practices, with 38.7% of low-risk patients (CHA2DS2-VASc score = 0) receiving anticoagulants and 40.7% of high-risk patients (score ≥2) not receiving them ²⁰. Al-Turaiki et al. ¹⁸ reported a lower rate of inappropriate anticoagulation in low-risk patients (1.5% prescribed warfarin), suggesting that clinical pharmacist-managed anticoagulation clinics may enhance adherence to guideline-directed therapy ¹⁸. These comparisons emphasize the importance of accurate risk stratification using the CHA2DS2-VASc score to guide anticoagulation decisions and improve outcomes in AF patients.

Kim et al. ¹³ conducted a comprehensive analysis to evaluate the predictive performance of three major thromboembolic risk stratification models—CHADS₂, CHA₂DS₂-VASc, and ATRIA—in an Asian atrial fibrillation (AF) cohort. At baseline, the proportions of patients categorized as low risk were 17.9% using CHADS₂, 14.7% with CHA₂DS₂-VASc, and notably higher at 56.0% with the ATRIA score. During follow-up, these low-risk designations were retained in 13.9%, 11.4%, and 46.6% of patients, respectively. Most notably, the observed ischemic stroke rates per 100 person-years among patients in the low-risk category were 0.42 for CHADS₂, 0.26 for CHA₂DS₂-VASc, and a significantly higher 1.43 for ATRIA. These findings suggest that the CHA₂DS₂-VASc score most effectively delineates truly low-risk patients within the Asian AF population, outperforming both the CHADS₂ and ATRIA scores in terms of stroke prediction accuracy, and reinforcing its role as the preferred tool for risk stratification in clinical practice for this demographic.

Our study showed that the diagnostic performance of the CHA₂DS₂-VASc score in predicting stroke and thromboembolic events among atrial fibrillation patients. The sensitivity of the score was 87.21% (95% CI: 76.23%–88.42%), and specificity was 83.32% (95% CI: 74.23%–89.21%). The positive predictive value (PPV) was 87.50% (95% CI: 73.23%–92.03%), while the negative predictive value (NPV) was 63.20% (95% CI: 54.12%–80.21%). The overall diagnostic accuracy of the CHA₂DS₂-VASc score was found to be 85.71% (95% CI: 76.32%–94.29%), indicating a high level of reliability in risk stratification.

Liu FD  et al ²¹  conducted a meta-analysis after screening 114 studies, of which six trials met the inclusion criteria and were ultimately analyzed. The pooled diagnostic odds ratio (DOR) for the CHADS₂ and CHA₂DS₂-VASc scores was 2.86 (95% CI: 1.83–4.28) and 2.80 (95% CI: 1.83–4.28), respectively. The CHA₂DS₂-VASc score demonstrated better sensitivity (0.920) compared to the CHADS₂ score (0.768). However, both scoring systems exhibited inherent heterogeneity and limited specificity. Despite demonstrating good overall diagnostic accuracy, the clinical applicability of CHADS₂ and CHA₂DS₂-VASc scores in predicting stroke risk among patients without atrial fibrillation requires further validation.

Shrestha M  et al ²²The mean CHA2DS2-VASc score was 3.2±2.8. 25.3% of patients with atrial fibrillation had sudden cardiac death. For prediction of sudden cardiac death, CHA2DS2-VASc score had a sensitivity of 78.3%, specificity of 82.3%, positive predictive value of 59.1%, negative predictive value 92% and a diagnostic accuracy of 81.3% for predicting risk of sudden cardiac death. Also, 25.3% of patients with atrial fibrillation had sudden cardiac death during hospitalization. The CHA2DS2-VASc score has a diagnostic accuracy of 81.3%, a sensitivity of 78.3%, a specificity of 82.3%, a positive predictive value (PPV) of 59.1%, a negative predictive value (NPV) of 92%. The study concluded that Diagnostic value of higher CHA2DS2-VASC score in predicting sudden cardiac death among atrial fibrillation patients is very good. The high predictive value of this score was significantly related to obesity, age, sex, diabetes, hypertension, previous history of stroke and socio-economic status. CHA2DS2-VASC score can be used in clinical practice to assess the risk sudden cardiac death among the patients with atrial fibrillation with high predictive value.

Chao et al  ¹¹ shows the ROC curves of CHADS2 and CHA2DS2-VASc scores in predicting ischemic stroke. The c-indexes based on areas under the ROC curves for the CHADS2 and CHA2DS2-VASc scores in predicting ischemic stroke were 0.659 (95% CI 0.654–0.665) and 0.698 (95% CI 0.691–0.705), respectively. The difference was statistically significant in favor of the CHA2DS2-VASc score (DeLong test P o .0001).

Tsiartas E  et al ²³The ROC curve for the baseline, follow-up, and Delta CHA2DS2-VASc scores, and the occurrence of stroke events was created . The AUC for the follow-up (0.854; 95%C1: 0.832-0.874; 19 < 0.001) and Delta (0.839; 95%C1: 0.816-0.860; 12=0.002) CHA2DS2-VASc scores were significantly higher in contrast to the baseline score (0.648; 95%C1: 0.619-0.676). Delta CHA2DS2-VASc score's predicting value was not found superior to that of the follow-up score (p=0.723).

The study demonstrated a significant association between higher CHADS-VASC+ scores and the presence of imaging-confirmed stroke. Among patients with a CHADS-VASC+ score ≥ 4, 71.0% showed imaging evidence of stroke, compared to only 29.0% in those with scores < 4. The odds ratio for stroke in the higher score group was 1.838 (95% CI: 1.042–3.241), with a p-value of 0.035, indicating statistical significance. Furthermore, ROC curve analysis revealed that the CHADSVASC+ score exhibited slightly better sensitivity and specificity in predicting stroke compared to the conventional CHADS-VASC score, though both models showed modest overall predictive power.²⁴

Our study evaluated the diagnostic performance of the CHA₂DS₂-VASc score in predicting stroke and thromboembolic events among patients with atrial fibrillation (AF) attending a tertiary care hospital. The results demonstrated high sensitivity and specificity, indicating strong utility in clinical risk stratification. Specifically, the sensitivity of the CHA₂DS₂-VASc score was 87.21% (95% CI: 76.23–88.42%) , and specificity was 83.32% (95% CI: 74.23–89.21%) . The positive predictive value (PPV) was 87.50% (95% CI: 73.23–92.03%) , while the negative predictive value (NPV) was 63.20% (95% CI: 54.12–80.21%) . Overall, the diagnostic accuracy of the score was 85.71% (95% CI: 76.32–94.29%) , highlighting its reliability in identifying patients at elevated risk for stroke and thromboembolism.

These findings are consistent with several published studies evaluating the performance of the CHA₂DS₂-VASc score across different populations. For instance, Liu et al. ²¹ conducted a meta-analysis of six studies involving over 100,000 patients and found that the CHA₂DS₂-VASc score had superior sensitivity (0.920) compared to the older CHADS₂ score (0.768) . Although both scores showed good overall diagnostic accuracy—demonstrated by pooled diagnostic odds ratios (DOR) of 2.86 for CHADS₂ and 2.80 for CHA₂DS₂-VASc —they also revealed inherent heterogeneity and suboptimal specificity, suggesting room for improvement in certain clinical settings.

In contrast, Shrestha et al.²² assessed the ability of the CHA₂DS₂-VASc score to predict sudden cardiac death (SCD) in AF patients rather than stroke [Reference 22]. Their study reported a sensitivity of 78.3% , specificity of 82.3% , PPV of 59.1% , and NPV of 92% , with an overall diagnostic accuracy of 81.3% . These data support the broader applicability of the CHA₂DS₂-VASc score beyond stroke prediction, particularly in identifying patients at risk for adverse cardiovascular outcomes such as SCD. Notably, the authors emphasized that higher CHA₂DS₂-VASc scores were significantly associated with obesity, age, sex, diabetes, hypertension, prior stroke, and socioeconomic status , all of which are integral components of the scoring system.

Further validation of the CHA₂DS₂-VASc score's predictive capacity was provided by Chao et al.¹¹ , who compared it with the CHADS₂ score using receiver operating characteristic (ROC) curve analysis to assess ischemic stroke risk in a large cohort . They reported C-indexes (AUC) of 0.659 (95% CI: 0.654–0.665) for the CHADS₂ score and 0.698 (95% CI: 0.691–0.705) for the CHA₂DS₂-VASc score, with the latter showing statistically significant superiority (P < 0.0001). This further supports the incremental benefit of the additional variables included in the CHA₂DS₂-VASc model.

More recently, Tsiartas et al.²³ investigated the dynamic changes in CHA₂DS₂-VASc scores over time and their association with stroke occurrence [Reference 23]. They found that follow-up and delta CHA₂DS₂-VASc scores had significantly better area under the curve (AUC) values (0.854 and 0.839 , respectively) compared to baseline scores (0.648 ), indicating that serial assessment of this score may improve risk prediction. Importantly, they concluded that follow-up scores outperformed baseline scores in predicting stroke events, suggesting that dynamic monitoring of risk factors enhances clinical decision-making.

Finally, a recent comparative study highlighted the clinical relevance of the modified CHADS-VASC+ score , which incorporates newer biomarkers or imaging parameters into the traditional CHA₂DS₂-VASc framework [Reference 24]. Among patients with a CHADS-VASC+ score ≥ 4 , 71.0% had imaging-confirmed stroke compared to only 29.0% in those with lower scores (odds ratio = 1.838; P = 0.035). While the CHADS-VASC+ score showed slightly improved sensitivity and specificity over the conventional CHA₂DS₂-VASc score, both systems demonstrated modest overall predictive power , reinforcing the need for ongoing refinement and integration with novel biomarkers.²⁴

Our clinical trial on risk stratification using the CHA₂DS₂-VASc score in atrial fibrillation (AF) patients attending a tertiary care hospital concluded that the score effectively predicts stroke, thromboembolism, and mortality, with 82.0% of patients classified as high risk and a diagnostic accuracy of 85.71%. The area under the ROC curve (AUC) of 0.823 for all-cause mortality and optimal cut-off scores of 4 and 5 for mortality and systemic embolism, respectively, underscore the score’s robust discriminative ability.

Limitations

The study’s single-center design and small sample size (50 patients) limit the generalizability of findings to broader Indian populations. The high prevalence of COPD (36.0%) and cor pulmonale (24.0%) may reflect referral bias or regional factors, potentially skewing risk profiles. The relatively low NPV (63.20%) suggests caution in ruling out risk in low-scoring patients. The study did not assess long-term outcomes beyond the follow-up period, limiting insights into the score’s predictive value over extended durations.

1. Go AS, Hylek EM, Phillips KA, Chang Y, Henault LE, Selby JV, et al. Prevalence of diagnosed atrial fibrillation in adults: national implications of rhythm vs rate control strategies. JAMA. 2001;285(18):2370–5. doi: 10.1001/jama.285.18.2370. Available from: https://jamanetwork.com/journals/jama/fullarticle/193807
2. Wolf PA, Abbott RD, Kannel WB. Atrial fibrillation as an independent risk factor for stroke: the Framingham Study. Stroke. 1991;22(8):983–8. doi: 10.1161/01.STR.22.8.983. Available from: https://www.ahajournals.org/doi/10.1161/01.STR.22.8.983
3. Lip GYH, Nieuwlaat R, Pisters R, Lane DA, Crijns HJGM. Refining clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation using a novel risk factor-based approach: the Euro Heart Survey on Atrial Fibrillation. Chest. 2010;137(2):263–72. doi: 10.1378/chest.09-1584. Available from: https://journal.chestnet.org/article/S0012-3692(10)00054-1/fulltext
4. Pisters R, Lane DA, Nieuwlaat R, de Vos CB, Crijns HJGM, Lip GYH. A novel user-friendly score (HAS-BLED) to assess 1-year risk of major bleeding in patients with atrial fibrillation: the Euro Heart Survey. Chest. 2010;138(5):1093–100. doi: 10.1378/chest.10-0134. Available from: https://journal.chestnet.org/article/S0012-3692(10)00579-9/fulltext
5. Camm AJ, Lip GYH, De Caterina R, Savelieva I, Atar D, Hohnloser SH, et al. 2012 focused update of the ESC Guidelines for the management of atrial fibrillation: an update of the 2010 ESC Guidelines for the management of atrial fibrillation. Eur Heart J. 2012;33(21):2719–47. doi: 10.1093/eurheartj/ehs253. Available from: https://academic.oup.com/eurheartj/article/33/21/2719/2398229
6. Friberg L, Rosenqvist M, Lip GYH. Net clinical benefit of warfarin anticoagulation in patients with atrial fibrillation and a 'low-medium' risk profile: a nationwide cohort study using the CHA2DS2-VASc score. Chest. 2012;141(5):1188–96. doi: 10.1378/chest.11-1919. Available from: https://journal.chestnet.org/article/S0012-3692(12)60265-8/fulltext
7. Olesen JB, Lip GYH, Hansen ML, Hansen PR, Tolstrup JS, Lindhardsen J, et al. The use of vitamin K antagonists and risk of bleeding in patients with atrial fibrillation varying in "real-life" stroke and bleeding risk (from the ORBIT-AF Registry). Am J Cardiol. 2012;110(10):1467–72. doi: 10.1016/j.amjcard.2012.06.035. Available from: https://www.ajconline.org/article/S0002-9149(12)01575-7/fulltext
8. Chugh SS, Havmoeller R, Narayanan K, Singh D, Rienstra M, Benjamin EJ, et al. Worldwide epidemiology of atrial fibrillation: a Global Burden of Disease 2010 Study. Circulation. 2014;129(8):837–47. doi: 10.1161/CIRCULATIONAHA.113.008040. Available from: https://www.ahajournals.org/doi/10.1161/CIRCULATIONAHA.113.008040
9. January CT, Wann LS, Alpert JS, Calkins H, Cigarroa JE, Cleveland JC, et al. 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: executive summary. J Am Coll Cardiol. 2014;64(21):2246–80. doi: 10.1016/j.jacc.2014.03.022. Available from: https://www.jacc.org/doi/pdf/10.1016/j.jacc.2014.03.022
10. Apostolakis S, Guo Y, Baumann G, Sullivan R, Lip GYH. Clinical and biomarker profiles associated with different types of stroke in patients with atrial fibrillation. J Am Coll Cardiol . 2014;63(10):1079–1087. DOI: 1016/j.jacc.2013.10.052
11. Chao TF, Lip GY, Liu CJ, Tuan TC, Chen SJ, Wang KL, Lin YJ, Chang SL, Lo LW, Hu YF, Chen TJ, Chiang CE, Chen SA. Validation of a Modified CHA2DS2-VASc Score for Stroke Risk Stratification in Asian Patients With Atrial Fibrillation: A Nationwide Cohort Study. Stroke. 2016 Oct;47(10):2462-9. doi: 10.1161/STROKEAHA.116.013880. Epub 2016 Sep 13. PMID: 27625386.Li YG, Lee SR, Choi EK, Lip GY. Stroke Prevention in Atrial Fibrillation: Focus on Asian Patients. Korean Circ J. 2018 Aug;48(8):665-684. doi: 10.4070/kcj.2018.0190. PMID: 30073805; PMCID: PMC6072666.
12. Li YG, Lee SR, Choi EK, Lip GY. Stroke Prevention in Atrial Fibrillation: Focus on Asian Patients. Korean Circ J. 2018 Aug;48(8):665-684. doi: 10.4070/kcj.2018.0190. PMID: 30073805; PMCID: PMC6072666.
13. Kim TH, Yang PS, Uhm JS, Kim JY, Pak HN, Lee MH, Joung B. CHA2DS2-VASc Score (Congestive Heart Failure, Hypertension, Age ≥75 [Doubled], Diabetes Mellitus, Stroke [Doubled]–Vascular Disease, Age 65–74, and Sex Category [Female]) Score. Circulation. 2017;135(9):834-847. Available from: https://www.ahajournals.org/doi/10.1161/CIRCULATIONAHA.116.025993¹
14. Nieuwlaat R, Capucci A, Camm AJ, et al. Atrial fibrillation management: a prospective survey in ESC member countries. Eur Heart J. 2005;26(22):2422–2434. Available from: https://academic.oup.com/eurheartj/article/26/22/2422/652464²
15. Olesen JB, Lip GYH, Hansen ML, Hansen PR, Tolstrup JS, Lindhardsen J, et al. Validation of risk stratification schemes for predicting stroke and thromboembolism in atrial fibrillation: nationwide cohort study. BMJ. 2011;342:d124. Available from: https://www.bmj.com/content/342/bmj.d124³
16. Ibdah R, Obeidat O, Khader Y, Al-Nusair J, Abusurrah O, Obeidat A, Obeidat A, Rawashdeh S, Alrabadi N, Obiedat AF, Alnadi NN, Hammoudeh A. Validation of CHA2DS2 VASc Score Predictability of Stroke and Systemic Embolization in a Middle Eastern Population with AF: The Jordan Atrial Fibrillation (JoFib) Study. Vasc Health Risk Manag. 2023 Apr 24;19:255-264. doi: 10.2147/VHRM.S404575. PMID: 37125391; PMCID: PMC10145451.
17. Melgaard L, Gorst-Rasmussen A, Lane DA, Rasmussen LH, Larsen TB, Lip GYH. Assessment of the CHA2DS2-VASc Score in Predicting Ischemic Stroke, Thromboembolism, and Death in Patients With Heart Failure With and Without Atrial Fibrillation. JAMA. 2015;314(10):1030–1038. doi:10.1001/jama.2015.10725
18. Al-Turaiki AM, Al-Ammari MA, Al-Harbi SA, Khalidi NS, Alkatheri AM, Aldebasi TM, et al. Assessment and comparison of CHADS2, CHA2DS2-VASc, and HAS-BLED scores in patients with atrial fibrillation in Saudi Arabia. Ann Thorac Med 2016;11:146-50.
19. Maeda T, Nishi T, Funakoshi S, Tada K, Tsuji M, Satoh A, Kawazoe M, Yoshimura C, Arima H. Risks of Bleeding and Stroke Based on CHA2DS2-VASc Scores in Japanese Patients With Atrial Fibrillation: A Large-Scale Observational Study Using Real-World Data. J Am Heart Assoc. 2020 Mar 3;9(5):e014574. doi: 10.1161/JAHA.119.014574. Epub 2020 Feb 28. PMID: 32106743; PMCID: PMC7335551.
20. Kakkar AK, Mueller I, Bassand JP, Fitzmaurice DA, Goldhaber SZ, Goto S, et al. Risk profiles and antithrombotic treatment of patients newly diagnosed with atrial fibrillation at risk of stroke: Perspectives from the international, observational, prospective GARFIELD registry. PLoS One 2013;8:e63479.
21. Liu FD, Shen XL, Zhao R, Li GF, Wu YL, Tao XX, Wang S, Zhou JJ, Zheng B, Zhang QT, Yao Q, Zhao Y, Zhang X, Wang XM, Liu HQ, Shu L, Liu JR. Predictive role of CHADS2 and CHA2DS2-VASc scores on stroke and thromboembolism in patients without atrial fibrillation: a meta-analysis. Ann Med. 2016 Aug;48(5):367-75. doi: 10.1080/07853890.2016.1179390. Epub 2016 May 6. PMID: 27153002.
22. Shrestha M, Luitel B. Risk Assessment of Sudden Cardiac Death in Patients with Atrial Fibrillation Using CHA2DS2-Vasc Score. 2023; 19(3); 277-81.
23. Tsiartas E, Samaras A, Papazoglou AS, et al. Changes in CHA₂DS₂-VASc score and risk of ischemic stroke among patients with atrial fibrillation. Heart Vessels. 2023;38:1267–1276. DOI: 1007/s00380-023-02278-1.
24. Sekar A, Gogtay M, Shanmugavel Geetha H, Sanghvi A, Singh Y, Balani PL, Shah D, George SV. Refining Clinical Risk Stratification for Estimating the Risk of Ischemic Stroke in Non-Atrial Fibrillation Patients with a Novel Risk Stratification Tool, CHA₂DS₂-Vasc+ Score. Blood. 2022;140(Suppl 1):13031–13032. DOI: 1182/blood-2022-167941.