Risk Assessment for Cardiovascular Disease

Introduction

Metabolic syndrome (MetS) is a prevalent global health concern, as evidenced by numerous studies linking it to cardiovascular disease (CVD).^1–4 Developing countries, in particular, bear a significant burden of morbidity and mortality related to CVD, with reports indicating that up to 75% of non-communicable disease-related mortality can be attributed to CVD.^5,6

Studies have indicated that the presence of MetS is associated with a significantly elevated risk of developing CVD, with a 50–60% increased risk compared to individuals without MetS.⁷ Furthermore, additional research has shown a substantially greater risk of CVD development in individuals with MetS, with reported two to five-fold increases in risk.^8,9

Early detection of MetS is paramount significant as it can identify individuals who are at risk of developing CVD thus avoiding adverse cardiovascular outcomes.¹⁰ Many algorithms that estimate risk of development of CVD in individuals with MetS have been validated so far.^2–4

Although the criteria for prediction of CVD risk in individuals with MetS display some discrepancies, however, data collected from large prospective population-based studies, like the Framingham offspring study,¹¹ Botnia study,¹² Kuopio Ischemic heart Disease study,¹³ Italian study,¹⁴ and Atherosclerosis Risk in Communities study,¹⁵ provide sufficient evidence in support of MetS hypothesis which states that MetS greatly increases risk of CVD associated morbidity and mortality in these individuals.^12,16

Evidence has revealed that globally, CVD is the leading cause of death, and around 80–86% of these deaths occur in low- and middle-income countries.^17,18 Most South Asian countries, including Pakistan, are identified to have a higher risk of cardiometabolic diseases as compared to other part of the globe.^19,20 Although numerous studies have been conducted regarding the risk factors of CVD, to our knowledge, there is a dearth of studies available from Pakistan that estimate the CVD risk among patients with MetS. As our study focuses specifically on newly diagnosed MetS patients, the Framingham Risk Score (FRS) and Globorisk score are particularly relevant. These scoring systems encompass risk factors that are commonly associated with MetS, such as blood pressure, cholesterol levels, and age, making them well suited for our study population. Moreover, one of the reasons for using Globorisk score is its ability to evaluate country-specific CVD risk. Thus, the current study assessed the risk of developing CVD events over 10 years using two widely used predictive scores, namely the FRS and Globorisk Score. As far as we know, this study is one of the first in Pakistan to perform an in-depth estimation of the risk of CVD among patients with newly diagnosed MetS.

Materials and Methods

This study is a part of a large community-based cross-sectional survey that was conducted primarily to assess the prevalence and associated risk factors of MetS among apparently healthy adult population of Karachi, Pakistan. The survey was carried out in various areas of Karachi from February 2022 to August 2022. Approval was obtained for this study from the human ethics committee of Dow University of Health Sciences (IRB-2332/DUHS/Approval/2021/670).

Sample Population

The inclusion criteria for this research study were individuals aged 30–74 years who were recently diagnosed with MetS. All these individuals were asymptomatic and perceived themselves as healthy prior to this screening survey. Any individual with major physical disability, known illness, and taking any regular medication was excluded. Moreover, pregnant or lactating women were also excluded from the study.

Risk Scores

Metabolic syndrome was defined based on the definition of International Diabetes Federation (IDF).²¹ FRS was evaluated using factors like age, gender, total cholesterol, high-density lipoprotein (HDL), systolic blood pressure (SBP), antihypertensive treatment, smoker, and diabetes. Ten-year FRS of 20% as high risk.²² Globorisk score also predicts ten year risk of heart attack or stroke in healthy individuals.² The variables included are country name (Pakistan), age, gender, smoker, diabetes, blood pressure, and cholesterol. The Globorisk tool has no categorical risk classification as other existing cardiovascular risk classification system. However, the current study categorized the risk as low (<10%), moderate (10–19.9%), high (20–29.9%) and very high (≥30%) as described in study by Barua et al.²³

Data Collection Procedure

A pre-structured questionnaire was used for the purpose of the collection of the data. Detailed information was collected regarding the sociodemographic and clinical characteristics of the individuals. All information required for the assessment of FRS and Globorisk Score was calculated. All participants provided informed consent prior to enrollment.

Data Analysis Plan

Statistical analysis was performed using STATA 17. The normality of the data was assessed using Shapiro–Wilk test. The mean along with the standard deviation (SD) was reported for quantitative variables. Frequency and percentages were calculated for qualitative variables. The One-Way ANOVA test was applied to see the mean difference of quantitative predictor variables with FRS and Globorisk Score. Moreover, a chi-square test was applied to see the association of outcome, ie, 10-year CVD risks using both risk scores with predicting factors. The P of ≤0.05 was considered significant. Pearson’s correlation test along with the Kappa statistics was also applied to see the relationship and inter-rater agreement between FRS and Globorisk scores. Moreover, the proportion of agreement between the two scores was also explored.

Results

During a seven-month survey from February 2022 to August 2022, a total of 1065 apparently healthy individuals underwent MetS screening, with 343 individuals testing positive. Since the FRS was developed for individuals aged 30–74 years, 39 patients aged <30 years were excluded from the study for 10-year CVD risk assessment using FRS. Similarly, as Globorisk was developed for individuals aged between 40 and 80 years, 119 patients aged <40 years were excluded from the study for 10-year CVD risk assessment using Globorisk Score. The inclusion of patients in this study is depicted in Figure 1, which shows a flowchart of the study’s patient selection process.

Figure 1 Flowchart showing inclusion of patients for 10-year CVD risk assessment using FRS and Globorisk scores. *MetS was confirmed using the definition of IDF.

The study participants included in FRS had a mean (SD) age of 46.60 (9.97) years, while those included in the Globorisk score had a mean (SD) age of 50.74 (8.15) years. Of the patients in FRS, 183 (60.2%) were male, while 135 (60.3%) were male in Globorisk score. Among the participants, only 74 (24.3%) in FRS were current smokers, while 60 (26.8%) in Globorisk score were current smokers (Table 1).

Table 1 Characteristics of the Patients Included in Framingham Risk Score and Globorisk Score

The 10-year CVD risk classification of FRS showed that out of 304 patients, 180 (59.2%) were observed to have low risk according to FRS, whereas moderate and high risks were observed in 62 (20.4%) each. Meanwhile, the 10-year CVD risk classification according to Globorisk score showed that of 224 patients, low CVD risk was observed in 100 (44.6%), moderate in 77 (34.4%), and high risk in 47 (21.0%) patients, as shown in Figure 2.

Figure 2 The 10-year CVD risk classification using Framingham and Globorisk Score.

Table 2 shows the agreement and correlation between the FRS and Globorisk score. The results indicate that the two CVD risk scores had moderate agreement and positive correlation. Specifically, the agreement between the FRS and Globorisk score was 67.85% (Kappa 0.501), indicating moderate agreement. Furthermore, a moderate positive correlation was observed between the two CVD risk scores (r = 0.651, 95% CI 0.58–0.71).

Table 2 Correlation Analysis and Agreement Between the Framingham Risk Score and GloboRisk Score

The study found significant differences in various parameters among different 10-year risk categories of FRS and Globorisk scores. For FRS, a significant increase in risk from low to high was observed with respect to the mean age (P < 0.001), weight (P < 0.001), height (P < 0.001), waist circumference (WC) (P < 0.001), fasting plasma glucose (FPG) (P < 0.001), and total cholesterol (TC) (P.008). While for Globorisk score, significant differences were observed in mean age (P < 0.001), height (P.002), WC (P < 0.001), SBP (P < 0.001), and FPG (P.040). These results are presented in Table 3.

Table 3 Mean Difference of Quantitative Predictors Variables with Framingham Risk Score and Globorisk Score

Furthermore, the study also found significant associations between the 10-year CVD risk according to FRS and several variables, including gender (P < 0.001), smoking status (P < 0.001), areca nut use (P.023), chew tobacco (P.009), current working status (P.001), number of MetS components (P < 0.001), high FPG (P < 0.001), and low HDL (P.007). Similarly, the 10-year CVD risk according to Globorisk score was significantly associated with gender (P < 0.001), smoking status (P < 0.001), and HTN (P.001). These associations were statistically significant (Ps < 0.05) for both risk scores and are summarized in Table 4.

Table 4 Comparison of Framingham Risk Score and Globorisk Score with Sociodemographic and Clinical Characteristics of Newly Diagnosed Individuals with Metabolic Syndrome

Discussion

The results of the present study indicate that nearly half of the newly diagnosed MetS patients were classified as having moderate to high-risk for developing CVD over a 10-year period using Globorisk whereas FRS predicted one-third of the study population in a moderate-to-high risk for MetS. The finding regarding underestimation of FRS is also reported in studies published previously in individuals with MetS and other diseases.^24–26 There could be several reasons why an individual’s risk score would be higher using the Globorisk score compared to the FRS. First, the FRS was developed based on data from a primarily white population in the United States, while the Globorisk score was developed using data from multiple countries and ethnic groups. It has been observed that South Asians exhibit genetic differences and a higher prevalence of most cardiovascular risk factors at a younger age.^27,28 Second, the Globorisk score includes additional risk factors such as smoking, diabetes, and BMI that are not included in the FRS.²² If an individual has one or more of these risk factors, their overall risk score would be higher using the Globorisk score.

The results of the current study indicate that the two CVD risk scores had moderate agreement and positive correlation. Specifically, the agreement between the FRS and Globorisk score was 67.85%, indicating moderate agreement. Furthermore, a moderate positive correlation was observed between the two CVD risk scores suggesting that the scores tended to increase or decrease together. These findings suggest that while there is some overlap between the FRS and Globorisk score in identifying patients at risk for CVD, they are not interchangeable and may provide complementary information. Previously published studies have also reported moderate relationship amongst different CVD prediction models.^29,30

The results of the present study reported that there is a significant association between several demographic and clinical variables and the risk of developing CVD over a 10-year period as determined by the FRS and Globorisk Score. Specifically, the study found that as the mean age, weight, height, WC, SBP, FPG, and TC of patients increased, so did their risk of developing CVD in 10 years. Moreover, male gender, current smokers, areca nut use, chewing of tobacco, no current working, higher number of components of MetS, high FPG, and low HDL are also significantly highly associated with risk of development of 10 years of CVD as predicted by both FRS and Globorisk scores. The variables that were identified as significant predictor variables in the current study have also been found to be significant in previously published studies.^3,4,31 This suggests that these factors may be important predictors of cardiovascular risk and should be closely monitored and managed in individuals with MetS to mitigate the risk of future CVD events. The findings also highlight the importance of early identification and intervention in individuals with MetS who have these risk factors to prevent the development of CVD.

The study has several limitations that need to be acknowledged. First, the study was limited to Karachi and did not consider other provinces in Pakistan, which limits its generalizability to the entire Pakistani population. Furthermore, the cross-sectional design of the study prevented long-term follow-up of patients, and a study with a follow-up period of at least 10 years, including disease reports and incidence, would provide a more comprehensive understanding of the development of CVD in this population. Another limitation is that the risk of CVD was calculated using predictive scores that did not take into account the family history of diabetes and CVD, both of which are strong predictors of long-term CVD risk. Finally, the study was community-based and did not offer counselling to individuals who were classified as having a moderate or high risk of developing CVD, which could have led to missed opportunities for lifestyle modifications and medication compliance.

Despite the aforementioned limitations, the study holds significant importance. Our study is the first, to the best of our knowledge, to comprehensively report on the 10-year prediction outcomes of CVD in newly diagnosed MetS patients. Although the study was conducted solely in Karachi, it included participants from diverse ethnic backgrounds and all major areas of the city, thereby increasing the gene pool of the study population and minimizing bias. Furthermore, individuals from all adult age groups were included in the study, which enabled the assessment of CVD risk in different age groups and identification of the age group most vulnerable to developing CVD in the future. The present study has brought to light the group of newly diagnosed MetS patients who are at a heightened risk of developing CVD in the future, underscoring the need for this population to be the focus of future research studies. Finally, a notable strength of this study is the comprehensive reporting of the correlation, inter-rater agreement, and proportion of agreement between the FRS and Globorisk scores in predicting the 10-year risk of CVD. This reporting is essential for evaluating the credibility and consistency of these two scales and for enhancing the accuracy of CVD risk predictions.

In terms of future research, it is recommended that studies similar to the present one be conducted more frequently in several cities and provinces to ensure that the study findings are generalizable to the entire Pakistani population. Additionally, interventions focused on lifestyle modification and counselling should be introduced and the outcomes analyzed through long-term follow-up to assess the effect of such modifications on MetS and its progression to complications, such as CVD.

Conclusion

In this study, the outcome of both CVD risk scores predicted moderate-to-high risk of CVD in 10 years in almost half of the newly diagnosed patients with MetS. In particular, the risk of development of CVD in 10 years in newly diagnosed MetS is higher with increasing age, in male gender, and current smokers as found in both FRS and Globorisk score. It is strongly recommended that the MetS who are at the old age category, males and smokers should be prioritised for healthy lifestyle counselling to prevent CVD events. They must follow strict compliance with the MetS therapeutic management and lifestyle modifications to reduce cardiovascular risk stratification in future. Moreover, the use of these CVD predicting risk scores in healthcare settings is also strongly recommended for all MetS patients.

Ethics Statement

The study was conducted in accordance with the Declaration of Helsinki and all procedures were approved by the Ethics Committee of Dow University of Health Sciences (IRB-2332/DUHS/Approval/2021/670). All participants received and signed an informed consent form.

Acknowledgments

The authors would like to thank the research assistants of Student Taskforce for Education & Public Health (STEP) of Primary Care Diabetes Association (PCDA) Pakistan who contributed by recruiting participants and assistance in data collection and entering of the data. Furthermore, we would like to thank all participants who took part in this study.

Funding

The study was supported by Sindh Higher Education Commission of Pakistan (Project code 299). In addition, PharmEvo Pakistan partially supported the logistics of this study. Furthermore, the University of Birmingham has provided support by covering the article processing charge for this paper.

Disclosure

Dr. Kashif Shafique, Mr. Syed Omair Adil and Dr. Fareed Uddin report grants from Sindh Higher Education Commission and PharmEvo Research Forum, during the conduct of the study. The author reports no other conflicts of interest in this work.

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