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INTRODUCTION
Cardiovascular Diseases (CVD) pose a huge global health and economic burden, they are the leading cause of death worldwide, and DM and its complications are responsible for the extremely high mortality rate associated with CVDs. Cardiovascular Diseases (CVD) are heart and circulatory system disorders (Francula et al., 2018). In India, CVD develops rapidly and is the primary cause of death for adults between the ages of 25 and 69 (Avinash et al., 2014). India comes at the 5th number in the global list of deaths caused by cardiovascular diseases (Jaspreet et al., 2020). A recent study states that the burden due to CVD in India is remarkably higher than what is being experienced at a global level. For example, the age-standardized death rate for CVD in India (282 deaths/100,000 (264-293)) was higher compared with global levels (233 deaths per 100,000 (229-236)) (Kalra et al., 2023). The majority of these deaths were attributable to heart attacks and strokes (Klimonto et al., 2021). Obesity, smoking, hypertension, gender, age, LDL cholesterol, diabetes, and a sedentary lifestyle are well-known risk factors for CVD development (Ghantous et al., 2020). A close link exists between CVD and DM, higher incidence of CVD in T2DM individuals (Ahmed et al., 2022) and, a cause of morbidity and mortality in diabetic patients (Leon et al., 2015). Diabetes Mellitus (DM) is a chronic disease caused by an inherited or acquired deficiency in insulin production by the pancreas or by the inefficiency of the insulin produced (Mahadeva et al., 2018). It can cause catastrophic damage to many of the body's systems, notably the neurons and blood arteries, which have been altered (Diabetes et al., 2022). It is estimated that almost three-fourths of individuals with DM2 die from CVD (Kavaric et al., 2018). According to the International Diabetes Federation (IDF), 415 million persons between the ages of 20 and 79 had diabetes in 2015, and 673 billion dollars were spent on treating the disease and its complications (Bilkis et al., 2021). With 1.3 billion people, India has the second-highest population in the world and the highest prevalence of diabetes (7.8%) (ADAD, 2005). Hence, prioritizing and controlling diabetic individuals with CVD risk factors is essential (Kalaivanan et al., 2017). More than 75% of instances of premature CVD reported to the World Health Organization (WHO) can be prevented, and associated risk factors can also be reduced (Nuhad et al., 2017). Elevated cardiac biomarkers are a typical indicator of the connection between T2D and CVD (Nuhad et al., 2017). Cardiac enzymes or biomarkers are released into the circulation upon injury or death of myocardial cells, and measurement of these enzymes or biomarkers in serum or plasma can aid in the diagnosis of cardiovascular diseases or other heart problems (Potter et al., 2009). However, several clinical biomarkers are currently associated with cardiovascular events that can only be used to identify patients at high risk and never prevent or predict an acute or fatal MI attack, which may be the first sign of Coronary Artery Disease (CAD) (Renuka et al., 2015). It is important to distinguish between heart attacks, heart failure, or other conditions that may have similar signs and symptoms because the treatment and monitoring requirements are different (Cardiac et al., 2015). In that way, single Natriuretic peptides (NT-Pro BNP, MR-Pro ANP) biomarkers play a crucial predictive role in CVD with TDM2. Natriuretic Peptides (NPs) are the enzymes that are released from the heart in response to pressure and volume overload (Cardiac et al., 2022). The NP level reflects a complication of systolic and diastolic function as well as right ventricular and valvular function (Daniels et al., 2007). As CVDs pose a huge global health and economic burden, they are the leading cause of death worldwide, and DM and its complications are responsible for an extremely high mortality rate associated with CVDs. Henceforth it can be used as both a diagnostic and prognostic marker in assessing the cardiac risk of developing MI in diabetic patients with asymptomatic CVD (Sarumathy et al., 2018). In addition, the United Kingdom Prospective for Diabetes Studies (UKPDS) the 10-year risk stratification tool is used to predict the CVD risk in type 2 diabetic patients. According to the United Kingdom Prospective for Diabetes Studies (UKPDS), a 0.9% decline in HbA1c results in trimming the risks for myocardial infarction by 14% (Hasan et al., 2020). Therefore, the UK Prospective Diabetes Study has the potential to determine improved blood glucose control which will be beneficial in preventing complications (UKPDS, 1991). This study summarizes the correlation between CVD and T2DM individuals with a focus on natriuretic peptides and their diagnostic and prognostic significance; we also attempted to provide a novel therapeutic strategy for employing UKPDS as a preventative tool.
OBJECTIVES
- To assess the correlation between natriuretic peptides (MR-pro-ANP and NT-pro-BNP) and cardiovascular risk in patients with type II diabetes.
- To study the correlation between demographic variables and cardiovascular burden in patients with type II diabetes.
- To assess the cardiovascular risk in patients with type II diabetes by using the 10-year risk stratification tool (UKPDS).
MATERIALS AND METHODS
Our study is a prospective observational study involving type II diabetic patients with CVD, conducted for 6 months and involving a sample size of 74 patients. The study was conducted at the Tertiary Care Hospital. Institutional approval has been taken to conduct this study.
Eligibility criteria
Inclusion criteria
Both males and females over 18 years old. All the type II diabetic patients with CVD and those who have natriuretic peptide test (MR-pro ANP, NT-pro BNP).
Exclusion criteria
Age below 18 years old, patients with type-I diabetes, pregnant women, and patients who were not willing to participate were excluded.
Data collection and design
Data were collected using a pre-structured patient data collection form based on inclusion and exclusion criteria. The following parameters were taken for the observation: lipid profile, blood sugar (FBS, PPBS, RBS, and HbA1C), levels of natriuretic peptides (MR-pro ANP, NT-pro BNP), 2DEchocardiography, history or events of CVD, patient demographic details, etc. The collected data were correlated based on the objective of the study. 10 years of cardiovascular risk assessment were performed using the UK Prospective Diabetes Study (UKPDS) tool.
Statistical analysis
Data were entered into Microsoft Excel and SPSS 23.00 Version was used for the statistical analysis. Descriptive statistics, the Mann-Whitney U test, and the Pearson correlation were used to identify the correlation relationship between two variables and the strength of that relationship.
A total of 74 patients were included in the study conducted at a tertiary care hospital during the study period.
The data shows a linear relationship between blood sugar (HbA1c) and UKPDS score, UKPDS score and natriuretic peptide (NT-Pro BNP), blood sugar (HbA1c) and natriuretic peptide (NT-Pro BNP, MR-Pro ANP), and age and natriuretic peptide (NT-Pro BNP, MR-Pro ANP).
The Mann-Whitney U Test is used to check the difference between two independent groups.
There is no statistically significant difference between gender and cardiac markers (pro-ANP, pro-BNP).
RESULTS
Association between HbA1c vs UKPDS 10 years cardiac risk score: The Correlation (Table 1) illustrates that there is a significant association between HbA1c and UKPDS 10 years cardiac risk score (p value=0.026).
| Variables | N | Correlation value | p Value |
|---|---|---|---|
| BloodSugar-FBS | 74 | -0.31 | 0.793 |
| UKPDS Score | 74 | ||
| BloodSugar-PPBS | 74 | 0.218 | 0.063 |
| UKPDS Score | 74 | ||
| BloodSugar-RBS | 74 | -0.01 | 0.93 |
| UKPDS Score | 74 | ||
| BloodSugar-HbA1C | 74 | 0.259 | 0.026* |
| UKPDS Score | 74 | ||
| BloodSugar-FBS | 74 | -0.175 | 0.136 |
| Cardiac markers-NT-Pro BNP | 74 | ||
| BloodSugar-PPBS | 74 | 0.163 | 0.165 |
| Cardiac markers-NT-Pro BNP | 74 | ||
| BloodSugar-RBS | 74 | 0.104 | 0.376 |
| Cardiac markers-NT-Pro BNP | 74 | ||
| BloodSugar-HbA1C | 74 | 0.276 | 0.017* |
| Cardiac markers-NT-Pro BNP | 74 | ||
| BloodSugar-FBS | 74 | 0.098 | 0.407 |
| Cardiac markers-MR-Pro ANP | 74 | ||
| BloodSugar- PPBS | 74 | ||
| Cardiac markers-MR-Pro ANP | 74 | -0.055 | 0.639 |
| BloodSugar-RBS | 74 | 0.078 | 0.506 |
| Cardiac markers-MR-Pro ANP | 74 | ||
| BloodSugar-HbA1C | 74 | 0.349 | 0.002** |
| Cardiac markers-MR-Pro ANP | 74 | ||
| UKPDS SCORE | 74 | 0.042 | 0.000** |
| Cardiac markers-NT-Pro BNP | 74 | ||
| UKPDS Score | 74 | 0.192 | 0.1 |
| Cardiac markers-MR-Pro ANP | 74 |
Association between HbA1c vs NT-Pro BNP: The correlation (Table 1) illustrates that there is a significant association between HbA1c and NT-Pro BNP (p value=0.017).
Association between HbA1c vs MR-Pro ANP: The correlation (Table 1) illustrates that there is a significant association between HbA1c and MR-Pro ANP (p value=0.002).
Association between UKPDS 10 years cardiac risk score vs NT-Pro BNP: The correlation (Table 1) illustrates that there is a significant association between UKPDS 10 years cardiac risk score and NT-Pro BNP (p value=0.000).
Association between UKPDS 10 years cardiac risk score vs MR-Pro ANP: The correlation (Table 1) illustrates that there is a significant association between UKPDS score 10 years risk score and MR-Pro score (p value=0.100).
Association between Age vs NT-Pro BNP: The correlation (Table 2) illustrates that there is a significant association between age and NT-Pro BNP (p value=0.044).
| Variables | N | Correlation value | p Value |
|---|---|---|---|
| DM | 74 | -0.022 | 0.852 |
| Cardiac markers-NT-Pro BNP | 74 | ||
| HTN | 74 | -0.195 | 0.097 |
| Cardiac markers-NT-Pro BNP | 74 | ||
| CVD | 74 | 0.24 | 0.040* |
| Cardiac markers-NT-Pro BNP | 74 | ||
| Age | 74 | 0.235 | 0.044* |
| Cardiac markers-NT-Pro BNP | 74 | ||
| BMI | 74 | 0.147 | 0.213 |
| Cardiac markers-NT-Pro BNP | 74 | ||
| DM | 74 | -0.055 | 0.642 |
| Cardiac markers-MR-Pro ANP | 74 | ||
| HTN | 74 | 0.116 | 0.325 |
| Cardiac markers-MR-Pro ANP | 74 | ||
| CVD | 74 | 0.04 | 0.734 |
| Cardiac markers-MR-Pro ANP | 74 | ||
| Age | 74 | 0.249 | 0.033* |
| Cardiac markers-MR- Pro ANP | 74 | ||
| BMI | 74 | 0.179 | 0.127 |
| Cardiac markers-MR-Pro ANP | 74 | ||
| UKPDS SCORE | 74 | 0.242 | 0.038* |
| CVD | 74 |
Association between Age vs MR-Pro ANP: The correlation (Table 2) illustrates that there is a significant association between age and MR-Pro ANP (p value=0.033).
Association between UKPDS 10years risk score vs CVD: The correlation (Table 2) illustrates that there is a significant association between UKPDS 10years risk score and CVD (p value=0.038).
Table 3 illustrates the association between gender and natriuretic peptides.
| Group | N | Mean Rank | Mann Whitney U | p value | |
|---|---|---|---|---|---|
| Cardiac markers-Pro BNP | Male | 74 | 39.09 | 520.5 | 0.358 |
| Female | 74 | 34.19 | |||
| Cardiac markers-Pro ANP | Male | 74 | 40.51 | 449.5 | 0.066 |
| Female | 74 | 31.23 |
DISCUSSION
Cardiovascular disease represents the major cause of death in subjects with T2DM. It is estimated that at most three-quarters of individuals with T2DM die from CVD. The Natriuretic peptides are a recognized diagnostic biomarker of CVD and a key factor in predicting death in individuals with T2DM. For predicting the future progression of CVDs in T2DM patients, UKPDS is a promising tool. More study is required for early detection of CVD in T2DM patients, which is still a rare aspect of research in the country. This study was conducted to assess the association between Natriuretic peptides and cardiovascular risk in T2DM patients and to evaluate the therapeutic value of NT PRO BNP in CVD.
Jesper Jensen et al., (2020) conducted a study in outpatients with type 2 diabetes (T2D), midregional pro-atrial natriuretic peptide (MR-pro ANP) is a helpful biomarker to identify Heart Failure (HF). Elevated B-type natriuretic peptides are used to define Heart Failure with preserved Ejection Fraction (HFpEF), but very little is known regarding the predictive benefit of incorporating A-type natriuretic peptides (MR-pro ANP) in the evaluation of T2DM patients.
Patients with T2DM and HFpEF who had high MR-pro ANP levels had an increased risk of CV events compared to patients with HFpEF who did not elevated MR-pro ANP and patients without HF, supporting the inclusion of MR-pro ANP in the definition of HFpEF from a prognostic point of view.
In our study, we assessed higher cardiovascular risk with elevating levels of NT PRO BNP and MR PRO ANP in patients with CVD AND T2DM.
Caterina Sujana et al., (2021) examined the correlations of N-terminal pro-B-type NP (NT-pro BNP) and mid-regional pro-atrial NP (MR-pro ANP) with type 2 diabetes distinguished by the appearance of CVD. NT-pro BNP and MR-pro ANP are inversely linked with incident type 2 diabetes. This study conducted Natriuretic Peptides and Risk of Type 2 Discussion Diabetes outcomes from the Biomarkers for Cardiovascular Risk Assessment. Finally, they concluded that both natriuretic peptides were inversely associated with incident type 2 diabetes.
From the study, we observed that the levels of NT-pro BNP and MR-pro ANP are inversely related to the occurrence of type 2 diabetes. However, the presence of CVD appears to alter the inverse association of NT-pro BNP.
Other than that, UKPDS (United Kingdom Prospective Diabetes Study) is found to be a significant tool for predicting the cardiovascular risk in T2DM. This aimed to determine the levels of 10-year CHD risk in type 2 diabetes using the UKPDS risk engine calculator.
Nebojsa Kavaric et al., (2018) conducted a similar study to estimate CVD risk by United Kingdom Prospective Diabetes Study (UKPDS) risk engine algorithm in individuals with T2DM, and the study concluded that high-sensitive CRP was not correlated with CVD prediction. In our study, it is explained that Natriuretic peptides are highly correlated with CVD risk stratification. In addition, our results are in line with previous studies showing an association between high natriuretic peptide levels and high blood glucose levels with an increased risk of CVD.
This study concluded that many of the cardiac biomarkers used clinically are late-stage biomarkers, indicating the presence of a CVD that has already developed. Identifying early-stage biomarkers of CVDs is of utmost importance in preventing these diseases from progressing and inducing their associated complications, hence the study proves that there is a significant correlation between Natriuretic peptides and Cardiovascular risk in T2DM patients in addition, UKPDS is used as a promising tool to predict 10-years risk of CVD.
CONCLUSION
Although several promising cardiac markers have been identified, it is unlikely that a single natriuretic peptide biomarker will unambiguously aid type 2 diabetes mellitus patients suffering from CVDs. The data shows a linear relationship between blood sugar (HbA1c) and UKPDS score, UKPDS score and natriuretic peptide (NT-Pro BNP), blood sugar (HbA1c) and natriuretic peptide (NT-Pro BNP, MR-Pro ANP), and age and natriuretic peptide (NT-Pro BNP, MR-Pro ANP). In conclusion, the study shows higher natriuretic peptide levels in type 2 diabetes mellitus are directly associated with cardiovascular risk.
