European Journal of Cardiovascular Medicine

Cardiovascular disease (CVD) is the commonest cause of death worldwide. In 2015, CVD accounted for 17.9 million deaths worldwide (32%) [1]. Coronary artery disease (CAD) results from interaction of many risk factors, environmental influence and genetic predisposition. Patients with history of CAD are at higher risk for subsequent cardiovascular events and require intensive risk reduction therapies to prevent it [2].

Endothelial and vascular smooth muscle dysfunctions are early abnormalities in atherosclerosis development in cardiometabolic disease. Diabetes is a significant risk factor for CVD due to elevated oxidant levels contributing to vascular dysfunction and impaired vasodilatory effect mediated through release of nitric oxide (NO) [3].

Endothelial function as assessed by Brachial artery Flow mediated dilatation (FMD); a non- invasive test has been impaired in patients of CAD according to several studies. FMD above 7.1% is significantly associated with lower risk of cardiovascular events in patients with history of CAD [2]. As diabetes has been CAD risk equivalent, this study is being done to correlate endothelial dysfunction in patients with and without diabetes mellitus and very few Indian studies have been done in this regard. Since all patients may not be able to undergo coronary angiogram, FMD may serve as an alternative to identify patients at high risk of CAD and initiate early and appropriate management.

OBJECTIVES

• To evaluate mean FMD value in patients of CAD with diabetes
• To evaluate mean FMD value in patients of CAD without diabetes
• To correlate endothelial dysfunction in diabetes mellitus patients through FMD and other target organ involvement.

Study Design and Duration:
This study employed a cross-sectional observational design and was conducted over a period of one and a half years, from January 2020 to June 2021.

Place of Study:

The study was performed at the Vydehi Institute of Medical Sciences and Research Centre, Bengaluru, India.

Source of Data:
Cases were selected from inpatients of the General Medicine and Cardiology departments at Vydehi Institute of Medical Sciences and Research Centre, Bengaluru, who satisfied the inclusion criteria.

Method of Collection of Data:
After obtaining approval and clearance from the Vydehi Institutional Ethics Committee, patients diagnosed with coronary artery disease (CAD) through ECG, 2D-ECHO, cardiac enzymes, or coronary angiography, with or without diabetes mellitus, were recruited. The ADA Diagnostic criteria for diabetes mellitus included FBS ≥ 126 mg/dl, PPBS ≥ 200 mg/dl, or HbA1C ≥ 6.5%. All subjects provided informed written consent, and data were collected using a standardized proforma that included history taking, treatment history, clinical examination, and relevant investigations.

Sample Size Estimation:
The sample size was calculated using the following formula:

where:

• σ = Standard deviation (4.9)
• Z_1−α/2 = 1.96 at 95% confidence interval
• Z_1−β = 0.84 at 80% power
• d = clinically significant difference (3)

The calculated sample size per group was 42 patients, leading to a total sample size of 84 patients, divided equally into diabetic and non-diabetic groups.

Inclusion Criteria:
The study included patients aged 18 years and above, both male and female, diagnosed with coronary artery disease based on ECG, 2D-ECHO, cardiac enzymes, or coronary angiography.

Exclusion Criteria:

Patients with specific conditions that could potentially confound the study outcomes were excluded to maintain the integrity of the findings. These conditions included hypertension, chronic kidney disease, and chronic liver disease, as these disorders could independently affect endothelial function and FMD values. Additionally, chronic smokers were excluded due to the established impact of smoking on vascular function and nitric oxide bioavailability. Patients with hypercoagulable disorders were also excluded to prevent complications related to vascular assessments. Furthermore, patients receiving vasodilatory drugs were excluded as such medications could interfere with the measurement of Flow Mediated Dilatation (FMD), potentially leading to misleading results regarding endothelial function.

Sampling Method:
Simple random sampling was employed to recruit patients who met the inclusion and exclusion criteria.

Methods
After obtaining informed written consent, patients diagnosed with CAD were categorized into diabetic and non-diabetic groups based on ADA Diagnostic criteria. A standardized proforma was used to collect demographic data, clinical history, treatment history, and relevant biochemical investigations.

Assessment of Flow Mediated Dilatation (FMD):

The assessment of Flow Mediated Dilatation (FMD) was conducted using a high-resolution ultrasound with a 7.5 MHz phased linear transducer probe by a qualified radiologist. Each participant was positioned in the supine position to ensure accurate measurement. A sphygmomanometric cuff was placed 5 cm below the antecubital fossa. The baseline brachial artery diameter, referred to as d1, was measured using the transducer probe prior to cuff inflation. Subsequently, the cuff was inflated to a pressure of at least 50 mmHg above the systolic blood pressure and maintained for five minutes to occlude arterial blood flow to the hand. Following cuff deflation, reactive hyperemia was induced, resulting in a transient increase in blood flow and shear stress on the endothelial cells of the brachial artery. The brachial artery diameter, referred to as d2, was then measured at one-minute post-deflation.

Calculation of Flow Mediated Dilatation (FMD):

The percentage change in brachial artery diameter due to reactive hyperaemia was calculated as the Flow Mediated Dilatation (FMD). The FMD percentage was determined using the formula:

where:
d1 denotes the baseline brachial artery diameter, measured before cuff inflation, and
d2 represents the brachial artery diameter measured at one minute after cuff deflation.

Endpoints/Outcome Measures:
The primary outcome measure was the comparison of mean FMD values between the diabetic and non-diabetic groups in patients with coronary artery disease.

Statistical Analysis:
Data collected were analysed using SPSS version 21. Continuous variables were expressed using mean and standard deviation. Independent sample t-test was performed to compare mean FMD values between diabetic and non-diabetic patients. Chi-square analysis was used to assess the correlation between FMD and diabetes status.

Age wise distribution:

A total 84 cases were considered for the study, the age wise classification was done based on mean and SD values. Logistic regression was employed to test the hypothesis. The mean age was 53.81 with SD of 9.52 years. Maximum and minimum age was 76 and 28 years respectively. Majority of the cases fall in the age group between 50-59 years (50%) followed by the 60-69 years (22.6%) and 40-49 years (19%).

Gender wise distribution

Gender wise distribution shows males were 67 (79.76%) and females were 17 (20.24%) with Sex ratio 1:4. Males were predominant as compared to females.

Gender distribution of diabetics and non-diabetics

The gender distribution of DM and non-DM patients shows that males were more predominant than females in both the groups.

Distribution of duration of diabetes mellitus (DM)

Mean duration of DM was tested by logistic regression analysis, where majority of patients (47.6%) fall into the duration group of 0-3.9 years followed by 30.9% in 4-7.9 years group. Overall mean duration of diabetes was 4.91 with SD 1.22 years, IQR 0-15.9 years.

Figure 1: Severity of CAD

The severity of CAD was tested by paired t- test in a total of 84 cases. Among three groups, SVD cases were the highest with 46 (54.76%), followed by DVD with 28 cases (33.33%) and TVD with 10 cases (11.90%).

Figure 2: Distribution of HbA1c

Fig 2 depicts the descriptive statistics of HbA1c distribution of 42 diabetic patients, where majority of patients, 18 (42.85%) were having HbA1c values between 6.4-7.89 % followed by 11(22.40%) patients in 7.9 - 9.39% and 7 (14.30%) patients were in 4.9 - 6.39% range.

Figure 3: Distribution of Total Cholesterol

The descriptive statistics of total cholesterol distribution, majority of patients fall in the total cholesterol values between 160 - 189 mg/dL- 30(35.70%) followed by - 22(26.20%) in 190 – 219 mg/dL and 16 (19.0%) in 130 – 159 mg/dL. The mean total cholesterol was 174.45±34.19, IQR 104-264 and median was 175.

Table 1: Mean HDL and LDL levels in relation to severity of CAD

Fundoscopy distribution

Fundoscopy distribution, among 84 patients, 11 (13.095%) had Mild NPDR, 2 (2.381%) patients had moderate NPDR and rest 71 (84.54%) patients had no retinopathy changes on fundoscopy.

Table 2: Brachial artery baseline diameter (BAD1) distribution

Table 3: BAD2 distribution

FMD % distribution

The distribution of FMD (%) is presented as 34 (40.50 %) patients fall into the range between 4 - 7.99 %, 27 (32.10 %) patients fall in range 8 - 11.99%; and 13 (15.50%) patients in 12 - 15.99 %.

Table 4: Association between severity of CAD and Diabetes

The significance of SVD, DVD and TVD in diabetes was tested by chi-square test. The present study shows SVD was seen in 26 (56.52%) non-DM patients and 20 (43.48%) diabetic patients, DVD was seen in 15 non diabetic cases (53.58%), and 13 (46.42%) in diabetics and TVD was seen in 9 (90%) diabetic cases. The association of severity of CAD with T2DM showed that involvement of TVD was more in diabetic patients than in non-diabetic patients compared to SVD and DVD, which was found to be statistically significant(p<0.02).

Table 5: Significance of biochemical parameters in relation to diabetes

In table 5, the significance of diabetes and non diabetes was tested by using unpaired t –test, among which increased creatinine, FBS, PPBS, TG and reduced FMD (%) was found to be statistically significant with respect to diabetes (p<0.01).

Table 6: Descriptive statistics of various parameters with respect to diabetes and non-diabetes

Association of mean FMD % with severity of CAD

According to Table 6, the mean FMD was found to be highest in patients with SVD (9.43± 4.48%) followed by DVD – 8.55± 2.83 % and lowest in patients with TVD (5.707± 1.93%), which indicates that endothelial dysfunction increases with involvement of multiple vessels.

Table 7: Association of mean FMD % in diabetes and non-diabetes

Figure 4: Association of mean FMD in diabetic and non-diabetic patients

The mean FMD was 5.878 ±2.03% (p<0.001) in diabetic group and 11.51±3.27% in non-diabetic group, suggesting increased endothelial dysfunction was seen in diabetes patients than in non-diabetic patients with known CAD.

Table 8: Association of FMD (%) with diabetes

Endothelial function as assessed by brachial artery flow mediated dilatation (FMD); a non- invasive test has been impaired in patients of CAD according to several studies, where lower FMD was associated with increased endothelial dysfunction. FMD above 7.1% is significantly associated with lower risk of cardiovascular events in patients with history of CAD. According to Table 8 among 84 patients of CAD, 35 patients (41.6%) had FMD <7.1% which suggested an increase in endothelial dysfunction in these patients, with higher risk of future cardiovascular events. Out of 42 diabetic patients, 33 patients (78.5%) patients had FMD <7.1% and 2 patients (4.76%) out of 42 non-diabetic patients had FMD <7.1%, indicating endothelial dysfunction as assessed by FMD was more common in diabetic patients with CAD than non-diabetic patients with CAD, which was found to be statistically significant.

Coronary artery disease (CAD) arises from the interplay of multiple risk factors, environmental influences, and genetic predispositions. Patients with a history of CAD are at an increased risk for subsequent cardiovascular events and thus require intensive risk reduction therapies to prevent further complications. Diabetes is a significant risk factor for cardiovascular disease, contributing to vascular dysfunction and impaired vasodilatory response through elevated oxidant levels that affect nitric oxide-mediated vasodilation. Given that diabetes is considered to be a CAD risk equivalent, this study aimed to correlate endothelial dysfunction in patients with and without diabetes mellitus using Flow Mediated Dilatation (FMD), a simple, non-invasive technique.

The present study investigated FMD in CAD patients, examining its association with diabetes and endothelial dysfunction. The study population consisted of patients aged 18 to 70 years, with a mean age of 53.81 years (SD 9.52 years). The majority of the participants (50%) were in the age group of 50–59 years, followed by 22.6% in the 60–69 years range, and 19% in the 40–49 years range. Males constituted 79.7% (n=67) of the participants, whereas females accounted for 20.2% (n=17), indicating a male predominance in the study population.

In this study, a total of 84 CAD patients were enrolled, evenly divided between diabetics and non-diabetics. The diabetic group demonstrated a significantly lower mean FMD of 5.87% (SD 2.03%) compared to the non-diabetic group, whose mean FMD was 11.51% (SD 3.27%), with a p-value of <0.001. This finding suggests a greater degree of endothelial dysfunction in diabetic CAD patients than in non-diabetic CAD patients, supporting the hypothesis that diabetes is independently associated with impaired endothelial function.

Supporting evidence was provided by a study conducted by Reyes-Soffer et al., which included 103 CAD patients, of whom 52 had Type 2 Diabetes Mellitus (T2DM). The mean FMD in CAD patients with T2DM was 3.9% (SD 3.2%), significantly lower than the mean FMD of 5.5% (SD 4.0%) observed in CAD patients without T2DM (p<0.03). This study also demonstrated that the presence of T2DM was independently associated with greater endothelial dysfunction, emphasizing the relevance of monitoring FMD in diabetic CAD patients [4].

A similar study by Hiroyuki Ito et al. measured FMD in 480 T2DM patients and 240 non-diabetic subjects with and without coronary heart disease (CHD). The FMD was significantly lower in diabetic patients with CHD (5.6% ± 2.8%) than in non-diabetic patients without CHD (6.9% ± 3.5%), reinforcing the notion that diabetes exacerbates endothelial dysfunction in CAD patients. The study also noted a significant correlation between FMD and estimated glomerular filtration rate (eGFR) in diabetic patients without CHD, a finding that aligns with our study’s observation of increased creatinine levels correlating with reduced FMD [5].

Bhargava K et al. conducted a study involving 198 individuals categorized into four groups based on CAD and diabetes status. The mean FMD was significantly higher in patients without CAD or diabetes (7.03% ± 2.87%) than in those with CAD or diabetes alone or in combination, with FMD values ranging from 4.26% to 5.51%. This study concluded that diabetes is associated with endothelial dysfunction comparable to that seen in CAD patients, establishing diabetes as a CAD risk equivalent. Our study similarly observed that 78.57% of diabetic CAD patients had FMD values below 7.1%, compared to only 4.7% in the non-diabetic group [6].

In a study conducted by Mahendra Chouhan et al., patients with CAD were divided into two groups based on FMD values. Those with FMD <7.5% exhibited significantly greater endothelial dysfunction (mean FMD 6.87% ± 5.48%) than those with FMD >7.5% (13.08% ± 3.40%) [7]. In our study, the mean FMD values were 9.43% ± 4.48% in patients with single vessel disease (SVD), 8.55% ± 2.83% in those with double vessel disease (DVD), and 5.707% ± 1.93% in patients with triple vessel disease (TVD), suggesting a progressive decline in endothelial function with increasing severity of CAD.

The correlation of FMD with blood biomarkers was evaluated in a study by Nivedita Muzalda et al., which demonstrated that FMD% was inversely related to lipid profile (r= -0.16, p<0.02) and HbA1c levels (r = -0.51, p<0.00001). In our study, significant associations were noted between FMD and biochemical parameters such as creatinine, fasting blood sugar (FBS), postprandial blood sugar (PPBS), and triglycerides, with p-values of <0.001 in diabetic patients. However, no significant correlations were found with HbA1c, total cholesterol, LDL, and HDL levels [8].

In a study conducted by G. S. Sainani, the endothelial function assessed by FMD was found to be similar in diabetic patients without CAD and non-diabetic CAD patients, indicating that diabetes poses a CAD risk equivalent [9]. Similarly, our study found comparable FMD impairment in diabetic CAD patients and non-diabetic CAD patients, reinforcing the relevance of FMD as a diagnostic marker of endothelial dysfunction in diabetes.

A study by Pijush Kanti Mandal et al. evaluated the impact of confounding factors such as BMI, smoking, and hypertension on FMD in diabetic patients. The study reported significantly lower FMD values in diabetic patients with additional risk factors, such as smoking and obesity, with FMD values of 4.13% ± 0.59% in smokers and 3.72% ± 0.44% in patients with BMI > 30. Our study also noted lower FMD values in diabetic patients with elevated BMI and other comorbid conditions, though statistical significance was not established [10].

The relationship between FMD and cardiovascular outcomes was further explored by Andrzej Bissinger et al., who assessed FMD in 93 patients with acute coronary syndrome (ACS). Diabetic patients with ACS had significantly lower FMD values (5.8% ± 2.2%) than non-diabetic ACS patients (8.8% ± 4.9%), a pattern consistent with the findings of our study [11].

The findings of our study align with existing literature, emphasizing the role of FMD as a reliable marker of endothelial dysfunction in diabetic CAD patients. Despite the lack of multivariate analysis to account for confounding variables, the study underscores the clinical utility of FMD as a simple, cost-effective, and non-invasive diagnostic tool for identifying high-risk CAD patients, particularly those with diabetes.

STRENGTHS:

The study employed brachial artery FMD assessment using USG Doppler, a non-invasive, cost-effective, and time-efficient technique with proven repeatability. Early detection of endothelial dysfunction in diabetic patients may facilitate timely interventions to mitigate future CAD events.

LIMITATIONS:

The study did not perform multivariate analysis to account for all cardiovascular risk factors, potentially influencing FMD outcomes. Additionally, the duration of CAD post-diagnosis was not documented, which could impact FMD values. The influence of ongoing medical therapy on FMD was not evaluated, limiting the generalizability of the findings. Furthermore, the study sample size was limited, necessitating larger prospective studies to validate these findings.

Diabetes is recognized as a CAD risk equivalent due to its association with significant endothelial dysfunction. The present study demonstrated that FMD values were significantly lower in diabetic CAD patients than in non-diabetic CAD patients, indicating greater endothelial impairment in the former group. These findings are consistent with previous studies that emphasize the impact of diabetes on vascular function. Given its non-invasive, simple, and cost-effective nature, FMD may serve as an important screening tool for identifying patients at high risk of CAD, especially those unable to undergo invasive diagnostic procedures such as coronary angiography. Early identification of endothelial dysfunction through FMD may facilitate timely intervention and prevent adverse cardiovascular outcomes in diabetic CAD patients.

1. Jameson JL, Fauci AS, Kasper DL et al eds. Harrison’s principles of internalmedicine, 20e. New York,NY: McGraw-Hill;2018:1662-1663.
2. Maruhashi T, Soga J, Fujimura N, Idei N, Mikami S, Iwamoto Y, et al. Endothelial dysfunction, increased arterial stiffness, and cardiovascular risk prediction in patients with coronary artery disease: FMD-J (flow-mediated dilation Japan) study A. J Am Heart Assoc. 2018;7(14).
3. Walther G, Obert P, Dutheil F, Chapier R, Lesourd B, Naughton G, et al. Metabolic syndrome individuals with and without type 2 diabetes mellitus present generalized vascular dysfunction: Cross-sectional study. Arterioscler Thromb Vasc Biol. 2015;35(4):1022–9.
4. Reyes-Soffer G, Ginsberg HN, Berglund L, Duell PB, Heffron SP, Kamanna VS, et al. Endothelial function in individuals with coronary artery disease with and without type 2 diabetes mellitus. Metabolism. 2010;59(10):1365–71.
5. Ito H, Nakashima M, Meguro K, Furukawa H, Yamashita H, Takaki A, et al. Flow mediated dilatation is reduced with the progressive stages of glomerular filtration rate and albuminuria in type 2 diabetic patients without coronary heart disease. J Diabetes Res. 2015;2015:728127.
6. Bhargava K, Hansa G, Bansal M, Tandon S, Kasliwal RR. Endothelium-dependent brachial artery mediated vasodilation in patients with diabetes mellitus and without coronary artery disease. J Assoc Physicians India. 2003;51:355–8.
7. Chouhan M, Mandloi SS, Kansal A, Jatav OP. To study the endothelial dysfunction by brachial artery flow mediated dilatation in coronary artery disease patients. Int J Adv Med. 2017;4(4):1158–64.
8. Muzalda N, Arora R, Tiwari S. Study of endothelial dysfunction in type 2 Diabetes Mellitus by brachial artery flow dilatation using linear probe 2D ultrasound. Int J Health Clin Res. 2020;3(9):155–8.
9. Sainani GS. Endothelial Cell Dysfunction in Assessment (ECD) of Diabetes Mellitus (DM) as an Equivalent of Coronary Artery Disease (CAD). JSM Heart Surg Case Images. 2016;2(1):1010.
10. Mandal PK, Ghosh S, Saha D. A study of endothelial dysfunction in diabetic patients in rural India. Asian J Med Res. 2015;4(3):239–42.
11. Bissinger A, Rozentryt P, Krzemińska-Pakuła M, Gąsior M, Kalarus Z. Endothelial function and left ventricular remodeling in diabetic and non-diabetic patients after acute coronary syndrome. Med Sci Monit. 2011;17(2):CR73–7.