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 Table of Contents  
ORIGINAL ARTICLES
Year : 2021  |  Volume : 12  |  Issue : 2  |  Page : 172-175

Clustered metabolic approach using HbA1c, BP, and aortic augmentation index in type 2 diabetes as a tool for risk stratification


1 Hamdard Institute of Medical Sciences and Research, New Delhi, India
2 Sri Jayadeva Institute of Cardiovascular Sciences and Research, Bengaluru, Karnataka, India
3 North Delhi Diabetes Centre, New Delhi, India

Date of Submission06-Jul-2020
Date of Decision19-Sep-2020
Date of Acceptance29-Sep-2020
Date of Web Publication31-Mar-2021

Correspondence Address:
Dr. Rajeev Chawla
North Delhi Diabetes Centre, New Delhi.
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jod.jod_61_20

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  Abstract 

Materials and Methods: Functional vascular age in 2000 patients was assessed using cardiac risk profiler (vascular profiler-genesis), over a period of 3 years and 3 months between October 2016 and January 2020. The cardiovascular interpretations generated were used for the measurement of central arterial stiffness. The metabolically healthy groups were compared with the metabolically nonhealthy groups for the relevance of the triple co-association of HbA1c, arterial stiffness, and hypertension in screening the patients in regular standard care. The mean age of the patients was 53 years. Mann–Whitney test was used for the statistical analysis. Results: The mean age was 53.3 ± 12 years. HbA1c was <7% and >7% in 530 and 1470 patients, respectively. The lipid profile in comorbid scenario (n = 2000 [M = 1170 and F = 830]) revealed mean LDL-C mg/dL values of< 100, 100–150, >150 in 1380, 520, and 100 patients, respectively. A total of 1000 patients had the duration of diabetes <5 years, 380 patients were between 5 and 10 years, and 620 patients had been diabetic for>10 years, respectively. Arterial stiffness markers-Ankle Brachial Index and Carotid-Femoral Pulse Wave Velocity (CFPWV) were assessed and cluster analyses was performed using the metabolically healthy (HbA1c <7 and aortic augmentation index @ HR75 < 14 and nonhypertensive n = 50) as compared to the metabolically unhealthy cohort (HbA1c >7 and aortic augmentation index @ HR75 > 14 and with known hypertension (n = 230). The difference in the triple co-association of HbA1c (glycemic status), hypertensive status, and arterial stiffness was statistically significant when compared between the metabolically healthy (n = 50) vs. the metabolically nonhealthy cohort all across (n = 230) (P = 0.0457)Conclusion: The clustered metabolic marker approach is a tool to identify and stratify patients with diabetes based on the metabolic risk to prevent complications and possibly improve outcomes.

Keywords: Aortic augmentation index (AI), arterial stiffness, metabolic marker, metabolically healthy, metabolically nonhealthy, pulse wave velocity (PWV)


How to cite this article:
Chawla S, Trehan S, Chawla A, Jaggi S, Chawla R. Clustered metabolic approach using HbA1c, BP, and aortic augmentation index in type 2 diabetes as a tool for risk stratification. J Diabetol 2021;12:172-5

How to cite this URL:
Chawla S, Trehan S, Chawla A, Jaggi S, Chawla R. Clustered metabolic approach using HbA1c, BP, and aortic augmentation index in type 2 diabetes as a tool for risk stratification. J Diabetol [serial online] 2021 [cited 2021 Apr 20];12:172-5. Available from: https://www.journalofdiabetology.org/text.asp?2021/12/2/172/312667




  Introduction Top


Diabetes, hypertension, chronic renal impairment, atherosclerosis, and aging have a detrimental effect on the systemic vasculature leading to changes in vessel walls.[1] The co-association of diabetes and hypertension is known to increase the aortic stiffness and pulse pressure (PP).[2] This association is even stronger with the greater body weight and waist-hip ratio.[3] Arterial stiffness is known to have a direct relationship with the characteristic impedance of the vessels and hence the pulsatile component of the arterial afterload. Increased arterial stiffness increases systolic and PP, reduces diastolic pressure, and accelerates the timing of return of the reflected waves from the peripheral sites resulting in increased afterload, potentiation of the development of myocardial hypertrophy and worsening of coronary perfusion, thereby eventually leading to impairment of left ventricular diastolic function.[4] It is important to identify the risk factors early at an asymptomatic preclinical stage as well as timely screening and detection of vessel wall changes in mitigating the ensuing cardiovascular morbidity and mortality.[5] Markers of large artery stiffness such as PP, pulse wave velocity (PWV), and aortic characteristic impedance (Zc) have been widely studied. There has been an improvement in techniques that have enabled noninvasive assessment of these hemodynamic parameters

Rationale of the study

In the clinical setting, measurement of PWV as well as augmentation index (AI) are important tools for noninvasive assessment tools for arterial stiffness. PWV is acclaimed as an established noninvasive benchmark measure for arterial stiffness and denotes the velocity of pulse transmission time between two regional arterial points, including central (e.g., cardio-femoral, carotid-femoral) and peripheral (e.g., brachial-ankle and femoral-ankle) segments.[6]

AI is a measure of wave reflection and arterial stiffness and is expressed as a ratio calculated from the blood pressure waveform. It is commonly accepted as a measure of the enhancement (or augmentation) of the central aortic pressure by a reflected pulse wave [Figure 1].[7]
Figure 1: Central aortic blood pressure and augmentation index. Central aortic systolic blood pressure (cSBP) and definition of the augmentation index (AIx). P1 = AI was calculated from aortic pressure waveform as (second systolic peak–first systolic peak)/pulse pressure × 100.6 Radial AIx is ratio of P2 to P1. There is a linear relationship between heart rate and AIx; the AIx is standardized to a heart rate of 75b.p.m. (AIx-75)

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Objectives

We investigated the association of glycemic control (assessed as HbA1c) with aortic AI as a routine screening tool by using the arterial health analysis along with the cardiovascular risk analysis. We assessed and explored whether the clustering approach would be useful for risk stratification based on the vascular age and the glycemic levels


  Materials and Methods Top


The total patient population evaluated for functional vascular age were 2000 over a period of 3 years and 3 months between October 2016 and January 2020. The sample size was calculated by assuming the prevalence of diabetes at about 10%–14% and prediabetes around 14% with relative error of 20% at level of significance of 95%. The cardiovascular risk analyzer (vascular profiler-genesis) was used for the measurement of central arterial stiffness is a validated device for arterial stiffness estimation that has shown a high level of both intra-observer as well as inter-observer reproducibility in variable populations, including in patients with diabetes.[8] AI was calculated from aortic pressure waveform using the formula (second systolic peak–first systolic peak)/PP × 100.6. The metabolically healthy groups were compared with the metabolically nonhealthy groups for the relevance of the triple co-association of HbA1c, arterial stiffness and hypertension in screening the patients in regular standard care. The research was conducted in accordance with the Helsinki Declaration and the permission was granted by the independent ethics committee.

Measurement of central arterial stiffness was done by vascular profiler-genesis. This enabled the risk profiling of the patients, for the distribution of the entire cohort into two sub-groups. The cohort of 2000 patients were divided into two groups having HbA1c <7% (n = 530) and HbA1c >7% (n = 1470) [Figure 2].
Figure 2: Patient flow and characteristics

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We quantified the arterial stiffness in patients with diabetes, clustered them based on glycemic control to further understand the vascular health. As body mass index (BMI) was already accounted for in the machine used for the analysis, we did not capture separately the BMI and intended to work for the functional vascular age as derived by these reports

Mann–Whitney test was used for the statistical analysis.


  Results Top


The mean age of patients was 53 years (males 1170 and females 830). The mean LDL-cholesterol (LDL-C) values measured were <100 mg/dL, between 100and 150 mg/dL, and >150 mg/dL in 1380, 520, and 100 patients, respectively. The baseline characteristics are shown in [Table 1].
Table 1: Patient baseline characteristics

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Total cholesterol (TC) level was >150 mg/dL (n = 1320) and <150 mg/dL (n = 680).

A total of 1000 patients had diabetes duration less than 5 years preceding the screening and 380 patients were known diabetics >5 and <10 years and 620 patients were diabetics >10 years.

Of 2000 patients, there were 510 hypertensive and 450 patients were found to have peripheral neuropathy by bed side clinical examination as per validated NSS NDS Criteria and 190 were smokers.

The arterial stiffness markers were evaluated that included Ankle Brachial Index, Carotid-Femoral Pulse Wave Velocity (CFPWV) and Aortic AI. The cluster analyses was performed using the metabolically healthy (with HbA1c <7 and Aortic AI @ 75 < 14 and nonhypertensives n = 50) as compared to the metabolically unhealthy cohort (with HbA1c >7 and Aortic AI @ 75 > 14, along with hypertension n = 230). This distribution was chosen for the basis for the cluster analysis as this was the most representative of the entire group population.

The difference in the triple co-association of HbA1c (glycemic status), hypertensive status and arterial stiffness was statistically significant when compared among the metabolically healthy (n = 50) with the metabolically nonhealthy cohort (n = 230) (P = 0.0457).

As this was a cluster-based approach, we could not independently assess the relation of each of the factors.


  Discussion Top


We showed that the mean Aortic AI was related to glycemic status. Therefore, central arterial stiffness can be considered a surrogate marker for vascular damage induced by persistent hyperglycemia. As arterial stiffness can be increased even in individuals with pre-diabetes or impaired glucose tolerance as well as those with metabolic syndrome even before the onset of overt DM,[9] PWV and AI may be considered useful screening tools for early detection of vascular complications secondary to hyperglycemia. Aortic AI corrected for heart rate at 75 beats/min is a specific marker for arterial health evaluation and this correlated with the grade of glycemic control in our study.

Triple marker of HbA1c, blood pressure, and arterial stiffness as assessed by the aortic AI is a convenient and potentially useful screening tool to identify at risk patient groups that would require intensive and precise therapies in order to prevent complications and improve outcomes. Optimized glycemic control with targeted pharmacotherapy may further improve arterial stiffness indices and reduce co-morbidities.

Implications for the real-world practice

We recommend future studies looking at interventions that target arterial stiffness by means of lifestyle behavioral modification (i.e., documenting smoking, salt consumption) or pharmacotherapy that may prevent and or delay the progression of micro and macrovascular risk in patients with diabetes. Pragmatic approach by the physicians should entail an attentive approach to increased arterial stiffness, regardless of its severity which subsequently has been shown to increase vascular risk in diabetes patients. We suggest that as shown in other study, carotid femoral PWV may be considered as an important index of arterial stiffness and one of the markers for target organ damage.[5] The strength of our study lies in a relatively sizeable sample size as well as the use of robust techniques for assessment of arterial stiffness measuring both PWV (the gold standard) and AI (the surrogate index).

The study was limited due to the confounding effect of other cardiovascular risk factors that would have potentially influenced, the arterial stiffness and therefore mandate a cautious interpretation of our study findings. Even though the study was designed in a manner that did not enable us to exclude subjects with known macrovascular complications, the number of patients with these complications did not vary significantly between both groups.


  Conclusion Top


The clustered metabolic marker approach is a tool to identify and stratify the patients with diabetes based on the metabolic risk to provide intensive, targeted therapies that may be useful to prevent the complications and improve the outcomes. The study was limited for the fact that the parameters were clustered which did not permit us to develop a predictive model for the risk of diabetes. However, this study would help to formulate the basis for the future research to identify the population at risk and delineate the confounding variables so as to evaluate the future risk of the diabetes, even in the low-risk population.

Ethical policy and institutional review board statement

The study was conducted with the ethical principles mention in the Declaration of Helsinki (2013).

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Cockcroft JR, Wilkinson IB, Webb DJ The Trevor Howell Lecture: Age, arterial stiffness and the endothelium. Age Ageing 1997;26:53‐60.  Back to cited text no. 1
    
2.
Figueroa A, Maharaj A, Johnson SA, Fischer SM, Arjmandi BH, Jaime SJ Exaggerated aortic pulse pressure and wave amplitude during muscle metaboreflex activation in type 2 diabetes patients. Am J Hypertens 2020;33:70-6.  Back to cited text no. 2
    
3.
Aoun Bahous S, Thomas F, Pannier B, Danchin N, Safar ME Country of birth affects blood pressure in the French hypertensive diabetic population. Front Physiol 2015;6:248.  Back to cited text no. 3
    
4.
Dolan E, Thijs L, Li Y, Atkins N, McCormack P, McClory S, et al. Ambulatory arterial stiffness index as a predictor of cardiovascular mortality in the Dublin outcome study. Hypertension 2006;47:365-70.  Back to cited text no. 4
    
5.
Garcia-Ortiz L, Ramos-Delgado E, Recio-Rodriguez JI, Agudo-Conde C, Martínez-Salgado C, Patino-Alonso MC, et al; Vaso risk group. Peripheral and central arterial pressure and its relationship to vascular target organ damage in carotid artery, retina and arterial stiffness. Development and validation of a tool. The VASO risk study. BMC Public Health 2011;11:266.  Back to cited text no. 5
    
6.
Kim WJ, Park CY, Park SE, Rhee EJ, Lee WY, Oh KW, et al. The association between regional arterial stiffness and diabetic retinopathy in type 2 diabetes. Atherosclerosis 2012;225:237-41.  Back to cited text no. 6
    
7.
Shimizu M, Kario K Role of the augmentation index in hypertension. Ther Adv Cardiovasc Dis 2008;2:25-35.  Back to cited text no. 7
    
8.
Laugesen E, Rossen NB, Høyem P, Christiansen JS, Knudsen ST, Hansen KW, et al. Reproducibility of pulse wave analysis and pulse wave velocity in patients with type 2 diabetes. Scand J Clin Lab Invest 2013;73:428-35.  Back to cited text no. 8
    
9.
Prenner SB, Chirinos JA Arterial stiffness in diabetes mellitus. Atherosclerosis 2015;238:370-9.  Back to cited text no. 9
    


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