European Journal of Cardiovascular Medicine

Diabetes mellitus is a group of metabolic diseases specified by hyperglycemia resulting from defects in insulin secretion, insulin action, or both⁴. The assessment of glycemic control is of foremost importance because of its key role in the management of T2DM. Diabetics with poor glycemic control have unfavourable effects on the life expectancy and quality of life mostly because of its complications and late detection. Glycated hemoglobin (HbA1c) has been considered as a good indicator of overall glycemic control and possible risk for long-term complications of DM. Although it is validated, however, laboratory determinations of plasma HbA1c are yet not widely available and standardized in all services in addition to its high cost². Recent evidence has suggested that calculated measure incorporating triglyceride and glucose, termed “TyG index” which is nothing but ‘triglyceride glucose index’ has been suggested to help as surrogate marker for insulin resistance⁵. Triglyceride glucose (TyG) index is a novel marker for metabolic disorders and recently it has been reported to be associated with cardiovascular disease (CVD) risk in apparently healthy individuals. Tyg index was firstly studied as a marker of identifying insulin resistance with a high sensitivity and specificity.

It was demonstrated that TyG index was a useful predictor of type 2 diabetes and metabolic syndrome which contributed to cardiometabolic risk. Metabolic syndrome over the years has structured definitions to classify an individual with the disease. Literature review suggests insulin resistance is hallmark of these metabolic clustering. While measuring insulin resistance directly or indirectly remains technically difficult in general practice, along with multiple stability issues for insulin, various indirect measures have been suggested by authorities. Fasting triglycerides-glucose (TyG) index is one such marker, which is recently been suggested as a useful diagnostic marker to predict metabolic syndrome. Despite the potential of the TyG index, limited data is available on the subject with almost no literature from Indian population on the subject.

Establishing the reliability of the TyG index as a surrogate marker could provide a valuable tool for T2DM management in resource-limited settings. Its ease of calculation and affordability could lead to wider accessibility and more frequent monitoring of glycemic control, potentially improving patient outcomes.

Aims and Objectives:

Aim: To evaluate the potential role of TyG index as a surrogate marker of glycemic control in patients with type 2 diabetes mellitus.

Objectives:

1. To compare and correlate the TyG index and HbA1c values.

This retrospective study was conducted at St. John’s Medical College Hospital after obtaining approval from the institutional ethics committee (IEC Study Ref.No.396/2019). Data of a total of 197 samples were collected. All patients with T2DM in whom HbA1C, FBS and Lipid profile had been requested as a part of their routine Diabetic work up and reports available around the same time period were included in this study and those in whom the glycated hemoglobin values had unknown peaks, had incomplete reports or with values on compromised samples were omitted.

The patients were divided into two groups based on their HbA1C as HbA1C ≤7 (n=27) and HbA1C≥7 (n=170). Of the subjects recruited for the study, data of HbA1c, FBS, TC, HDL, LDL, TG were noted. Further TyG Index was calculated as ln [ (TG x FBS)/2] (ln is the natural log). Descriptive statistics was used for all data and suitable statistical tests of comparison were done. All data were presented as mean ± SD. Independent samples t-test (2-tailed) was used to compare means of different parameters. Pearson's correlation test was performed to assess correlations between different parameters. Statistical significance was taken as P < 0.05. The data was analysed using R software. Microsoft Excel 2020 was used to generate charts.

This study encompassed 197 patients who fulfilled the inclusion criteria, of which 107 were males followed by 90 females. Mean age of this study population was 54.16yrs. HbA1C was used as the marker for glycemic control.

On the entire dataset, Pearson’s correlation coefficients were applied to establish the correlations between glycated hemoglobin and all the study parameters. As shown in Table 1, TC, LDL and TG had a significant but weak correlation with HbA1c. FBS and TyG index had a moderate correlation with HbA1c with FBS being the strongest. HDL did not have a correlation with HbA1c.

Table 1: Association of HbA1C with study parameters: correlation coefficient (95% CI)

The subjects were then divided into 2 groups based on their HbA1c levels. We had 27 patients with HbA1c < 7% and 170 with HbA1c > 7%. As shown in Table 2, difference between TG, TC, HDL, and LDL level between the study groups were not significant. Patients in the HbA1c ≥ 7% group had significantly higher values of FBS and TyG compared to patients in HbA1c < 7% group.

Table 2: Baseline characteristics of study parameters in the 2 groups.

 Data presented as Mean ± SD. p value <0.05 is considered significant.

Table 3: Correlation coefficient with 95% Confidence interval

FBS and TyG had a moderate correlation with HbA1c. Scatter plot (graph 4 & 5) shows the correlation of HbA1c with FBS and TyG index.

Graph 1: Lipid profile baseline characteristics

In the current study we evaluated whether TyG index correlates with long term glycemic control in terms of HbA1c in type 2 diabetic patients and its possible use as a surrogate marker of glycemic control. Guerrero-Romero et al. proposed that TyG index could be a marker of IR with an excellent correlation with the gold standard euglycemic-hyperinsulinemic clamp test⁶. Several studies have proposed the use of TyG index to predict the occurrence of type 2 DM, several possible mechanisms have been suggested to explain the correlation between TyG index and glycemic control. Increased triglyceride levels can lead to increased free fatty acids and, thus, increased flux of free fatty acids from adipose to non-adipose tissue, which may affect the glycemic control. Many studies have confirmed that higher levels of triglycerides in the liver and muscle may affect glucose metabolism in each target organ². Many individuals with diabetes who have poor glycemic control experience a dyslipidemic state such as an increase in triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and a decrease in high density lipoprotein cholesterol (HDL-C). In addition, low density lipoprotein cholesterol (LDL-C) is converted to small, dense LDL that is more atherogenic. Increased free fatty acid flux secondary to insulin resistance and increased proinflammatory adipokines and cytokines from enlarged adipose tissue may also be the underlying determinants of this interrelationship³.

It was observed that TyG index among the two divided groups was significantly higher in HbA1c ≥7% group compared to HbA1c <7% group (5.0354 ± 0.3132 vs. 4.8721 ± 0.2605; p 0.006). TyG index had a significant correlation with HbA1c in the group with HbA1c ≥ 7 with a correlation coefficient of 0.45(0.32,0.56). This is in accordance with Babic et al.⁴, NMK Selvia⁸ Laverdy et al.³⁴.

The rationale to use the TyG index in the clinical setting is that it is routinely measured, easy, cost effective and reflects many cardiometabolic risk factors. Since the measurement of HbA1c is expensive, and not available in most laboratories of the hospitals in rural areas, an alternative test that is inexpensive and routinely available is required to provide the opportunity for follow up of long term glycemic among these individuals. HbA1C levels vary not only according to glycemia, but also to conditions resulting in increased erythrocyte turnover rates (e.g., hemoglobinopathies, malaria, anemia, blood loss). In these individuals, monitoring of glycemic control will not be possible with HbA1c.

We conclude that TyG index can be used to assess glycemic status in patients with HbA1c ≥7 and with other disorders that affect HbA1c estimation or in settings where estimation of HbA1c is not feasible due to unavailability or financial constraints.

A limitation of the present study is that it is a cross-sectional study. Hence, we cannot draw any cause-effect relations between our results. Higher sample size with more samples with <7 HbA1c would have given more accurate and reliable results.

Funding source: Not availed.

Conflict of interest: The authors have no conflict of interest.

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