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Table of Contents
ORIGINAL ARTICLE
Year : 2022  |  Volume : 11  |  Issue : 3  |  Page : 138-143

Prediabetes in acute coronary syndrome


Department of Medicine, Kasturba Medical College, Manipal Academy of Higher Educatioin, Manipal, Karnataka, India

Date of Submission23-Jan-2022
Date of Decision17-Feb-2022
Date of Acceptance21-Feb-2022
Date of Web Publication08-Jun-2022

Correspondence Address:
Sudha Vidyasagar
Professor, Department of Medicine, Kasturba Medical College, Manipal Academy of Higher Educatioin, Manipal, Udupi 576 104, Karnataka
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jcsr.jcsr_13_22

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  Abstract 


Background: There is increasing evidence that cardiovascular disease risk starts rising from the stage of prediabetes. Our aim was to study the relationship of prediabetes with coronary artery disease (CAD) severity and whether the degree of glycaemia impacts the severity of CAD.
Methods: In this cross-sectional study patients admitted with acute coronary syndrome (ACS) who had impaired fasting glucose (IFG) were studied. Coronary angiography (CAG) severity was calculated using Gensini scoring system. Their glycaemic status was reclassified and reanalysed after 1 month using oral glucose tolerance test. Glycaemic status was then correlated with CAD severity.
Results: Of the 140 patients studied, at 1 month follow-up, only 94 persisted in the IFG category; Stress hyperglycaemia (SH) was evident in 32.8%. A moderate positive correlation (0.4) was observed between Gensini score and 2h PPG as compared to that with FBS (0.18) and glycosylated haemoglobin (HbA1c) (0.1). Multiple linear regression showed only 2h postprandial blood glucose (2h-PPBG) had a significant correlation with Gensini score (adjusted odds ratio 1.006).
Conclusions: SH, being a major confounding factor during acute coronary events, demands revisiting patients' glycaemic status after 1 month for correct classification. Significant correlation was found between CAD severity and IGT. This highlights the importance of assessing 2h-PPBG in predicting the risk of macrovascular complications like ACS even in prediabetic individuals.

Keywords: Acute coronary syndrome, fasting plasma glucose, gensini score, impaired fasting glycaemia, prediabetes


How to cite this article:
Chaitanya G B, Vidyasagar S, Nandakrishna B, Muralidhar Varma D M, Holla A. Prediabetes in acute coronary syndrome. J Clin Sci Res 2022;11:138-43

How to cite this URL:
Chaitanya G B, Vidyasagar S, Nandakrishna B, Muralidhar Varma D M, Holla A. Prediabetes in acute coronary syndrome. J Clin Sci Res [serial online] 2022 [cited 2022 Aug 12];11:138-43. Available from: https://www.jcsr.co.in/text.asp?2022/11/3/138/347033




  Introduction Top


The major long-term consequences of diabetes are all vascular. While the microvascular complications are directly related to glycaemia, the macrovascular ones are multifactorial, and can result in acute vascular events such as myocardial infarction (MI) and strokes. These are hence the most important causes of morbidity and mortality. The prevalence of coronary artery disease (CAD) is increasing in diabetes patients in India also. Diabetes mellitus is considered to be a cardiovascular risk equivalent, as the morbidity and mortality are equal to that of patients with prior ischaemic heart disease (IHD).[1]

There has been an opinion about glycaemia being a continuous risk for CAD, even below the diabetes threshold. Prediabetes, both in the fasting and post-glucose load criteria, is known to predispose to cardiovascular disease (CVD) risk[2] as evidenced by landmark studies like Framingham heart study and many other studies.

We undertook this study, in non-diabetic patients admitted with the acute coronary syndrome (ACS) to our hospital, to estimate the relationship between CAD severity and glycaemic status. We focused on patients with prediabetes admitted with ACS, to study if their glycaemia impacted the severity of their CAD.


  Material and Methods Top


This was a cross-sectional study on 140 patients aged 18 years and above diagnosed with ACS (defined as per American Heart Association [AHA] guidelines 2014) who come under impaired fasting glucose (IFG) category (according to American Diabetes Association [ADA] guidelines 1997, 2003)[3],[4] admitted in the Department of Cardiology, Kasturba Hospital, Manipal.

The study was conducted after obtaining the Institutional Ethics Committee approval as per the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Written informed consent was obtained from all individual participants included in the study.

Patients known diabetics had stable coronary artery disease, or had recurrent myocardial infarction, renal dysfunction, those on steroids, those who had chronic liver dysfunction or had any active infection were excluded from the study. Based on the pilot study, the anticipatory prevalence of prediabetes (IFG) in ACS was 40% and considering relative precision of 20% and 95% confidence level, the minimum sample size was 140.

Height and weight of the recruited patients were measured and body mass index (BMI) was calculated. Family history of diabetes and heart disease (in first-degree relatives) was noted. A detailed history was taken regarding their medical illness and habits.

Patients underwent complete assessment considering all their associated comorbidities. Routine biochemical tests were performed.

ACS was diagnosed based on AHA guidelines 2014[5],[6] All these patients diagnosed with ACS underwent coronary angiography and the severity of the CAD was calculated using Gensini score. Gensini score takes into account the degree of stenosis in different coronary vessels and also gives higher scores for the involvement of the main arteries (left main coronary artery involvement gets the highest score of 5).[7] All patients were followed up at the end of 1 month. Patients were reclassified at 1 month follow-up based on their glycaemic status by performing fasting plasma glucose (FPG) and 2 h Post-prandial following 75 g oral glucose tolerance test (OGTT). This was done to avoid misclassifying patients at the time of ACS, because of stress hyperglycaemia (SH).

After reanalysing and classifying the sugars at 1 month follow-up, the degree of glycaemia was then correlated with the angiographic severity of the disease using Gensini scoring.

FPG and post-prandial glucose (PPG) were measured using automated auto analyzer Hitachi P800. The coefficient of variation was <2% and <5% for intra- and inter-batch, respectively, HbA1c was measured-high-performance liquid chromatography method Ion exchange based method (National Glycohaemoglobin Standardisation Programme certified). Gensini score was calculated based on the coronary angiography findings and this was carried out by a cardiologist, who was blind to other parameters of the patients.

Statistical analysis

As Gensini scores are not normally distributed data are presented as median with interquartile range. Non-parametric Kruskal-–Wallis was performed to compare the median Gensini scores between normal, prediabetic and diabetes mellitus patients. Mann-Whitney U-test was done to test between NGT and IGT groups. Correlation between these parameters was assessed by calculating Pearson's correlation coefficient. P < 0.05 was considered to be statistically significant. Data were analysed using the Statistical Package for the Social Sciences (SPSS) version 20 (SPSS, Chicago, IL, USA).


  Results Top


During the study period, one hundred and forty patients with IFG were included in the study. The general characteristics of the patients are shown in [Table 1]. At the end of 1 month, reclassification based on FPG showed that 70% remained IFG, 26.4% reverted to normoglycaemia and 3.60% came under diabetes. Reclassification based on 2 h post-prandial (OGTT) at the end of 1 month showed that 65.70% had normal glucose tolerance (NGT), 31.4% had impaired glucose tolerance (IGT) and 2.90% had diabetes mellitus.{Table 1}

HbA1c could identify only 63.6% as prediabetes, 22.10% of them reverted to normoglycaemia and 14.30% were classified as diabetes. The details are given in [Table 2]. The total no of prediabetics (at 1 month follow up as per ADA definition) was equal to 102 The number of patients who were misclassified (i.e, IFG was normalised) was 46 (140-94) Therefore the percentage of SH in our study was 32.8%.{Table 2}

The relationship of FPG, 2 h PP, and HbA1c with Gensini scoring for CAD severity is shown in [Table 2]. Median Gensini scores of the groups classified based on FPG i.e., normoglycaemia, IFG and diabetes mellitus showed a rising trend with the degree of glycemia, but the difference was not statistically significant (P = 0.772). However, median Gensini scores of the groups classified based on 2H PP showed a significant difference with normoglycaemia, IGT and diabetes having median scores of 32, 66 and 28, respectively. The median Gensini Score of the diabetes mellitus group was observed to be low (n = 4); these patients (with diabetes) were not included for further analysis. The median Gensini scores of the above groups classified based on HbA1c did not show any correlation (P = 0.81).

As ACS is a stressful event, one of the major concerns is that of SH. Hence HbA1c, an average of 3 months sugar does not reliably predict the risk of acute coronary event in patients without diabetes. On the contrary, in patients with diabetes, it is a very good indicator of CVD risk. Median Gensini scores of the three groups (IFG, IGT and prediabetes) when compared showed the highest median Gensini in the IGT group [Figure 1].{Figure 1}

Pearson's correlation was used to assess the correlation between various variables used for assessing the glycaemic status like FPG, PPG, HbA1c and gensini score. FPG showed a weak positive correlation (0.187) whereas 2 h PPG showed a moderate positive correlation (0.416). HbA1c value, when correlated with the severity of CHD showed a very weak correlation (0.1) [Figure 2], [Figure 3], [Figure 4].{Figure 2}{Figure 3}{Figure 4}

The occurrence of CAD/acute coronary event, which we are interested in is influenced by many factors other than glycaemic status such as age, gender, smoking, hypertension, BMI and waist circumference. To adjust for these confounding variables, and to find out the effect of increasing glycaemia and the severity of CAD, multiple linear regression was performed.

After adjusting for all the variables, results showed only 2h-PPBG to have a significant correlation with Gensini score (regression coefficient 1.006). Implying that for every 1 unit increase in 2 h PP, there is 1 unit increase in Gensini score.


  Discussion Top


This study was done to assess prediabetes in ACS. ACS is a stressful event, SH would undoubtedly be a part of the clinical scenario. To eliminate SH, we reclassified the patients at follow-up after 1 month with OGTT. After reclassification, 32.8% of patients with IFG on admission reverted to normoglycaemia, suggesting that they had SH. This was similar to to that reported in other Indian studies.[8],[9],[10]

We correlated the glycaemic status of the patients at 1 month follow-up using FBS, 2h- PPBG after 75 g OGTT and HbA1c (on admission) with CAG severity of disease using Gensini score. IFG is known to be associated with cardiovascular risk according to many studies. In our study, the median Gensini scores among three glycaemic groups (normoglycaemia, IFG and diabetes) showed differences among the groups, though statistically not significant (P = −0.772). Pearson's correlation coefficient was 0.187 which showed a weak positive correlation [Figure 2]. In a Chinese study,[11] nondiabetic patients who underwent CAG were classified based on 75 g OGTT into NGT, isolated IFG, isolated IGT and combined glucose intolerance (CGI). The authors[11] found that Gensini scores were similar among the first three groups compared to the CGI group where there was a significant rise in Gensini score. They found that fasting glucose had a strong association with coronary artery stenosis by Gensini score. Another study[12] compared mean calcium scores, plaque burden and obstructive CAD in patients with normal FPG, IFG and DM. They found higher values in IFG and DM compared to normoglycaemic individuals.

Many studies such as DECODA, RIAD emphasised the importance of postprandial hyperglycaemia (after OGTT) than fasting hyperglycaemia in predicting the risk of acute coronary events.[13],[14] The reason that acute hyperglycaemia or intermittent hyperglycaemia being more important in increasing the risk of atheroma formation, plaque destabilisation and cardiovascular events than sustained hyperglycaemia is because of two main factors, namely: (i) increase in oxidative stress and endothelial dysfunction caused by reactive oxygen species promotes further cascade of events; and (ii) increase in circulating cytokine concentrations causing a systemic inflammatory state which is responsible for insulin resistance (tumour necrosis factor-alpha, interleukin-6) and plaque rupture.[15]

In our study, there was a significant difference in median Gensini scores between NGT and IGT groups (P < 0.016). Significant difference was not found between diabetes, and NGT or IGT groups because the numbers in the diabetic group were too low to be considered. Gensini score and 2h-PPBG had a moderate positive correlation in our study with the Pearson's correlation coefficient being (0.416). In a study[16] from north India, prevalence and relation of prediabetes with ACS was assessed in nondiabetic subjects with ACS. They found a higher odds ratio for glucose intolerance (IFG + IGT) and proinsulin levels, both being significant independent predictors for ACS. Another study[10] showed a high prevalence of abnormal glucose tolerance in patients with ACS, more at a younger age in the Indian population compared to Western population and among those who had glucose intolerance at the baseline, two-thirds persisted to be in abnormal glucose tolerance (IGT or diabetes) as revealed after multiple logistic regression analysis.

In another study[17] authors compared the degree of glycaemia with the number of coronary vessels involved. 363 nondiabetic patients (who underwent CAG) were classified into groups I, II and III (one, two and three-vessel disease). Of them, 36.1% and 16.1% had IGT and type 2 diabetes mellitus with most of them in Groups II and III. PPG levels were at a higher range in patients with multivessel disease.[17] Another study[18] also found that 2 h plasma glucose was an independent risk factor for CAD. The RIAD study[14] on carotid intima-media thickness (IMT) found higher IMT in patients with IGT as compared to those with isolated IFG or NGT. In our study too, the post glucose sugar showed the best correlation with Gensini score.

A study[19] investigated the cardiovascular risk profile in terms of Augmentation index (arterial stiffness), IMT and soluble receptor for Advanced Glycation End products (sRAGEs) in those without previously diagnosed diabetes by using HbA1c as a baseline indicator. They divided the subjects into three groups based on HbA1c into normal, prediabetes and diabetes (<5.7, 5.7–6.4, >6.5, respectively). It was found that those who were prediabetics (based on HbA1c, but with NGT and normal FBS) had higher augmentation index and cIMT compared to those with HbA1c >6.5. Thereby suggesting HbA1c as a better marker to identify prediabetics at higher cardiovascular risk than FBS or 2h-PPBG.[19] However, in our study, HbA1C and Gensini scores did not show any correlation, (Pearson's correlation coefficient being 0.1.) A Turkish study[20] also could not derive a significant association between HbA1c and Gensini score (P = −0.299), but it demonstrated a significant association between Gensini score and obesity (P = −0.024).

So to conclude, several other studies and ours did show that postprandial sugar is possibly the best way to assess glycaemic risk for IHD. However, doing PP sugar at the time of ACS is difficult in view of various other factors like SH which could be misleading as discussed above. Hence, the mode of assessment of glycaemic status at 1 month would help to identify high-risk individuals, specifically with OGTT which can reliably identify those with abnormal glucose tolerance.

We then performed multiple linear regression to adjust for the various confounding factors such as age, gender, BMI and smoking and for parameters of glycaemia such as FPG, PPG and HbA1c. After adjusting for all the confounding factors, among the three glycaemic variables FPG, PPG and HbA1C, we found only 2h-PPBG to have significant association with Gensini score. The regression coefficient thus obtained was 1.006, which means for every 1 unit increase in 2 h PP there is 1 unit increase in Gensini. It, therefore, showed only 2 h PP to have a significant association with Gensini score.

In support with the above idea are other major studies like DECODA study where post-challenge hyperglycaemia was found to be a better predictor of macrovascular complications and death, RIAD study which tells that IGT but not IFG as a better predictor of atherosclerosis. Post-meal hyperglycaemia may translate into increased mortality[21] suggesting that the cumulative survival rates among NFG, IFG, IGT and diabetes were significantly lower among IGT and diabetes than other groups (0.962 and 0.954 in the former; NGT, NFG, IFG-0.988,0.985 and 0.977). A study[13] from Australia also demonstrated similar results that people with isolated post-challenge hyperglycaemia had higher mortality rates almost double the mortality risk. HbA1c is a better predictor of CV risk in patients who are diabetics, but in prediabetics or normoglycaemics, its positive predictive value is low.

The strength of the present study is that we measured the burden of CAD by Gensini score on angiogram. To eliminate the possibility of SH, reclassification of patients was undertaken at 1 month follow-up and OGTT was done in all patients. Since all patients had ACS, P2h-PPBG could not be done at the time of ACS in view of practical issues, this could be a limitation. There was a significant correlation between severity of CAD as assessed by Gensini score and glycaemic status. IGT was the best predictor of CAD followed later by IFG and HbA1c. However, because of a high percentage of SH, an OGTT done after 1 month from discharge may help in identifying patients at high risk, as was done in our study.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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