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Table of Contents
ORIGINAL ARTICLE
Year : 2019  |  Volume : 9  |  Issue : 3  |  Page : 148-153

Glycemic variability as a predictor of major adverse cardiac events after percutaneous coronary intervention


Department of Cardiology, Faculty of Medicine, Zagazig University, Zagazig, Egypt

Date of Web Publication3-Dec-2019

Correspondence Address:
Dr. Ahmed Said Eldamanhory
Department of Cardiology, Faculty of Medicine, Zagazig University, Zagazig
Egypt
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/JICC.JICC_9_19

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  Abstract 


Background: The endothelial dysfunction was greater by glucose fluctuation than by chronic hyperglycemia. The glycemic variability (GV) may be an independent risk factor for atherosclerotic coronary artery disease in diabetic patients. The cardiovascular complications are higher following myocardial infarction in diabetic patients than nondiabetic individuals. Aim of the Work: Our aim is to prove that good controlling of acute shooting of blood glucose level up and down will improve the outcome in patient undergoing percutaneous coronary intervention (PCI). Subjects and Methods: GV is evaluated using intraday variability by fasting, preprandial, and postprandial blood glucose levels in 120 patients. Hemoglobin A1c was used to evaluate glycemic control. The relationship between GV and development of major adverse cardiac events (MACE) in patients undergoing PCI is studied. Results: There is a statistically significant difference between the relation of GV and MACE within 1 month after PCI in uncontrolled diabetes compared to controlled group. There is no statistically significant difference found between the two groups regarding age, gender, risk factors (hypertension, smoking and dyslipidemia), and laboratory parameters including triglycerides, total cholesterol, low-density lipoprotein, and high-density lipoprotein. Conclusions: Uncontrolled GV is associated with poor short-term outcome after PCI in controlled diabetic patients compared to nondiabetic individuals undergoing PCI. Greater GV is associated with composite MACE, especially for uncontrolled diabetic patients. After multivariable logistic analysis, GV remains an independent prognostic factor for composite MACE after 3 months in patients undergoing PCI.

Keywords: Glycemic variability, hemoglobin A1c, intraday variation, major adverse cardiac events


How to cite this article:
Alzaky MM, Eldamanhory AS, Kandeel NT, Ameen MI. Glycemic variability as a predictor of major adverse cardiac events after percutaneous coronary intervention. J Indian coll cardiol 2019;9:148-53

How to cite this URL:
Alzaky MM, Eldamanhory AS, Kandeel NT, Ameen MI. Glycemic variability as a predictor of major adverse cardiac events after percutaneous coronary intervention. J Indian coll cardiol [serial online] 2019 [cited 2019 Dec 13];9:148-53. Available from: http://www.joicc.org/text.asp?2019/9/3/148/272177




  Introduction Top


Glycemic variability (GV) is one component of the dysglycemia, which includes both upward and downward acute glucose changes. Variability of glycemia in ambulatory conditions defined as the deviation from steady state is a phenomenon of normal physiology.[1] Recent studies have shown that GV might play an important role in the pathogenesis of atherosclerosis and may be an independent risk factor for cardiovascular complications in diabetic patients.[2]

Glycemic fluctuations are manifested principally as postprandial glycemic spikes and minor (or asymptomatic) hypoglycemia. However, the term GV may refer to within-day variability, variability between daily means, or within-series variability.[3]

It has been suggested that indicators of variability may provide a better indication than hemoglobin A1c (HbA1c) of overall long-term problems with glycemic control.[4]

In short-term (<1 month), retrospective, general population studies of critically ill patients, glucose variability has been implicated in increased mortality rates, as such there is an increasing interest in the possible role of glucose variability in the development and underlying pathology of diabetes-related complications.[1]

The complications of diabetes mellitus (DM) almost involved each organ of the body; 60%–80% of the patients died of vascular disease.[5]

Quagliaro et al. confirmed that the blood vessel endothelium was damaged greater by blood glucose fluctuation than by chronic persistent hyperglycemia.[6]

Chang et al., 2006, had demonstrated that acute and chronic fluctuations in blood glucose levels can increase oxidative stress in DM patients, which results in cell dysfunction and tissue injury. Therefore, it is important to evaluate the relationship between the blood glucose fluctuation and the coronary artery disease (CAD) by dynamic glucose monitoring.[7]

Coronary heart disease (CHD) is a major cause of morbidity and mortality among patients with DM. Compared to nondiabetic individuals, diabetic patients are more likely to have CHD, to have multivessel disease when it occurs, and to have episodes of silent ischemia. Morbidity, mortality, and reinfarction are higher following myocardial infarction (MI) in diabetic patients than nondiabetic individuals, with 1-year mortality in this population as high as 50%.[8]


  Subjects and Methods Top


Study design and population

A prospective study on 120 patients was conducted in Cardiology Department, Zagazig University Hospitals, from April 2017 to December 2017 and included diabetic patients admitted for doing percutaneous coronary intervention (PCI).

Inclusion criteria of the study

Inclusion criteria include patients who have type II DM, patients who are on oral hypoglycemic agents, patients with documented CAD by previous coronary angiography, and patients referred for doing PCI.

Exclusion criteria of the study

*Exclusion criteria include all patients with:

  • Previous revascularization by percutaneous intervention or coronary artery bypass grafting
  • Alcohol, lead, opiate toxicity, splenectomy, and uremia should be excluded due to increased level of HbA1c
  • Chronic renal disease – hepatic cirrhosis – previous or current cancer.


Ethical consideration

Consent was obtained from every patient after explanation of the procedure. Medical research and ethics committee approved the study.

Data collection

Data were collected for all patients before and after performing coronary angiography. The data collection includes the following:

  1. Complete history taking and examination
  2. Resting 12-lead standard surface electrocardiogram
  3. Echocardiography: Bedside screening echo using “Vivid e machine with 2.5 MHz probe” was done with special attention given to detect abnormalities of wall motion, estimation of left ventricular (LV) systolic function (modified Simpson's method), and diastolic function
  4. Laboratory test


  5. CBC for platelets, serum creatinine, and blood urea, LDL, triglycerides, and blood glucose level:

    (Fasting blood glucose [FBG] – preprandial and 2-h postprandial – HbA1c; preprocedural, 24 h after PCI, and 1 month after PCI)

    • The GV


    • It will be estimated in patients who are having DM with:

      • FBG >126 mg/dl, or
      • 2-h postprandial blood glucose ≥200 mg/dl, or
      • Glycosylated HBA1c level ≥6.5%
      • Under the active treatment with oral hypoglycemic agents.


    • Coronary intervention:


      • It will be performed with standard technique
      • Aspirin 100–325 mg and clopidogrel 600 mg were given at least 12 h before the procedure. Contrast agent used in all procedure was iodinated, nonionic, and low-osmolality contrast medium
      • The procedure was considered successful if there was <30% residual stenosis in the target lesion, with thrombolysis in MI Grade III flow and in the absence of major in-hospital complications:
      • Death, MI, or urgent coronary revascularization (re-PCI or coronary artery bypass graft).


    • Major adverse cardiac events (MACE) follow-up:


      • Follow-up of the patient after 1 month for developing any of the MACE
      • MACE were included in the study (heart failure, nonfatal MI, cerebrovascular stroke and mortality cardiac events, and death).



  Results Top


Our study included 82 males with a mean age of 56.45 ± 8.19 years. Seventy-six patients were hypertensive, 48 patients were smokers, and 60 patients were dyslipidemic patients.

The patients were classified into two groups based on the development of MACE during the 1-month follow-up after PCI:

  • Group A: MACE − ve group, this group included 72 cases (n = 72, 60%)
  • Group B: MACE + ve group, this group included 48 cases (n = 48, 40%).


Regarding demographic data, there was no statistically significant difference between the two groups regarding the age or gender of the patients, hypertension, smoking, or dyslipidemia.

We measured blood glucose level at the day of PCI seven times: fasting, preprandial, prelaunch, predinner, postprandial, postlaunch, and postdinner with standard deviation 1 (SD1) of minimum glucose level – 18.68 mg/dl and maximum blood glucose level – 121.77 mg/dl and mean – 62.25 mg/dl as shown in [Table 1] and [Table 2].
Table 1: Intraday glycemic variability at the day of percutaneous coronary intervention

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Table 2: Intraday glycemic variability at the day of percutaneous coronary intervention and after 1 month in relation to the two groups

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Furthermore, we measured blood glucose level at same times 1 month after PCI with SD1 of minimum glucose level and mean – 60.37 mg/dl as shown in [Table 2] and [Table 3].
Table 3: Intraday glycemic variability 1 month after percutaneous coronary intervention

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In studied patients, we found eight patients with acute coronary syndrome (13.3%), six patients with heart failure (10%), two patients with stroke (3.3%), five patients with arrhythmia (8.3%), and three patients died out hospital (5%). Total patients with MACEs were 24 (40%).

There was no significant correlation between the number of vessels affected in the patient and development of MACE in our study [Table 4].
Table 4: Correlation between number of vessels affected and major adverse cardiac events

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There was a statistical significant difference concerning left ventricular ejection fraction between studied groups, and it could be predictor of MACE occurrence [Table 5] and [Table 6].
Table 5: Univariate logistic regression analysis for the intraday glycemic variability at the day of percutaneous coronary intervention and 1 month after percutaneous coronary intervention and ejection fraction as a risk factors for major adverse cardiac events

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Table 6: Multivariate logistic regression analysis between the ejection fraction, intraday glycemic variability at the day of percutaneous coronary intervention, and 1 month after percutaneous coronary intervention as independent risk factors for the development of major adverse cardiac events

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We found that there is a significant positive correlation between the GV (SD1 and SD2) and the occurrence of MACE.

In this study, regarding the GV at the day of PCI and 1 month after PCI, cutoff points from receiver operating characteristic curve were 60.95 mg/dl and 57.53 mg/dl, respectively. The probability of MACE could achieve 70%, 66.7% sensitivity and 75%, 69.4% specificity, respectively [Figure 1]and [Figure 2].
Figure 1: Receiver operating characteristic curve and appropriate use criteria for the development of major adverse cardiac events according to the glycemic variability at the day of percutaneous coronary intervention (standard deviation 1)

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Figure 2: Receiver operating characteristic curve and appropriate use criteria for the development of major adverse cardiac events according to the glycemic variability 1 month after percutaneous coronary intervention (standard deviation 2)

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  Discussion Top


The complications of DM almost involved each organ of the body; 60%–80% of the patients died of vascular disease.[9]

Large vascular disease affects the aorta, coronary artery, cerebral artery, renal artery, and peripheral artery mainly, which is hard to ignore; many researchers have studied the effect of blood glucose fluctuation on the vascular complications of DM.[10]

The blood vessel endothelium is damaged greater by blood glucose fluctuation than by chronic persistent hyperglycemia.[11]

Recent studies have demonstrated that acute and chronic fluctuations in blood glucose levels can increase oxidative stress in DM patients, which results in cell dysfunction and tissue injury.[12] Therefore, it is important to evaluate the relationship between the blood glucose fluctuation and the CAD by dynamic glucose monitoring.[7]

PCI with stent implantation is the most commonly used myocardial revascularization procedure.[13]

Despite the proven safety and efficacy of PCI, adverse cardiovascular clinical events do occur after stent implantation, impairing its short- and long-term outcome.[14]

Conventionally, events occurring within the 1st month following PCI are attributed to the intervention and considered as periprocedural, whereas those presenting later arise either from the stented (target) lesion or from disease progression at other sites in the coronary tree.[13]

The current study showed that the increase in the GV is associated with poor short outcome after PCI and the vice versa.

The study populations were 120 patients. All patients were included according to inclusion and exclusion criteria and were divided into two groups as follows:

  • Group A (n = 72) – Include the patients who did not develop any MACE during the period of the short-term follow-up after PCI
  • Group B (n = 48) – Include the patients who developed any MACE during the period of the short-term follow-up after PCI.


The instability of blood glucose was calculated as the SD around the mean of a seven-point glycemic profile measured.[15]

We used a SD of a seven-point glycemic profile measures as the reflection of the intraday GV at the day of PCI (SD1) and 1 month after the PCI (SD2).

Regarding the HbA1c, the current study found no statistically significant correlation with MACE between the MACE +ve and −ve groups.

This was in agreement with the study by Zhang et al., 2014, who did not find a statistically significant difference between the two groups of the study concerning intraday variation.[16] This is also in agreement with study by Wang et al., 2014 (P = 0.17).[17]

Regarding the intraday variation of blood glucose, the current study found a statistically significant correlation between GV and our groups. There was a highly statistically significant difference between the two studied groups regarding the GV at the day of PCI and after 1 month with the significance being higher with the variability at the day of PCI.

This was in agreement with the study by Wang et al., 2014, who found a statistically significant difference between the two groups of the study concerning intraday variation reflected by the SD that the MACE group had significantly greater SD (3.25 ± 0.70 vs. 2.40 ± 0.82; P = 0.026).[17]

However, this was in contradiction to study by Siegelaar et al., 2011, who found that there was no difference in GV between those experiencing versus those not experiencing a cardiovascular event. This may be from the inclusion of type 2 diabetic patients only in their study.[18]

In this study, regarding the intraday GV at the day of PCI, the GV with 60.95 mg/dl cutoff value for the SD1, the SD1 value for the MACE development could achieve a sensitivity of 70% and a specificity of 75%, whereas regarding intraday GV 1 month after PCI, the GV with 57.35 mg/dl cutoff value for the SD2, the SD2 value for the MACE development could achieve a sensitivity of 66.7% and a specificity of 69.4%. Actually, we did not have enough studies which determined a cutoff value for SD as a representative of the GV value for the MACE development.

The pathophysiology of diabetic complications can be considered the result of two major deleterious metabolic alterations (excessive glycation and generation of oxidative stress) that are activated by three main glycemic disorders: hyperglycemia both at fasting and during postprandial periods and acute glucose fluctuations.[19]

In vitro studies have shown that glucose fluctuations are linked to pathologic processes including the production of reactive oxygen species with some studies, suggesting that large fluctuations in glucose levels may be a greater trigger of oxidative stress processes than chronic sustained levels of hyperglycemia.[20]

The blood vessel endothelium is damaged greater by blood glucose fluctuation than by chronic persistent hyperglycemia.[11]

Recent studies have demonstrated that acute and chronic fluctuations in blood glucose levels can increase oxidative stress in DM patients, which results in cell dysfunction and tissue injury.[12]

There was a statistical significant difference concerning LVEF, and it could be predictor of MACE occurrence. These results agreed with Schühlen et al., 1998, who found that LV function has a statistically significant difference when comparing between the MACE + ve and –ve groups (P = 0.01).[21] However, these results disagreed with Wang et al., 2014, who did not find any significance between the two groups regarding the LVEF. This may be from the low number of patients included in their study (n = 34).[17]

There was no significant correlation between the number of vessels affected in the patient and development of MACE in the current study. This is in agreement with study by Wang et al., 2014, which found that MACE exhibited no significant correlation with the number of the vessels affected in CAD patient (P = 0.2).[17]

Furthermore, study by Pourmoghaddas et al., 2014, found that patients with MACE had no statistically significant difference from those without MACE regarding the total number of vessels affected.[22]


  Conclusions Top


Uncontrolled GV is associated with poor short-term outcome after PCI in controlled diabetic patients compared to nondiabetic individuals undergoing PCI. GV remains an independent prognostic factor for composite MACE after 1 month in patients undergoing PCI.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

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Dossett LA, Cao H, Mowery NT, Dortch MJ, Morris JM Jr., May AK. Blood glucose variability is associated with mortality in the surgical intensive care unit. Am Surg 2008;74:679-85.  Back to cited text no. 1
    
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22.
Pourmoghaddas A, Bazgir A, Sanei H, Golshahi J, Rabiei K, Sistani E, et al. Prediction of short-term clinical outcome of percutaneous coronary intervention in patients with acute coronary syndrome through myeloperoxidase levels. ARYA Atheroscler 2014;10:100-6.  Back to cited text no. 22
    


    Figures

  [Figure 1], [Figure 2]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]



 

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