|
 
 |
| ORIGINAL ARTICLE |
|
| Year : 2021 | Volume
: 10
| Issue : 1 | Page : 2-7 |
|
Electrocardiography indices in healthy metabolic syndrome patients: Markers for future cardiovascular risk
Khushboo Agarwal MD , Dhruv Thakur MD , Alok Gupta MD , Rajat Gupta MD
Department of Medicine, DR SN Medical College, Jodhpur, Rajasthan, India
| Date of Submission | 12-Aug-2020 |
| Date of Acceptance | 19-Dec-2020 |
| Date of Web Publication | 27-Mar-2021 |
Correspondence Address:
Dr. Khushboo Agarwal
Flat No 203 Real Orchid APT, B141 Vijaypath Tilak Nagar, Jaipur - 302 004, Rajasthan
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/jcpc.jcpc_52_20
Background: Metabolic syndrome is a constellation of cardiovascular risk factors characterized by insulin resistance, prothrombotic and pro-inflammatory state. This study was an attempt to evaluate ECG changes as markers for metabolic syndrome before development of overt cardiovascular disease. Aims: We evaluated association between metabolic syndrome and ECG indices: QT dispersion, QTc dispersion, TpTe interval and TpTe/QT ratio. Settings and Design: Cross-sectional study Methods and Material: The study was conducted on 108 patients with metabolic syndrome and compared with age and sex matched 50 controls. Indices were measured from 12 lead ECG and data was compared. Statistical analysis used: SPSS Results: Metabolic syndrome was more common in females with most common criteria present being waist circumference followed by hypertriglyceridemia Metabolic syndrome group had higher levels of BMI, waist circumference, fat percentage, serum triglycerides and fasting glucose, systolic and diastolic pressure as well as lower HDL levels than control subjects. The QTc dispersion, QT dispersion, TpTe intervals and TpTe/QT ratio were significantly increased in Metabolic syndrome group compared to the control group. Increased Odd's ratio of the ECG parameters in comparison with the control group was also calculated. ROC curve revealed that QTc dispersion and TpTe/ QT ratio were better predictors for future metabolic syndrome. Conclusions: Hence ECG indices (QT dispersion, QTc dispersion, TpTe interval and TpTe/ QT ratio) can be used to predict cardiovascular risk in such patients.
Keywords: Metabolic syndrome, predictive markers, QT Dispersion, TpTe interval, TpTe/QT Ratio
How to cite this article:
Agarwal K, Thakur D, Gupta A, Gupta R. Electrocardiography indices in healthy metabolic syndrome patients: Markers for future cardiovascular risk. J Clin Prev Cardiol 2021;10:2-7 |
How to cite this URL:
Agarwal K, Thakur D, Gupta A, Gupta R. Electrocardiography indices in healthy metabolic syndrome patients: Markers for future cardiovascular risk. J Clin Prev Cardiol [serial online] 2021 [cited 2023 Mar 24];10:2-7. Available from: https://www.jcpconline.org/text.asp?2021/10/1/2/312226 |
| Introduction | |  |
Metabolic syndrome is a constellation of cardiovascular risk factors including abdominal obesity, hyperglycemia, hypertension, and hypertriglyceridemia. It is characterized by insulin resistance, prothrombotic and pro-inflammatory state.
India as a country is more susceptible as insulin resistance is observed in nearly 30% of children and adolescents.[1] Data also indicate that atherogenic dyslipidemia, glucose intolerance, thrombotic tendency, subclinical inflammation, and endothelial dysfunction are proportionately higher in Asian Indians than Caucasians,[2] resulting in cardiovascular epidemic in India characterized by its accelerated build-up, the early age of disease onset in the population, and the high case fatality rate.[3] Indians have a peculiar body phenotype characterized by increased waist circumference, increased waist–hip ratio, excessive body fat mass, increased plasma insulin levels and insulin resistance, as well as an atherogenic dyslipidemia, with low levels of high-density lipoprotein cholesterol (HDL-c) and increased triglyceride levels,[2] predisposing them to T2DM and premature heart disease.
In order to identify patients with higher risk, a number of markers have been developed including interleukin-6, tumor necrosis factor-α, oxidized LDL, uric acid, plasminogen activator inhibitor-1, interleukin-10, ghrelin, adiponectin, and paraoxonase-1. They have limited use in our country because of high costs and lack of wider availability. The need of the hour is to identify inexpensive markers which can predict the same. This study was an attempt to evaluate electrocardiography (ECG) changes as markers for metabolic syndrome before development of overt cardiovascular disease.
These markers include QT dispersion (QTd), QTc dispersion, Tpeak-Tend (TpTe) interval, and TpTe/QT ratio. The metabolic syndrome is associated with increased sympathetic activity which causes malignant ventricular arrhythmias and death independent of coronary artery disease and heart failure.[4] QTd and QTc dispersion are markers of myocardial electrical instability and is a predictor of arrhythmic events.[5] TpTe interval and TpTe/QT ratio are markers of transmural dispersion of ventricular repolarization[6] and also have been accepted as ECG index of ventricular arrhythmogenesis.[7]
Although there a number of studies evaluating these markers, they have not been evaluated for their sensitivity and specificity. In this study, we aim to evaluate these four markers in asymptomatic metabolic syndrome patients as markers of cardiovascular risk. We also evaluate relation between ECG indices and individual component of metabolic syndrome. We also aim to evaluate if the values change with severity of metabolic syndrome and if the individual marker is sensitive enough to predict future metabolic syndrome risk.
| Subject and Method | | |
The study was conducted on 108 OPD patients diagnosed with metabolic syndrome as defined by the National Cholesterol Education Program Expert Panel (adult treatment panel III)[8] as the presence of three or more of the following: triglycerides (TG) ≥150 mg/dL; HDL-c <50 mg/dL in women or <40mg/dL in men, blood pressure (BP) ≥130/85 mmHg or those taking drugs for hypertension, fasting blood glucose ≥110 mg/dL, or history of antidiabetic medication; waist circumference cutoff was taken according to ethnic guidelines specified by international diabetes federation for South Asians: 80 cm for females and 90 cm for males.[9] Fifty age- and sex-matched individuals were recruited as a control group.
Patients with following abnormalities were excluded from the study: Coronary artery disease, chronic renal failure, chronic liver disorders, chronic lung disease, moderate or severe valvular heart disease, congenital heart disease, left ventricular systolic dysfunction on echocardiography, recent acute coronary syndrome, pregnancy, obstructive sleep apnea, known malignancy; electrolyte imbalance, bundle branch block, atrioventricular conduction abnormalities. Patients taking medication known to affect repolarization parameter on the ECG, such as digoxin, antiarrhythmic drugs, phenothiazines, tricyclic antidepressant, lithium carbonate, erythromycin, theophylline, levodopa, etc.
The anthropometric data taken included height, weight, waist circumference, hip circumference, and waist-to-hip ratio. The waist circumference was measured at the level of umbilicus. Fat percentage was calculated using Omron Handheld Fat Loss Monitor which worked on the basis of bioelectrical impedance by sending an extremely low-level electrical current of 50 kHz and 500 μA through the body to determine the amount of fat tissue. BP was measured early in the morning, after a 10-min rest in a quiet room, while subjects were in the seated position and by the use of a validated oscillometric device, with a cuff of the appropriate size applied to the right upper arm. The mean value of three BP readings (obtained at 1-min intervals) was considered as the variable of the study. Body mass index (BMI) was calculated as weight in kilograms divided by height squared in meters (kg/m2). Complete hemogram was performed using automatic blood counter Sysmex KX-21 and H51 Benesphera coulter from EDTA bulb. Fasting serum sample was used for measurement of glucose levels, lipid profile, and uric acid. Plasma glucose levels were measured by the glucose oxidase method. Total cholesterol, TG, and HDL were measured by commercial enzymatic calorimetric method and LDL by direct enzymatic method.
Electrocardiography
For analysis of the electrocardiographic parameters, lead II was recorded at a paper speed of 50 mm/s. QT interval and TpTe interval were measured manually. The QT interval was defined as extending from the beginning of the QRS complex to where T-waves descend onto the isoelectric baseline.[10] When a U-wave interrupted the T-wave before returning to baseline, the QT interval was measured to the nadir of the curve between the T- and U-waves. The QTc interval was calculated using the Bazett formula: QTc (ms)=QT measured/√RR (s). Extended QTc interval was defined as a duration of >440 ms. The QTd value was determined as the difference between the longest and shortest QT intervals observed from the 12-lead ECG.[11] The TpTe interval was defined as the interval from the peak of T-wave to the end of T-wave. Measurements of TpTe interval were performed in the precordial leads. The TpTe/QT ratio was calculated using these measurements.[12]
Statistical method
The data were compared with the age-matched control group. The obtained parameters were evaluated using descriptive statistical analysis. Statistical analyses were performed using the IBM USA SPSS (Statistical Package for the Social Sciences v15.0) and Microsoft Excel 2007 software. The Student's t-test and the one-way analysis of variance test were used for comparing the group means. The Chi-square test was used, and P < 0.05 was taken as statistically significant. Logistic regression analysis was done to look for association of various ECG indices with metabolic syndrome, and their ability to predict metabolic syndrome was examined by receiver-operating characteristic (ROC) curve analyses.
| Results | | |
Our study involved 108 patients with metabolic syndrome (43 males, 65 females; mean age: 56.39 ± 11.36 years) and 50 controls (20 males, 30 females; mean age: 53 ± 9.3). The case and control groups were similar in terms of gender and age. Metabolic syndrome was more common in females, with the most common criteria present being waist circumference followed by hypertriglyceridemia [Figure 1]. Most patients had 4 criteria positive [Figure 2]. | Figure 1: Distribution of the study population according to metabolic criteria
Click here to view |
 | Figure 2: Distribution of the study population according to number of metabolic criteria fulfilled
Click here to view |
A summary of biochemical and anthropometric characteristics studied is shown in [Table 1]. The metabolic syndrome group had higher levels of BMI, waist circumference, fat percentage, serum triglycerides and fasting glucose, systolic and diastolic pressure as well as lower HDL levels than control subjects [Table 1]. | Table 1: Comparison of biochemical and echocardiographic variables in MetS patients and healthy controls
Click here to view |
A comparison of ECG parameters – in patients with and without metabolic syndrome to individual parameter of metabolic syndrome – is given in [Table 2]. The QTc dispersion, QTd, TpTe intervals, and TpTe/QT ratio were significantly increased in the metabolic syndrome group compared to the control group. | Table 2: Comparison of various electrocardiogram parameters and serum uric acid with individual metabolic criteria in the study population
Click here to view |
A multivariable logistic regression model was used to determine the effect of ECG parameters on the risk of metabolic syndrome after adjusting for confounding factors. Increased odds ratio of the ECG parameters in comparison with the control group was also calculated [Table 3]. There was a positive association observed between metabolic syndrome incidence and various ECG indices (QTc dispersion, QTd, TpTe intervals, and TpTe/QT ratio), and the results were significant (P = 0.01). | Table 3: Odds ratio of various parameters associated with metabolic syndrome in comparison to nonmetabolic syndrome
Click here to view |
[Figure 3] shows the ROC curve of ECG indices for predicting metabolic syndrome. QTc dispersion and TpTe/QT ratio were better predictors for future metabolic syndrome than QTd and TpTe interval. These ECG indices have high sensitivity but low specificity for metabolic syndrome. | Figure 3: Receiver-operating characteristic curves of electrocardiography indices: (a) QT dispersion, (b) QTc dispersion, (c) Tpeak-Tend interval, (d) Tpeak-Tend/QT ratio
Click here to view |
| Discussion | | |
Individuals with metabolic syndrome are at increased risk for cardiovascular heart disease. The studies exploring effect of metabolic syndrome on ECG changes before development of overt cardiovascular abnormalities are limited. We examined relation of ECG indices (QTd, QTc dispersion, TpTe interval, and TpTe/QT ratio) with individual component and severity of metabolic syndrome. We also examined the ability of these indices to predict future metabolic syndrome risk.
In our study, we found that the ECG indices were significantly increased in patients with metabolic syndrome and were also significantly related to each component of metabolic syndrome. We also analyzed the ability of these indices to predict future cardiovascular risk in metabolic syndrome patients. While all of the markers were highly sensitive, they were not specific for metabolic syndrome. TpTe/QT ratio had the highest sensitivity and specificity among them.
A prolonged QT interval reflects the myocardial refractoriness and electrical instability of myocardium and has been associated with adverse cardiovascular outcomes including ventricular fibrillation and sudden death.[13] Soydinc et al.[14] also revealed that the patients with uncomplicated metabolic syndrome have a greater dispersion of ventricular repolarization time even in the absence of left ventricular hypertrophy. High insulin levels increase sympathetic activity enhancing myocardial cell refractoriness[15] and also cause hypokalemia: both can increase Qt and QTc interval even in healthy subjects.[16]
The TpTe interval and TpTe/QT ratio have emerged as novel electrocardiographic markers of increased dispersion of ventricular repolarization.[7] Increased dispersion of repolarization between the base and apex of the heart intramurally or in the region of interventricular septum predisposes to ventricular arrhythmias.[17] TpTe also increased in acute coronary syndrome including ST and non-ST-elevation myocardial infarction;[18] silent cardiac ischemia may account for increased TpTe interval. It has been previously shown in diabetic animal models that hyperglycemia alters ionic currents of the sarcolemma leading to action potential prolongation.[18]
Alterations in cardiac autonomic activity in DM may be responsible for ventricular arrhythmias by increasing the heterogeneity of ventricular repolarization.[19] QT interval and its parameters have often been criticized as poor indicators of ventricular arrhythmogenesis[20] as some studies some show significant results[21] while others show no correlation.[22],[23] The main problem with QTd is that there is no universally recognized method of lead selection or a standardized method of measurement. The intra- and inter-observer reproducibility of QTd is low.[24] Despite its shortcomings, the greatest advantage of QTd as screening test is it does not require patient compliance and is easily obtained.[25]
TpTe interval and TpTe/QT ratio are markers of transmural dispersion, hence considered to be more accurate.[7] Karaagac et al. reported a positive correlation between these indices and metabolic syndrome;[26] Tokatli et al.[23] and Clemente et al.[27] reported a positive correlation between these indices and diabetes.
This is the first study to analyze the ability of these indices to predict future metabolic syndrome by plotting ROC curve. TpTe/QT ratio had the highest sensitivity (100%) and specificity (57.9%) among them followed by QTc dispersion. The markers which were independent of heart rate were more accurate for predicting the future risk. Despite low sensitivity, these markers are great screening tools because of nonreliability on a patient's compliance, easy access even in remote areas of the country, and cost-effectiveness.
| Conclusion | | |
Our results showed that cardiac repolarization abnormalities may be present in healthy subjects with metabolic syndrome. Hence, ECG indices (QTd, QTc dispersion, TpTe interval, and TpTe/QT ratio) can be used to predict cardiovascular risk in such patients. Despite low sensitivity, these markers are great screening tools because of nonreliability on a patient's compliance, easy access even in remote areas of the country, and cost-effectiveness. Standardization of methodology of measurement of these indices is required for their large-scale use and further prospective studies in larger number of patients are required.
Limitations
- It was a cross-sectional study with small number of patients that cannot definitively determine the causality of the association between reduced insulin sensitivity and an increase in the QTc interval. A higher number of patients and long follow-up are necessary to assess arrhythmic events in these patients and its correlation with QTc or QTd values
- Although patients with uncomplicated metabolic syndrome had a significantly higher values of QTc-min, QTc-max, and QTd than the control group (P < 0.001), the absolute mean values are not grossly abnormal in our study
- We did not evaluate the association between ventricular arrhythmias and Tp-Te interval or QTc dispersion. Therefore, we are not sure about prognostic importance of Tp-e interval prolongation and higher Tp-e/QT ratio in our patients
- We categorized our patients as asymptomatic metabolic syndrome patients based on lack of coronary event and normal two-dimensional echocardiogram, but silent ischemia may have occurred.
Informed consent
Informed consent was obtained from all individual participants included in the studies.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
| References | | |
| 1. | Misra A, Misra R, Wijesuriya M, Banerjee D. The metabolic syndrome in South Asians: continuing escalation & possible solutions. Indian J Med Res 2007;125:345-54.  [ PUBMED] [Full text] |
| 2. | Mohan V, Rao GH. Type 2 Diabetes in South Asains. 1 st ed.. New Delhi: South Asian Society on Atherosclerosis and Thrombosis; 2007. |
| 3. | Joshi P, Islam S, Pais P, Reddy S, Dorairaj P, Kazmi K, et al. Risk factors for early myocardial infarction in South Asians compared with individuals in other countries. JAMA 2007;297:286-94. |
| 4. | Grassi G, Quarti-Trevano F, Seravalle G, Dell'Oro R. Cardiovascular risk and adrenergic overdrive in the metabolic syndrome. Nutr Metab Cardiovasc Dis 2007;17:473-81. |
| 5. | Galinier M, Vialette JC, Fourcade J, Cabrol P, Dongay B, Massabuau P, et al. QT interval dispersion as a predictor of arrhythmic events in congestive heart failure. Importance of aetiology. Eur Heart J 1998;19:1054-62. |
| 6. | Antzelevitch C. Tpeak–Tend interval as an index of transmural dispersion of repolarization. Eur J Clin Invest 2003;31:555-7. |
| 7. | Gupta P, Patel C, Patel H, Narayanaswamy S, Malhotra B, Green JT, et al. T (p-e)/QT ratio as an index of arrhythmogenesis. J Electrocardiol 2008;41:567-74. |
| 8. | Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III). JAMA 2001;285:2486-97. |
| 9. | |
| 10. | Hanci V, Yurtlu S, Aydin M, Bilir S, Erdogan G, Dilek R, et al. Preoperative abnormal P and QTc dispersion intervals in patients with metabolic syndrome. Anesth Analg 2011;112:824-7. |
| 11. | Day CP, McComb JM, Campbell RW. QT dispersion: An indication of arrhythmia risk in patients with long QT intervals. Br Heart J 1990;63:342-4. |
| 12. | Castro Hevia J, Antzelevitch C, Tornés Bárzaga F, Dorantes Sánchez M, Dorticós Balea F, Zayas Molina R, et al. Tpeak-Tend and Tpeak-Tend dispersion as risk factors for ventricular tachycardia/ventricular fibrillation in patients with the Brugada syndrome. J Am Coll Cardiol 2006;47:1828-34. |
| 13. | Guiraud T, Gayda M, Curnier D, Juneau M, Talajic M, Fortier A, et al. Long-term exercise-training improves QT dispersion in the metabolic syndrome. Int Heart J 2010;51:41-6. |
| 14. | Soydinc S, Davutoglu V, Akcay M. Uncomplicated metabolic syndrome is associated with prolonged electrocardiographic QTc interval and QTc dispersion. Ann Noninvasive Electrocardiol 2006;11:313-7. |
| 15. | Dekker JM, Feskens EJ, Schouten EG, Klootwijk P, Pool J, Kromhout D. QTc duration is associated with levels of insulin and glucose tolerance. The Zutphen elderly study. Diabetes 1996;45:376-80. |
| 16. | Van De Borne P, Hausberg M, Hoffman RP, Mark AL, Anderson EA. Hyperinsulinemia produces cardiac vagal withdrawal and nonuniform sympathetic activation in normal subjects. Am J Physiol 1999;276:R178-83. |
| 17. | Bieganowska K, Sawicka-Parobczyk M, Bieganowski M, Piskorski J. Tpeak -tend interval in 12-lead electrocardiogram of healthy children and adolescents tpeak -tend interval in childhood. Ann Noninvasive Electrocardiol 2013;18:344-51. |
| 18. | Nishiyama A, Ishii DN, Backx PH, Pulford BE, Birks BR, Tamkun MM. Altered K(+) channel gene expression in diabetic rat ventricle: Isoform switching between Kv4.2 and Kv1.4. Am J Physiol Heart Circ Physiol 2001;281:H1800-7. |
| 19. | Valensi PE, Johnson NB, Maison-Blanche P, Extramania F, Motte G, Coumel P. Influence of cardiac autonomic neuropathy on heart rate dependence of ventricular repolarization in diabetic patients. Diabetes Care 2002;25:918-23. |
| 20. | Bravenboer B, Hendriksen PH, Oey LP, Gispen WH, van Huffelen AC, Erkelens DW. Is the corrected QT interval a reliable indicator of the severity of diabetic autonomic neuropathy? Diabetes Care 1993;16:1249-53. |
| 21. | Naas AA, Davidson NC, Thompson C, Cummings F, Ogston SA, Jung RT, et al. QT and QTc dispersion are accurate predictors of cardiac death in newly diagnosed non-insulin dependent diabetes: cohort study. BMJ 1998;316:745-6. |
| 22. | Balkau B, Jouven X, Ducimetière P, Eschwège E. Diabetes as a risk factor for sudden death. Lancet 1999;354:1968-9. |
| 23. | Tokatli A, Kiliçaslan F, Alis M, Yiginer O, Uzun M. Prolonged Tp-e interval, Tp-e/QT ratio and Tp-e/QTc ratio in patients with type 2 diabetes mellitus. Endocrinol Metab (Seoul) 2016;31:105-12. |
| 24. | Glancey MJ, Weston PJ, Bhullar HK, Garratt CJ, Bono DP. Reprucibility and automatic measurement of QT dispersion. Eur Jour J 1996;17:1035-9. |
| 25. | Kumar R, Fisher M, Macfarlane PW. Review: Diabetes and the QT interval: Time for debate. Br J Diabetes Vasc Dis 2004;4:146-50. |
| 26. | Karaagac K, Emul A, Tenekecioglu E, Agca FV, Ozluk OA, Tutuncu A, et al. The effects of metabolic syndrome on TpTe interval and Tpte/QT ratio in patients with normal coronary arteries. Eurasian J Med 2014;46:182-6. |
| 27. | Clemente D, Pereira T, Ribeiro S. Ventricular repolarization in diabetic patients: characterization and clinical implications. Arq Bras Cardiol 2012;99:1015-22. |
[Figure 1], [Figure 2], [Figure 3]
[Table 1], [Table 2], [Table 3]
|
Search Pubmed for