Association of T-wave Changes and Type 2 diabetes: A cross-sectional sub-analysis of MASHAD cohort population using Minnesota coding system of Electrocardiogram

Association of T-wave Changes and Type 2 diabetes: A cross-sectional sub-analysis of MASHAD cohort population using Minnesota coding system of Electrocardiogram | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association of T-wave Changes and Type 2 diabetes: A cross-sectional sub-analysis of MASHAD cohort population using Minnesota coding system of Electrocardiogram Sara Saffar Soflaei, Isa Nazar, Toktam Sahranavard, Farzad Fayedeh, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3216881/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Jan, 2024 Read the published version in BMC Cardiovascular Disorders → Version 1 posted 9 You are reading this latest preprint version Abstract Background: Type 2 Diabetes Mellitus (T2DM) has become a major health concern with an increasing prevalence and is now one of the leading causes of death globally. T2DM and cardiovascular disease are strongly associated and T2DM is an important independent risk factor for ischemic heart disease. T-wave abnormalities (TWA) on electrocardiogram (ECG) can indicate several pathologies including ischemia. In this study, we aimed to investigate the association between T2DM and T-wave changes evaluated using the Minnesota coding system. Methods: A cross-sectional study was conducted on the MASHAD cohort study population. All participants of the cohort population were enrolled in the study. 12-lead ECG and Minnesota coding system (codes 5-1 to 5-4) were utilized for T-wave observation and interpretation. Regression models were used for the final evaluation with a level of significance being considered at p<0.05. Results: A total of 9035 participants aged 35-65 years old were included in the study, of whom 1273 were diabetic. The prevalence of code 5-2, 5-3, major and minor TWA were significantly higher in diabetics (p0.05). Whereas, hypertension, age, and body mass index were significantly associated with T2DM. Conclusions: Although some T-wave abnormalities were more frequent in diabetics, none of them were statistically associated with T2DM in our study. Further research is needed to better understand the associations between T2DM and ischemic heart diseases. Electrocardiogram Type 2 Diabetes Mellitus T-wave Figures Figure 1 Figure 2 1. Introduction Type 2 Diabetes Mellitus (T2DM) is a complex condition associated with impaired glucose tolerance, insulin resistance and hyperglycaemia, with an increasing prevalence and has become a serious global health challenge. It is accountable for 11.3% of deaths worldwide and is believed to affect approximately 10.9% of the global population [ 1 ]. T2DM is accompanied by debilitating complications such as kidney disease, retinopathy, neuropathy, microvascular impairments, and cardiovascular complications [ 1 , 2 ]. Cardiovascular complications are responsible for up to 68% of all diabetes-related mortalities. Several studies have revealed that patients with diabetes are at increased risk of coronary disease [ 3 ], myocardial infarction [ 4 ], heart failure [ 5 ], cardiomyopathy [ 6 ], and thrombotic events [ 7 ]. It has been shown that diabetic patients have a two- to three-fold increase in cardiovascular disease (CVD) development [ 8 ]. Various mechanisms have been proposed to explain the increased CVD rates among diabetic patients. Higher incidence of dyslipidemia [ 9 ], chronic inflammatory states [ 10 , 11 ], enhanced oxidative stress and reactive oxygen species [ 12 ], and hypercoagulability [ 13 ] are some of the key findings in patients with diabetes that can potentially increase atherosclerosis, plaque formation, and consequently result in increased rates of CVD [ 10 , 14 ]. Thus, it is of great importance to investigate sufficient early detection methods and effective therapeutic approaches for CVD among diabetic patients. An electrocardiogram (ECG) is a recording of cardiac electrical activities. An ECG is a useful and non-invasive assessment that has been utilized for several biomedical uses such as the determination of arrhythmias, fibrillations, heart rates, premature contractions and ischemia [ 15 – 17 ]. T-wave in ECG represents ventricular repolarization. T-wave abnormalities (TWA) can be an indicator of a variety of conditions such as cardiomyopathy, pulmonary embolism, peri- and myocarditis, and ischemia [ 18 – 21 ]. Given the importance of T2DM and its complication – especially those affecting the cardiovascular system – as well as considering the ease of accessibility and practicality of ECG in medical practice, this cross-section study was designed to investigate the prevalence of T-wave abnormalities and its association with T2DM. 2. Method 2.1. Study design and participants: The current cross-sectional study was conducted on the population of Mashhad stroke and heart atherosclerotic disorder (MASHAD) cohort [ 22 ]. All the participants aged from 35 to 65 years old were enrolled in the study from the cohort population. A checklist containing participants’ demographic data including age, sex, educational level, and marital status was recorded. Patients whose systolic blood pressure levels were at or above 140 mmHg and/or diastolic blood pressure were at or beyond 90 mmHg - measured using a mercury sphygmomanometer- were considered hypertensive. A fasting blood glucose (FBG) over 126 mg/dl or being under anti-hyperglycemic medication was defined as diabetic patients. The FBG was provided by a peripheral blood sample following 14 hours of fasting. The study was approved by the Human Research ethics committee of Mashhad University of Medical Sciences, Mashhad, Iran, and all participants provided informed consent prior to data collection. 2.2. ECG analysis: A standard resting 12-lead ECG was taken from each participant of the study. These ECGs were interpreted by instructed medical students in accordance with Minnesota coding system [ 23 ]. Five percent of all ECGs were also read by certified cardiologists. Four different t-wave abnormalities were described within the coding system including codes 5 − 1, 5 − 2, 5 − 3 and 5 − 4. The code 5 − 1 was defined as T amplitude negative 5.0 mm or more in either of leads I, V6, or in lead aVL when R amplitude is ≥ 5.0 mm. Code 5 − 2 was defined as T amplitude negative 5.0 mm or more in either of leads I, V6, or in lead aVL when R amplitude is ≥ 5.0 mm. Code 5 − 3 was described as flat, negative or diphasic t-wave with less than 1 mm negative phase in any leads of I, II or V3 to V6 or in lead aVL when the R amplitude is ≥ 5.0 mm. Lastly, code 5 − 4 was defined as a positive T amplitude and a T/R amplitude ratio < 1:20 in any of leads I, II, aVL, or V3 through V6. The R-wave amplitude must be ≥ 10.0 mm [ 23 ]. 2.3. Statistical analysis: Qualitative and quantitative variables were summarized as Mean \(\pm\) SD and frequency (%), respectively. An Independent t-test was used in order to compare the mean of quantitative variables between the two groups. In addition, evaluating the association between qualitative variables was performed using Chi-square and Fisher's exact test. Further analyses were performed in order to investigate the association between T wave impairments and T2DM after adjusting the effect of potential confounders (variables with P < 0.25 in the univariate logistic regression model) and using the multiple logistic regression (LR) model. Furthermore, receiver operating characteristic (ROC) curves were used to evaluate the ability of the multiple LR model to predict the occurrence of TWA and T2DM. All statistical analyses were carried out using SPSS version 20 and the statistical significance level was considered at 0.05. 3. Results 3.1. Study population characteristics A total of 9035 individuals were enrolled into the cohort study, including 1273 diabetic patients and 7762 non-diabetic individuals. The average age was 47.45 ± 8.17 and 51.77 ± 7.73 in non-diabetic and diabetic patients which differed significant (p < 0.001). Diabetic patients were found to have higher body mass index (BMI), as well as higher rates of hypertension (50.3 vs 27.9%, p < 0.001). Marital status and educational levels also showed a significant different distribution between the two diabetic and non-diabetic groups with married being the most prevalent status among studied groups (P < 0.001). Table 1 presents patients’ demographic data distributions. Table 1 Comparing the frequency distribution of demographical characteristics between individuals with and without diabetes Variables Total T2DM P-value No (N = 7762) Yes (N = 1273) Age 51.77 \(\pm\) 7.73 47.45 \(\pm\) 8.17 51.77 \(\pm\) 7.73 < 0.001 * Body mass index (kg/m 2 ) 28.93 \(\pm\) 4.62 27.71 \(\pm\) 4.73 28.93 \(\pm\) 4.62 < 0.001 * Gender Male 3615 (40.00) 3129 (40.30) 486 (38.20) 0.15 Female 5420 (60.00) 4633 (59.70) 787 (61.80) Marital status Single 55 (0.60) 51 (0.70) 4 (0.30) < 0.001 * Married 8418 (93.20) 7262 (93.60) 1156 (90.80) Divorced/widowed 562 (6.20) 449 (5.80) 113 (8.90) Education level Illiterate 1155 (12.80) 927 (11.90) 228 (17.90) < 0.001 * Lower than diploma 6815 (75.40) 5881 (75.80) 934 (73.40) Higher than diploma 1065 (11.80) 954 (12.30) 111 (8.70) Hypertension No 6220 (69.00) 5589 (72.10) 631 (49.70) < 0.001 * yes 2798 (31.00) 2159 (27.90) 639 (50.30) *Significance level of 0.05; Values are reported as Mean \(\pm\) SD and frequency (%). 3.2. T-wave abnormality frequency A total of 1246 T wave abnormalities were reported among the study sample population, approximately 13.79% of all participants. The most frequent T-wave abnormalities among both groups were code 5 − 2 (4.9% in diabetics and 3.6% in the control group) and major T-wave abnormalities (5% in diabetics and 3.7% in the control group). Different T-wave abnormalities yielded varying associations with T2DM. While T-wave abnormalities code 5 − 1 and 5 − 4 failed to show a significantly different distribution among diabetic and non-diabetic participants (P = 0.24 and 0.92 respectively), code 5 − 2 and 5 − 3 were shown to be significantly higher among diabetic patients compared to the non-diabetic individuals (P = 0.02 and 0.01, respectively). Overall, both major and minor T-wave abnormalities were significantly more frequent among patients with T2DM compared to the control group, (p = 0.02 and 0.008, respectively). Table 2 compares T wave impairments and T2DM distribution. Table 2 Evaluation the association between the T wave impairments and having diabetes (n = 9035) T-wave impairment Total T2DM P-value No (N = 7762) Yes (N = 1273) Code T 5 − 1 No 9010 (99.70) 7738 (99.70) 1272 (99.90) 0.24 Yes 25 (0.30) 24 (0.30) 1 (0.10) Code T 5 − 2 No 8689 (96.20) 7479 (96.40) 1210 (95.10) 0.02 * yes 346 (3.80) 283 (3.60) 63 (4.90) Code T 5 − 3 No 8814 (97.60) 7585 (97.70) 1229 (96.50) 0.01 * Yes 221 (2.40) 177 (2.30) 44 (3.50) Code T 5 − 4 No 8980 (99.40) 7715 (99.40) 1265 (99.40) 0.92 Yes 55 (0.60) 47 (0.60) 8 (0.60) Major T impairment No 8683 (96.10) 7474 (96.30) 1209 (95.00) 0.02 * Yes 352 (3.90) 288 (3.70) 64 (5.00) Minor T impairment No 8788 (97.30) 7564 (97.40) 1224 (96.20) 0.008 * Yes 247 (2.70) 198 (2.60) 49 (3.80) *Significance level of 0.05; Values are reported as frequency (%). 3.3. T2DM predictive factors Results from the multiple logistic regression models following adjustment for age, BMI, gender, marital status, education, and hypertension variables indicated a significant association between age (OR = 1.05, 95%CI = 1.04–1.05) and BMI (OR = 1.03, 95%CI = 1.02–1.05) and T2DM. Gender, marital status, and educational level did not show a significant relationship (all P > 0.05). Hypertension was reported to increase the risk of diabetes by 1.86 times (95%CI = 1.63–2.12, p < 0.001). According to Table 2 , only major and minor T wave impairments as well as impairments code 5 − 2 and 5 − 3 were reported to be higher among diabetic patients and thus only these items were further analyzed. A model analyzing T-wave abnormality code 5 − 2 and 5 − 3 showed that the odds of having T2DM among patients with T-wave code 5 − 2 and 5 − 3 abnormalities were 1.07 and 1.31 times as those without these abnormalities respectively. This observed difference between patients with and without T-wave abnormalities regarding having diabetes failed to yield statistical significance (P = 0.63 and 0.12, respectively). The area under the ROC curve (AUC) of the final multiple LR model was 0.6847, which indicates a good predictive power of the final model, as shown in Fig. 1 . Using a different regression model for major and minor T-wave abnormality, the odds of having diabetes in patients who had T major and T minor abnormalities were 1.06 and 1.30 times than those without ischemia abnormalities, respectively. However, this difference did not show a significant difference within the logistic regression model (P = 0.65 and 0.11 respectively). The AUC for this model was 0.6846 which suggests a strong predictive power of the final model, as shown in Fig. 2. Table 3 presents the results of the regression model analyses. Table 3 Investigating the association of T wave impairments with having diabetes using multiple LR model Variables (Reference) OR # (%95 CI) P-value Age 1.05 (1.04, 1.05) < 0.001 * BMI 1.03 (1.02, 1.05) < 0.001 * Gender Female Reference - Male 1.01 (0.88, 1.16) 0.88 Marital status Single Reference - Married 1.20 (0.42, 3.37) 0.72 Divorced/ Widowed 1.34 (0.46, 3.85) 0.58 Educational level Illiterate Reference - Lower than diploma 0.94 (0.79, 1.11) 0.48 Higher than diploma 0.73 (0.56, 0.95) 0.02 * Hypertension 1.86 (1.63, 2.12) < 0.001 * T wave impairment code 5 − 2 1.07 (0.80, 1.44) 0.63 T wave impairment code 5 − 3 1.31 (0.92, 1.87) 0.12 Major T-wave impairment 1.06 (0.79, 1.42) 0.65 Minor T-wave impairment 1.30 (0.93, 1.82) 0.11 Adjusted by age, gender, and HTN; # OR = Odds Ratio; *Significance level of 0.05. 4. Discussion The current cross-sectional study aimed to investigate the distribution of t-wave impairment among diabetic patients and its association with diabetes according to the Minnesota coding system. The primary results showed significantly higher rates of code 5 − 2 and 5 − 3 t-wave impairment among diabetic patients. Both minor and major t-wave abnormalities were also significantly higher among diabetics. However, upon adjusting several factors such as age, gender, and hypertension within the regression model, none of the mentioned t-wave abnormalities showed a significant association with T2DM. Myocardial ischemia is a relatively frequent finding among diabetic patients and can potentially lead to coronary artery disease. Patients with myocardial ischemia can present both symptomatic and asymptomatic, with or without previous cardiovascular events. The rates of silent asymptomatic myocardial ischemia have been shown to be three to six times higher among diabetic patients [ 24 ]. Atherosclerosis and endothelial damage of vessels has been shown to be strong risk factors for ischemic heart disease (IHD). On the other hand, the formation of plaque and thrombi can lead to acute forms of myocardial ischemia and coronary syndromes [ 25 , 26 ]. T2DM can contribute vastly to atherogenesis, thrombosis, and vascular damage, therefore leading to increased risks of IHD [ 27 ]. Hyperglycemia, increased levels of free fatty acids, and insulin resistance can lead to several destructive mechanisms such as inflammation, oxidative stress, and the production of advanced glycation products (AGE) [ 27 , 28 ]. Following the increase in AGE production, inflammatory responses are triggered and pro-inflammatory transcription factors such as NF-kB are upregulated [ 29 , 30 ]. Vascular motion is also affected via the reduction in nitric oxide synthesis and enhanced endothelin-1 release. Upregulated pro-thrombotic tissue factor and plasminogen activator inhibitor-1 levels, as well as decreased tissue plasminogen activator within diabetes, can lead to thrombi formation [ 27 , 31 ]. The results of these various mechanisms is endothelial dysfunction, vasoconstriction, and enhanced plaque formations, which as mentioned before, are key components in the development and progression of IHD [ 27 , 31 ]. Several studies have shown TWA among diabetic patients and their utilization as risk predictors. A 2021 study by Molud et al. studied the relationship between TWA and cardiovascular events among diabetic patients [ 32 ]. Minnesota code 5 − 1 and 5 − 2 were considered major TWA and codes 5 − 3 and 5 − 4 were considered to be minor TWAs. Their results indicated that patients with TWA had increased risks of both cardiovascular and all-cause mortality and major TWA was attributed to higher risk than minor TWAs. According to a prospective longitudinal study by Harms et al. 45% of diabetic patients had or develop ECG abnormalities and 7.5% developed major adverse cardiac events within a 6.6-year follow-up period [ 33 ]. Upon grading ECG abnormalities using the Minnesota coding system, 6 and 5% of the diabetic population had minor and major ST-segment/T-wave abnormalities respectively. They also concluded that ST-segment/T-wave abnormalities were associated with heart failure and coronary heart disease. Thus, T-T-wave modifications can be used as risk predictor for cardiovascular events and mortality among diabetic patients. T-wave variation and abnormalities have also been shown within several other diabetes-related pathologies other than IHD. T-wave inversion within some diabetic patients can be explained via hyperkalemia. Diabetic ketoacidosis is a state of hyperkalemia and can result in a variety of ECG modifications affecting T-wave, QT, and ST segments (34). T-wave inversion is also associated with left ventricle hypertrophy findings of ECG among diabetic patients, which might indicate myocardial injury but not coronary disease (35). This finding is contradicted by another study, in which, ST-T changes are significant predictors of coronary artery disease, defined as elevated, depressed, or inversed T waves (36). The observed difference can be due to sample size or ECG coding and grading system. Some of the novel ECG parameters such as the QRS-T angle and T-wave axis of the frontal plane have also been investigated in diabetic patients. It has been shown that 20.9% of diabetic patients have abnormal T-wave axis while 14% of them have increased QRS-T angle. The authors also concluded these two ECG parameters are associated with some atherosclerotic disease markers among type II diabetic patients [ 34 ]. Studies on the relationship between diabetes and t-wave changes have controversial results. A Chinese study investigated ECG abnormalities within several disorders such as hypertension, smoking, obesity, and so forth [ 35 ]. Diabetes was found to be associated with ST elevation but failed to show a significant correlation with other electrocardiogram findings such as ST depression, T-wave and Q-wave impairment, tall R wave, atrial hypertrophy, and axial deviations. Unlike diabetes, hypertension, and hypercholesterolemia were significantly attributed to ST depression and T-wave abnormalities. These findings are in line with the results of our study, since upon adjustment, none of the T-wave abnormalities were associated with diabetes. However, two studies showed a contrary result. Flatter and asymmetric T-waves were observed in patients with type I diabetes, according to the study by Isaksen et al. [ 36 ]. This association was also confirmed by a regression model corrected for age, gender, BMI, blood pressure, potassium, and cholesterol. Interestingly, asymmetrical t-wave was significantly associated with both macro and microalbuminuria among type I diabetic patients. An Italian cross-sectional study also confirmed this finding and suggests higher rates of T-wave axis abnormalities – described as T-wave rotation in the frontal plane – in diabetic patients compared to non-diabetic individuals [ 37 ]. These differences could be due to a lack of differentiating diabetes types, as well as the ethnicity of the study population. Even though our analysis showed no significant association between T2DM and T-wave changes in the ECG, several other factors such as hypertension, age, and BMI were significantly associated with diabetes. A meta-analysis of a total of 452584 patients also showed similar results about the association between diabetes and hypertension (pooled OR:8.32, 95%CI: 3.05–22.71) [ 38 ]. Our results indicated no significant relationship between gender and diabetes, whereas some studies show a significant contribution of sex and diabetes. A longitudinal study in Iran showed significantly higher rates of T2DM among females while the global prevalence is higher in men [ 39 , 40 ]. These differences in findings can be due to sampling size as well as not differentiating the type of diabetes among different studies. This study is one of very few studies to differentiate T-wave abnormalities into six categories, while most of the studies only summarize them in two. Second, a large population (n = 9035) was examined and observed in this cross-section study which belonged to the MASHAD cohort study. Third, some of the interpretations were also controlled by certified cardiologists which reduce the chances of errors. However, our study faced several limitations which need to be considered for future studies. First, available documentation did not differentiate type I or II diabetes, and thus, exact conclusions cannot be made for each type. Second, the age group of the study was limited to 35–65 years old, and variation might exist in ages above or below the cutoff used in our study. Third, only t-waves were used for ischemic changes of the heart, and future studies can use several other modalities, such as other ECG findings, and other para-clinical values to further confirm ischemic diseases of the heart due to diabetes. We also highly encourage future researchers to perform multi-central cohort studies in order to precisely evaluate the relationship between the two. High-quality meta-analyses are needed for confirming our findings. 5. Conclusion The results of this study showed a significantly higher prevalence of Minnesota codes 5 − 2, 5 − 3, major and minor T-wave abnormalities in diabetic patients compared to non-diabetic individuals. However, the association between these abnormalities was not significant using regression models and adjusting for age, gender, and BMI. Considering the aberrant diabetes complications, especially cardiovascular ones, it is highly important to investigate CVD diagnostic tools among diabetics. Given the contrary results of other studies, large-scale studies on the topic of using t-wave abnormalities as ischemic pathologies resulting from diabetes are needed for further identification of sufficient indicative and predictive tools. Abbreviations T2DM Type 2 Diabetes Mellitus TWA T-wave abnormalities ECG Electrocardiogram CVD Cardiovascular disease MASHAD Mashhad stroke and heart atherosclerotic disorder FBG Fasting blood glucose LR Logistic regression ROC Receiver operating characteristic BMI Body mass index AUC Area under the ROC curve IHD Ischemic heart disease AGE Advanced glycation products Declarations Ethics approval and consent of participant: The study protocol was given approval by the Ethics Committee of Mashhad University of Medical Sciences (MASHAD study code: 85134). Informed consents were obtained from all participants. All study methods were conducted in accordance with ethical guidelines and principals of the Declaration of Helsinki [41]. Consent of publication: Not applicable. Availability of data and materials: The data that support the findings of this study are available from [Mashhad University of medical sciences], but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of [Mashhad University of medical sciences]. Competing interests: There is no competing interest. Funding: The collection of clinical data was financially supported by Mashhad University of Medical Sciences. Author contributions All authors have read and approved the manuscript. Study concept and design: Sara Saffar Soflaei and Azadeh Izadi-Moud; data collection: Farzad Fayedeh, Mahmoud Ebrahimi, Hedieh Alimi, Bahram Shahri, Alireza Ghodsi, Saeed Mehrabi, and Milad Tarhimi; Analysis and interpretation of data: Isa Nazar and Habibollah Esmaily; Drafting of the manuscript: Toktam Sahranavard and AmirAli Moodi Ghalibaf; Critical revision of the manuscript for important intellectual content: Gordon A. Ferns, Majid Ghayour-Mobarhan, and Mohsen Moohebati. Acknowledgements : We would like to thank Mashhad University of Medical Sciences for supporting this study. References Duan D, Kengne AP, Echouffo-Tcheugui JB. Screening for Diabetes and Prediabetes. Endocrinol Metab Clin North Am. 2021;50(3):369–85. Zheng Y, Ley SH, Hu FB. Global aetiology and epidemiology of type 2 diabetes mellitus and its complications. Nat Rev Endocrinol. 2018;14(2):88–98. Ali MK, Narayan KM, Tandon N. Diabetes & coronary heart disease: current perspectives. 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J Electrocardiol. 2018;51(6s):72–s77. Assanelli D, Di Castelnuovo A, Rago L, Badilini F, Vinetti G, Gianfagna F, Salvetti M, Zito F, Donati MB, De Gaetano G. T-wave axis deviation and left ventricular hypertrophy interaction in diabetes and hypertension. J Electrocardiol. 2013;46(6):487–91. Tesfaye B, Alebel A, Gebrie A, Zegeye A, Tesema Leshargie C, Ferede A, Abera H, Alam K. Diabetes Mellitus and Its Association with Hypertension in Ethiopia: A Systematic Review and Meta-Analysis. Diabetes Res Clin Pract. 2019;156:107838. Mirzaei M, Rahmaninan M, Mirzaei M, Nadjarzadeh A, Dehghani tafti AA. Epidemiology of diabetes mellitus, pre-diabetes, undiagnosed and uncontrolled diabetes in Central Iran: results from Yazd health study. BMC Public Health. 2020;20(1):166. Ciarambino T, Crispino P, Leto G, Mastrolorenzo E, Para O, Giordano M. Influence of Gender in Diabetes Mellitus and Its Complication. Int J Mol Sci 2022, 23(16). World Medical Association. Declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA. 2013;310(20):2191–4. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 13 Jan, 2024 Read the published version in BMC Cardiovascular Disorders → Version 1 posted Editorial decision: Major revision 19 Sep, 2023 Reviews received at journal 24 Aug, 2023 Reviewers agreed at journal 24 Aug, 2023 Reviewers agreed at journal 24 Aug, 2023 Reviewers invited by journal 24 Aug, 2023 Editor assigned by journal 24 Aug, 2023 Editor invited by journal 24 Aug, 2023 Submission checks completed at journal 24 Aug, 2023 First submitted to journal 30 Jul, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3216881","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":228538301,"identity":"f3789019-e389-4b4f-9abc-35f5ba27491a","order_by":0,"name":"Sara Saffar Soflaei","email":"","orcid":"","institution":"Mashhad University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sara","middleName":"Saffar","lastName":"Soflaei","suffix":""},{"id":228538302,"identity":"d78b407d-e38e-43b5-b8da-760be2f9f3cf","order_by":1,"name":"Isa Nazar","email":"","orcid":"","institution":"Mashhad University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Isa","middleName":"","lastName":"Nazar","suffix":""},{"id":228538303,"identity":"23c07f00-f648-4334-976c-2c9775e3be13","order_by":2,"name":"Toktam Sahranavard","email":"","orcid":"","institution":"Mashhad University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Toktam","middleName":"","lastName":"Sahranavard","suffix":""},{"id":228538304,"identity":"89bc78bd-3802-4144-81e6-e1e3dae23c0a","order_by":3,"name":"Farzad Fayedeh","email":"","orcid":"","institution":"Birjand University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Farzad","middleName":"","lastName":"Fayedeh","suffix":""},{"id":228538305,"identity":"5d262241-48d8-4b0a-b87b-4b839d43091b","order_by":4,"name":"AmirAli Moodi Ghalibaf","email":"","orcid":"","institution":"Birjand University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"AmirAli","middleName":"Moodi","lastName":"Ghalibaf","suffix":""},{"id":228538306,"identity":"be3e63c9-0996-43a3-ac99-27b67e6a0c61","order_by":5,"name":"Mahmoud Ebrahimi","email":"","orcid":"","institution":"Mashhad University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mahmoud","middleName":"","lastName":"Ebrahimi","suffix":""},{"id":228538307,"identity":"2f687987-6888-4b27-92e4-900c2c4bcdf0","order_by":6,"name":"Hedieh Alimi","email":"","orcid":"","institution":"Mashhad University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hedieh","middleName":"","lastName":"Alimi","suffix":""},{"id":228538308,"identity":"96cf138c-33d2-4fe6-89b2-0f1e1253fa90","order_by":7,"name":"Bahram Shahri","email":"","orcid":"","institution":"Mashhad University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bahram","middleName":"","lastName":"Shahri","suffix":""},{"id":228538309,"identity":"4304b384-03aa-45e6-b156-21311893cfd9","order_by":8,"name":"Azadeh Izadi-Moud","email":"","orcid":"","institution":"Mashhad University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Azadeh","middleName":"","lastName":"Izadi-Moud","suffix":""},{"id":228538310,"identity":"759c0c30-26db-4ae6-87fe-d19721258419","order_by":9,"name":"Gordon A. Ferns","email":"","orcid":"","institution":"Brighton and Sussex Medical School","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Gordon","middleName":"A.","lastName":"Ferns","suffix":""},{"id":228538311,"identity":"ea69d973-f1ed-46e0-bc8a-30464acabff6","order_by":10,"name":"Alireza Ghodsi","email":"","orcid":"","institution":"Mashhad University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Alireza","middleName":"","lastName":"Ghodsi","suffix":""},{"id":228538312,"identity":"24ab8890-bd55-420f-8f3c-3ea1bac3a121","order_by":11,"name":"Saeed Mehrabi","email":"","orcid":"","institution":"Gonabad University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Saeed","middleName":"","lastName":"Mehrabi","suffix":""},{"id":228538313,"identity":"5b5a87fe-9a1d-48e4-ab9e-1b38baec69ba","order_by":12,"name":"Milad Tarhimi","email":"","orcid":"","institution":"Gonabad University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Milad","middleName":"","lastName":"Tarhimi","suffix":""},{"id":228538314,"identity":"28bb5fe1-1155-42bc-b419-59f417dc0126","order_by":13,"name":"Habibollah Esmaily","email":"","orcid":"","institution":"Mashhad University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Habibollah","middleName":"","lastName":"Esmaily","suffix":""},{"id":228538315,"identity":"e2bcbfd6-2748-4eee-9a1e-68e6efbb6165","order_by":14,"name":"Mohsen Moohebati","email":"","orcid":"","institution":"Mashhad University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mohsen","middleName":"","lastName":"Moohebati","suffix":""},{"id":228538316,"identity":"1af6e79b-14fb-494f-a94e-a7ee384843ac","order_by":15,"name":"Majid Ghayour-Mobarhan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2ElEQVRIiWNgGAWjYBAC/hkQOrEfLsRMQIvEDQhdPLOBWC0GEhC6fsMBYh1mIN38TOJj273czdfOmG78wWAnz8DO+wC/FpljZpIz24pzt93OMbvNw5Bs2MDMboBXi+GNBDNp3rYEiBagRxIYmNkIOOxG+jeQlsTNs3PMbv5gqCdGSw7YlsQN0jlmN3gYDhPWInEjp9hyxrmExBm308pu8xgcN2wjpIV/RvrGGx/KEhL7Zydvu/mjolqen/8Yfi1AwCKB5E4GBgJ2gAHzByIUjYJRMApGwUgGAPgTQvs7+BayAAAAAElFTkSuQmCC","orcid":"","institution":"Mashhad University of Medical Sciences","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Majid","middleName":"","lastName":"Ghayour-Mobarhan","suffix":""}],"badges":[],"createdAt":"2023-07-30 05:14:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3216881/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3216881/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12872-023-03649-2","type":"published","date":"2024-01-13T15:02:12+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":42317889,"identity":"30e83048-8607-41c2-9aea-bf266c829cff","added_by":"auto","created_at":"2023-08-29 16:30:00","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":34599,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eshowing predictive power of final multiple LR model of T-wave abnormality code 5-2 and 5-3 and diabetes\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3216881/v1/a7840faafbd4d354ccdd5c3c.png"},{"id":42317888,"identity":"6af7345d-8588-463a-8ddb-78cea2ca81cc","added_by":"auto","created_at":"2023-08-29 16:30:00","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":34394,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eshowing predictive power of final multiple LR model of major and minor T wave abnormality and diabetes.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3216881/v1/1782e0e606007602a871c4b1.png"},{"id":49629374,"identity":"5f5a3b50-b98d-4863-881e-89e29a0e7717","added_by":"auto","created_at":"2024-01-15 15:10:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":483035,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3216881/v1/82b3aafc-0c06-4505-bce3-8e4f3fcc7d8c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association of T-wave Changes and Type 2 diabetes: A cross-sectional sub-analysis of MASHAD cohort population using Minnesota coding system of Electrocardiogram","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eType 2 Diabetes Mellitus (T2DM) is a complex condition associated with impaired glucose tolerance, insulin resistance and hyperglycaemia, with an increasing prevalence and has become a serious global health challenge. It is accountable for 11.3% of deaths worldwide and is believed to affect approximately 10.9% of the global population [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. T2DM is accompanied by debilitating complications such as kidney disease, retinopathy, neuropathy, microvascular impairments, and cardiovascular complications [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCardiovascular complications are responsible for up to 68% of all diabetes-related mortalities. Several studies have revealed that patients with diabetes are at increased risk of coronary disease [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], myocardial infarction [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], heart failure [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], cardiomyopathy [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], and thrombotic events [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. It has been shown that diabetic patients have a two- to three-fold increase in cardiovascular disease (CVD) development [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Various mechanisms have been proposed to explain the increased CVD rates among diabetic patients. Higher incidence of dyslipidemia [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], chronic inflammatory states [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], enhanced oxidative stress and reactive oxygen species [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], and hypercoagulability [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] are some of the key findings in patients with diabetes that can potentially increase atherosclerosis, plaque formation, and consequently result in increased rates of CVD [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Thus, it is of great importance to investigate sufficient early detection methods and effective therapeutic approaches for CVD among diabetic patients.\u003c/p\u003e \u003cp\u003eAn electrocardiogram (ECG) is a recording of cardiac electrical activities. An ECG is a useful and non-invasive assessment that has been utilized for several biomedical uses such as the determination of arrhythmias, fibrillations, heart rates, premature contractions and ischemia [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. T-wave in ECG represents ventricular repolarization. T-wave abnormalities (TWA) can be an indicator of a variety of conditions such as cardiomyopathy, pulmonary embolism, peri- and myocarditis, and ischemia [\u003cspan additionalcitationids=\"CR19 CR20\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGiven the importance of T2DM and its complication \u0026ndash; especially those affecting the cardiovascular system \u0026ndash; as well as considering the ease of accessibility and practicality of ECG in medical practice, this cross-section study was designed to investigate the prevalence of T-wave abnormalities and its association with T2DM.\u003c/p\u003e"},{"header":"2. Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study design and participants:\u003c/h2\u003e \u003cp\u003eThe current cross-sectional study was conducted on the population of Mashhad stroke and heart atherosclerotic disorder (MASHAD) cohort [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. All the participants aged from 35 to 65 years old were enrolled in the study from the cohort population. A checklist containing participants\u0026rsquo; demographic data including age, sex, educational level, and marital status was recorded. Patients whose systolic blood pressure levels were at or above 140 mmHg and/or diastolic blood pressure were at or beyond 90 mmHg - measured using a mercury sphygmomanometer- were considered hypertensive. A fasting blood glucose (FBG) over 126 mg/dl or being under anti-hyperglycemic medication was defined as diabetic patients. The FBG was provided by a peripheral blood sample following 14 hours of fasting. The study was approved by the Human Research ethics committee of Mashhad University of Medical Sciences, Mashhad, Iran, and all participants provided informed consent prior to data collection.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. ECG analysis:\u003c/h2\u003e \u003cp\u003eA standard resting 12-lead ECG was taken from each participant of the study. These ECGs were interpreted by instructed medical students in accordance with Minnesota coding system [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Five percent of all ECGs were also read by certified cardiologists.\u003c/p\u003e \u003cp\u003eFour different t-wave abnormalities were described within the coding system including codes 5\u0026thinsp;\u0026minus;\u0026thinsp;1, 5\u0026thinsp;\u0026minus;\u0026thinsp;2, 5\u0026thinsp;\u0026minus;\u0026thinsp;3 and 5\u0026thinsp;\u0026minus;\u0026thinsp;4. The code 5\u0026thinsp;\u0026minus;\u0026thinsp;1 was defined as T amplitude negative 5.0 mm or more in either of leads I, V6, or in lead aVL when R amplitude is \u0026ge;\u0026thinsp;5.0 mm. Code 5\u0026thinsp;\u0026minus;\u0026thinsp;2 was defined as T amplitude negative 5.0 mm or more in either of leads I, V6, or in lead aVL when R amplitude is \u0026ge;\u0026thinsp;5.0 mm. Code 5\u0026thinsp;\u0026minus;\u0026thinsp;3 was described as flat, negative or diphasic t-wave with less than 1 mm negative phase in any leads of I, II or V3 to V6 or in lead aVL when the R amplitude is \u0026ge;\u0026thinsp;5.0 mm. Lastly, code 5\u0026thinsp;\u0026minus;\u0026thinsp;4 was defined as a positive T amplitude and a T/R amplitude ratio\u0026thinsp;\u0026lt;\u0026thinsp;1:20 in any of leads I, II, aVL, or V3 through V6. The R-wave amplitude must be \u0026ge;\u0026thinsp;10.0 mm [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Statistical analysis:\u003c/h2\u003e \u003cp\u003eQualitative and quantitative variables were summarized as Mean\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003eSD and frequency (%), respectively. An Independent t-test was used in order to compare the mean of quantitative variables between the two groups. In addition, evaluating the association between qualitative variables was performed using Chi-square and Fisher's exact test. Further analyses were performed in order to investigate the association between T wave impairments and T2DM after adjusting the effect of potential confounders (variables with P\u0026thinsp;\u0026lt;\u0026thinsp;0.25 in the univariate logistic regression model) and using the multiple logistic regression (LR) model. Furthermore, receiver operating characteristic (ROC) curves were used to evaluate the ability of the multiple LR model to predict the occurrence of TWA and T2DM. All statistical analyses were carried out using SPSS version 20 and the statistical significance level was considered at 0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Study population characteristics\u003c/h2\u003e \u003cp\u003eA total of 9035 individuals were enrolled into the cohort study, including 1273 diabetic patients and 7762 non-diabetic individuals. The average age was 47.45\u0026thinsp;\u0026plusmn;\u0026thinsp;8.17 and 51.77\u0026thinsp;\u0026plusmn;\u0026thinsp;7.73 in non-diabetic and diabetic patients which differed significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Diabetic patients were found to have higher body mass index (BMI), as well as higher rates of hypertension (50.3 vs 27.9%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Marital status and educational levels also showed a significant different distribution between the two diabetic and non-diabetic groups with married being the most prevalent status among studied groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents patients\u0026rsquo; demographic data distributions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparing the frequency distribution of demographical characteristics between individuals with and without diabetes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eT2DM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo (N\u0026thinsp;=\u0026thinsp;7762)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes (N\u0026thinsp;=\u0026thinsp;1273)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.77\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e7.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.45\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e8.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e51.77\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e7.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBody mass index (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.93\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e4.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.71\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e4.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.93\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e4.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3615 (40.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3129 (40.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e486 (38.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5420 (60.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4633 (59.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e787 (61.80)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55 (0.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51 (0.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4 (0.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8418 (93.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7262 (93.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1156 (90.80)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDivorced/widowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e562 (6.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e449 (5.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e113 (8.90)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eEducation level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1155 (12.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e927 (11.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e228 (17.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLower than diploma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6815 (75.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5881 (75.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e934 (73.40)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigher than diploma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1065 (11.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e954 (12.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e111 (8.70)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6220 (69.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5589 (72.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e631 (49.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2798 (31.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2159 (27.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e639 (50.30)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e*Significance level of 0.05; Values are reported as Mean\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003eSD and frequency (%).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2. T-wave abnormality frequency\u003c/h2\u003e \u003cp\u003eA total of 1246 T wave abnormalities were reported among the study sample population, approximately 13.79% of all participants. The most frequent T-wave abnormalities among both groups were code 5\u0026thinsp;\u0026minus;\u0026thinsp;2 (4.9% in diabetics and 3.6% in the control group) and major T-wave abnormalities (5% in diabetics and 3.7% in the control group). Different T-wave abnormalities yielded varying associations with T2DM. While T-wave abnormalities code 5\u0026thinsp;\u0026minus;\u0026thinsp;1 and 5\u0026thinsp;\u0026minus;\u0026thinsp;4 failed to show a significantly different distribution among diabetic and non-diabetic participants (P\u0026thinsp;=\u0026thinsp;0.24 and 0.92 respectively), code 5\u0026thinsp;\u0026minus;\u0026thinsp;2 and 5\u0026thinsp;\u0026minus;\u0026thinsp;3 were shown to be significantly higher among diabetic patients compared to the non-diabetic individuals (P\u0026thinsp;=\u0026thinsp;0.02 and 0.01, respectively). Overall, both major and minor T-wave abnormalities were significantly more frequent among patients with T2DM compared to the control group, (p\u0026thinsp;=\u0026thinsp;0.02 and 0.008, respectively). Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e compares T wave impairments and T2DM distribution.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEvaluation the association between the T wave impairments and having diabetes (n\u0026thinsp;=\u0026thinsp;9035)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eT-wave impairment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eT2DM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo (N\u0026thinsp;=\u0026thinsp;7762)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes (N\u0026thinsp;=\u0026thinsp;1273)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCode T 5\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9010 (99.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7738 (99.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1272 (99.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (0.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24 (0.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (0.10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCode T 5\u0026thinsp;\u0026minus;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8689 (96.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7479 (96.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1210 (95.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.02\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e346 (3.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e283 (3.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63 (4.90)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCode T 5\u0026thinsp;\u0026minus;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8814 (97.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7585 (97.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1229 (96.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.01\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e221 (2.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e177 (2.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44 (3.50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCode T 5\u0026thinsp;\u0026minus;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8980 (99.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7715 (99.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1265 (99.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55 (0.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47 (0.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 (0.60)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMajor T impairment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8683 (96.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7474 (96.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1209 (95.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.02\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e352 (3.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e288 (3.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64 (5.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMinor T impairment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8788 (97.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7564 (97.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1224 (96.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.008\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e247 (2.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e198 (2.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49 (3.80)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e*Significance level of 0.05; Values are reported as frequency (%).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.3. T2DM predictive factors\u003c/h2\u003e \u003cp\u003eResults from the multiple logistic regression models following adjustment for age, BMI, gender, marital status, education, and hypertension variables indicated a significant association between age (OR\u0026thinsp;=\u0026thinsp;1.05, 95%CI\u0026thinsp;=\u0026thinsp;1.04\u0026ndash;1.05) and BMI (OR\u0026thinsp;=\u0026thinsp;1.03, 95%CI\u0026thinsp;=\u0026thinsp;1.02\u0026ndash;1.05) and T2DM. Gender, marital status, and educational level did not show a significant relationship (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Hypertension was reported to increase the risk of diabetes by 1.86 times (95%CI\u0026thinsp;=\u0026thinsp;1.63\u0026ndash;2.12, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). According to Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, only major and minor T wave impairments as well as impairments code 5\u0026thinsp;\u0026minus;\u0026thinsp;2 and 5\u0026thinsp;\u0026minus;\u0026thinsp;3 were reported to be higher among diabetic patients and thus only these items were further analyzed. A model analyzing T-wave abnormality code 5\u0026thinsp;\u0026minus;\u0026thinsp;2 and 5\u0026thinsp;\u0026minus;\u0026thinsp;3 showed that the odds of having T2DM among patients with T-wave code 5\u0026thinsp;\u0026minus;\u0026thinsp;2 and 5\u0026thinsp;\u0026minus;\u0026thinsp;3 abnormalities were 1.07 and 1.31 times as those without these abnormalities respectively. This observed difference between patients with and without T-wave abnormalities regarding having diabetes failed to yield statistical significance (P\u0026thinsp;=\u0026thinsp;0.63 and 0.12, respectively). The area under the ROC curve (AUC) of the final multiple LR model was 0.6847, which indicates a good predictive power of the final model, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Using a different regression model for major and minor T-wave abnormality, the odds of having diabetes in patients who had T major and T minor abnormalities were 1.06 and 1.30 times than those without ischemia abnormalities, respectively. However, this difference did not show a significant difference within the logistic regression model (P\u0026thinsp;=\u0026thinsp;0.65 and 0.11 respectively). The AUC for this model was 0.6846 which suggests a strong predictive power of the final model, as shown in Fig.\u0026nbsp;2. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the results of the regression model analyses.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInvestigating the association of T wave impairments with having diabetes using multiple LR model\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eVariables (Reference)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR\u003csup\u003e#\u003c/sup\u003e (%95 CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.05 (1.04, 1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.03 (1.02, 1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.01 (0.88, 1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.20 (0.42, 3.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDivorced/ Widowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.34 (0.46, 3.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eEducational level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLower than diploma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.94 (0.79, 1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigher than diploma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.73 (0.56, 0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.86 (1.63, 2.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eT wave impairment code 5\u0026thinsp;\u0026minus;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.07 (0.80, 1.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eT wave impairment code 5\u0026thinsp;\u0026minus;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.31 (0.92, 1.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMajor T-wave impairment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.06 (0.79, 1.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMinor T-wave impairment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.30 (0.93, 1.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eAdjusted by age, gender, and HTN; # OR\u0026thinsp;=\u0026thinsp;Odds Ratio; *Significance level of 0.05.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e The current cross-sectional study aimed to investigate the distribution of t-wave impairment among diabetic patients and its association with diabetes according to the Minnesota coding system. The primary results showed significantly higher rates of code 5\u0026thinsp;\u0026minus;\u0026thinsp;2 and 5\u0026thinsp;\u0026minus;\u0026thinsp;3 t-wave impairment among diabetic patients. Both minor and major t-wave abnormalities were also significantly higher among diabetics. However, upon adjusting several factors such as age, gender, and hypertension within the regression model, none of the mentioned t-wave abnormalities showed a significant association with T2DM.\u003c/p\u003e \u003cp\u003eMyocardial ischemia is a relatively frequent finding among diabetic patients and can potentially lead to coronary artery disease. Patients with myocardial ischemia can present both symptomatic and asymptomatic, with or without previous cardiovascular events. The rates of silent asymptomatic myocardial ischemia have been shown to be three to six times higher among diabetic patients [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Atherosclerosis and endothelial damage of vessels has been shown to be strong risk factors for ischemic heart disease (IHD). On the other hand, the formation of plaque and thrombi can lead to acute forms of myocardial ischemia and coronary syndromes [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. T2DM can contribute vastly to atherogenesis, thrombosis, and vascular damage, therefore leading to increased risks of IHD [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Hyperglycemia, increased levels of free fatty acids, and insulin resistance can lead to several destructive mechanisms such as inflammation, oxidative stress, and the production of advanced glycation products (AGE) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Following the increase in AGE production, inflammatory responses are triggered and pro-inflammatory transcription factors such as NF-kB are upregulated [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Vascular motion is also affected via the reduction in nitric oxide synthesis and enhanced endothelin-1 release. Upregulated pro-thrombotic tissue factor and plasminogen activator inhibitor-1 levels, as well as decreased tissue plasminogen activator within diabetes, can lead to thrombi formation [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The results of these various mechanisms is endothelial dysfunction, vasoconstriction, and enhanced plaque formations, which as mentioned before, are key components in the development and progression of IHD [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral studies have shown TWA among diabetic patients and their utilization as risk predictors. A 2021 study by Molud et al. studied the relationship between TWA and cardiovascular events among diabetic patients [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Minnesota code 5\u0026thinsp;\u0026minus;\u0026thinsp;1 and 5\u0026thinsp;\u0026minus;\u0026thinsp;2 were considered major TWA and codes 5\u0026thinsp;\u0026minus;\u0026thinsp;3 and 5\u0026thinsp;\u0026minus;\u0026thinsp;4 were considered to be minor TWAs. Their results indicated that patients with TWA had increased risks of both cardiovascular and all-cause mortality and major TWA was attributed to higher risk than minor TWAs. According to a prospective longitudinal study by Harms et al. 45% of diabetic patients had or develop ECG abnormalities and 7.5% developed major adverse cardiac events within a 6.6-year follow-up period [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Upon grading ECG abnormalities using the Minnesota coding system, 6 and 5% of the diabetic population had minor and major ST-segment/T-wave abnormalities respectively. They also concluded that ST-segment/T-wave abnormalities were associated with heart failure and coronary heart disease. Thus, T-T-wave modifications can be used as risk predictor for cardiovascular events and mortality among diabetic patients.\u003c/p\u003e \u003cp\u003eT-wave variation and abnormalities have also been shown within several other diabetes-related pathologies other than IHD. T-wave inversion within some diabetic patients can be explained via hyperkalemia. Diabetic ketoacidosis is a state of hyperkalemia and can result in a variety of ECG modifications affecting T-wave, QT, and ST segments (34). T-wave inversion is also associated with left ventricle hypertrophy findings of ECG among diabetic patients, which might indicate myocardial injury but not coronary disease (35). This finding is contradicted by another study, in which, ST-T changes are significant predictors of coronary artery disease, defined as elevated, depressed, or inversed T waves (36). The observed difference can be due to sample size or ECG coding and grading system.\u003c/p\u003e \u003cp\u003eSome of the novel ECG parameters such as the QRS-T angle and T-wave axis of the frontal plane have also been investigated in diabetic patients. It has been shown that 20.9% of diabetic patients have abnormal T-wave axis while 14% of them have increased QRS-T angle. The authors also concluded these two ECG parameters are associated with some atherosclerotic disease markers among type II diabetic patients [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eStudies on the relationship between diabetes and t-wave changes have controversial results. A Chinese study investigated ECG abnormalities within several disorders such as hypertension, smoking, obesity, and so forth [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Diabetes was found to be associated with ST elevation but failed to show a significant correlation with other electrocardiogram findings such as ST depression, T-wave and Q-wave impairment, tall R wave, atrial hypertrophy, and axial deviations. Unlike diabetes, hypertension, and hypercholesterolemia were significantly attributed to ST depression and T-wave abnormalities. These findings are in line with the results of our study, since upon adjustment, none of the T-wave abnormalities were associated with diabetes. However, two studies showed a contrary result. Flatter and asymmetric T-waves were observed in patients with type I diabetes, according to the study by Isaksen et al. [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. This association was also confirmed by a regression model corrected for age, gender, BMI, blood pressure, potassium, and cholesterol. Interestingly, asymmetrical t-wave was significantly associated with both macro and microalbuminuria among type I diabetic patients. An Italian cross-sectional study also confirmed this finding and suggests higher rates of T-wave axis abnormalities \u0026ndash; described as T-wave rotation in the frontal plane \u0026ndash; in diabetic patients compared to non-diabetic individuals [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. These differences could be due to a lack of differentiating diabetes types, as well as the ethnicity of the study population.\u003c/p\u003e \u003cp\u003eEven though our analysis showed no significant association between T2DM and T-wave changes in the ECG, several other factors such as hypertension, age, and BMI were significantly associated with diabetes. A meta-analysis of a total of 452584 patients also showed similar results about the association between diabetes and hypertension (pooled OR:8.32, 95%CI: 3.05\u0026ndash;22.71) [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Our results indicated no significant relationship between gender and diabetes, whereas some studies show a significant contribution of sex and diabetes. A longitudinal study in Iran showed significantly higher rates of T2DM among females while the global prevalence is higher in men [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. These differences in findings can be due to sampling size as well as not differentiating the type of diabetes among different studies.\u003c/p\u003e \u003cp\u003eThis study is one of very few studies to differentiate T-wave abnormalities into six categories, while most of the studies only summarize them in two. Second, a large population (n\u0026thinsp;=\u0026thinsp;9035) was examined and observed in this cross-section study which belonged to the MASHAD cohort study. Third, some of the interpretations were also controlled by certified cardiologists which reduce the chances of errors. However, our study faced several limitations which need to be considered for future studies. First, available documentation did not differentiate type I or II diabetes, and thus, exact conclusions cannot be made for each type. Second, the age group of the study was limited to 35\u0026ndash;65 years old, and variation might exist in ages above or below the cutoff used in our study. Third, only t-waves were used for ischemic changes of the heart, and future studies can use several other modalities, such as other ECG findings, and other para-clinical values to further confirm ischemic diseases of the heart due to diabetes. We also highly encourage future researchers to perform multi-central cohort studies in order to precisely evaluate the relationship between the two. High-quality meta-analyses are needed for confirming our findings.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe results of this study showed a significantly higher prevalence of Minnesota codes 5\u0026thinsp;\u0026minus;\u0026thinsp;2, 5\u0026thinsp;\u0026minus;\u0026thinsp;3, major and minor T-wave abnormalities in diabetic patients compared to non-diabetic individuals. However, the association between these abnormalities was not significant using regression models and adjusting for age, gender, and BMI. Considering the aberrant diabetes complications, especially cardiovascular ones, it is highly important to investigate CVD diagnostic tools among diabetics. Given the contrary results of other studies, large-scale studies on the topic of using t-wave abnormalities as ischemic pathologies resulting from diabetes are needed for further identification of sufficient indicative and predictive tools.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eT2DM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eType 2 Diabetes Mellitus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTWA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eT-wave abnormalities\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eECG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eElectrocardiogram\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCVD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCardiovascular disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMASHAD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMashhad stroke and heart atherosclerotic disorder\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFBG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFasting blood glucose\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLogistic regression\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReceiver operating characteristic\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBody mass index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAUC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eArea under the ROC curve\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIHD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIschemic heart disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAGE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAdvanced glycation products\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent of participant:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was given approval by the Ethics Committee of Mashhad University of Medical Sciences (MASHAD study code: 85134). Informed consents were obtained from all participants. All study methods were conducted in accordance with ethical guidelines and principals of the Declaration of Helsinki [41].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent of publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from [Mashhad University of medical sciences], but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of [Mashhad University of medical sciences].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is no competing interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe collection of clinical data was financially supported by Mashhad University of Medical Sciences.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have read and approved the manuscript. Study concept and design: Sara Saffar Soflaei and Azadeh Izadi-Moud; data collection: Farzad Fayedeh, Mahmoud Ebrahimi, Hedieh Alimi, Bahram Shahri, Alireza Ghodsi, Saeed Mehrabi, and Milad Tarhimi; Analysis and interpretation of data: Isa Nazar and Habibollah Esmaily; Drafting of the manuscript: Toktam Sahranavard and AmirAli Moodi Ghalibaf; Critical revision of the manuscript for important intellectual content: Gordon A. Ferns, Majid Ghayour-Mobarhan, and Mohsen Moohebati.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eWe would like to thank Mashhad University of Medical Sciences for supporting this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDuan D, Kengne AP, Echouffo-Tcheugui JB. Screening for Diabetes and Prediabetes. 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Association of T-wave abnormalities with major cardiovascular events in diabetes: the ACCORD trial. Diabetologia. 2021;64(3):504\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarms PP, Elders P, Rutters F, Lissenberg-Witte BI, Tan HL, Beulens JWJ, Nijpels G, van der Heijden AA. Longitudinal association of electrocardiogram abnormalities with major adverse cardiac events in people with Type 2 diabetes: the Hoorn Diabetes Care System cohort. Eur J Prev Cardiol. 2023;30(8):624\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCardoso CR, Leite NC, Salles GF. Factors associated with abnormal T-wave axis and increased QRS-T angle in type 2 diabetes. Acta Diabetol. 2013;50(6):919\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYu L, Ye X, Yang Z, Yang W, Zhang B. Prevalences and associated factors of electrocardiographic abnormalities in Chinese adults: a cross-sectional study. BMC Cardiovasc Disord. 2020;20(1):414.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIsaksen JL, Graff C, Ellervik C, Jensen JS, Andersen HU, Rossing P, Kanters JK, Jensen MT. Type 1 diabetes is associated with T-wave morphology changes. The Thousand \u0026amp; 1 Study. J Electrocardiol. 2018;51(6s):72\u0026ndash;s77.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAssanelli D, Di Castelnuovo A, Rago L, Badilini F, Vinetti G, Gianfagna F, Salvetti M, Zito F, Donati MB, De Gaetano G. T-wave axis deviation and left ventricular hypertrophy interaction in diabetes and hypertension. J Electrocardiol. 2013;46(6):487\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTesfaye B, Alebel A, Gebrie A, Zegeye A, Tesema Leshargie C, Ferede A, Abera H, Alam K. Diabetes Mellitus and Its Association with Hypertension in Ethiopia: A Systematic Review and Meta-Analysis. Diabetes Res Clin Pract. 2019;156:107838.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMirzaei M, Rahmaninan M, Mirzaei M, Nadjarzadeh A, Dehghani tafti AA. Epidemiology of diabetes mellitus, pre-diabetes, undiagnosed and uncontrolled diabetes in Central Iran: results from Yazd health study. BMC Public Health. 2020;20(1):166.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCiarambino T, Crispino P, Leto G, Mastrolorenzo E, Para O, Giordano M. Influence of Gender in Diabetes Mellitus and Its Complication. Int J Mol Sci 2022, 23(16).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Medical Association. Declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA. 2013;310(20):2191\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Electrocardiogram, Type 2 Diabetes Mellitus, T-wave","lastPublishedDoi":"10.21203/rs.3.rs-3216881/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3216881/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Type 2 Diabetes Mellitus (T2DM) has become a major health concern with an increasing prevalence and is now one of the leading causes of death globally. T2DM and cardiovascular disease are strongly associated and T2DM is an important independent risk factor for ischemic heart disease. T-wave abnormalities (TWA) on electrocardiogram (ECG) can indicate several pathologies including ischemia. In this study, we aimed to investigate the association between T2DM and T-wave changes evaluated using the Minnesota coding system.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A cross-sectional study was conducted on the MASHAD cohort study population. All participants of the cohort population were enrolled in the study. 12-lead ECG and Minnesota coding system (codes 5-1 to 5-4) were utilized for T-wave observation and interpretation. Regression models were used for the final evaluation with a level of significance being considered at p\u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e A total of 9035 participants aged 35-65 years old were included in the study, of whom 1273 were diabetic. The prevalence of code 5-2, 5-3, major and minor TWA were significantly higher in diabetics (p\u0026lt;0.05). Following adjustment for age, gender, and hypertension, no TWAs were significantly associated with T2DM (p\u0026gt;0.05). Whereas, hypertension, age, and body mass index were significantly associated with T2DM.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Although some T-wave abnormalities were more frequent in diabetics, none of them were statistically associated with T2DM in our study. Further research is needed to better understand the associations between T2DM and ischemic heart diseases.\u003c/p\u003e","manuscriptTitle":"Association of T-wave Changes and Type 2 diabetes: A cross-sectional sub-analysis of MASHAD cohort population using Minnesota coding system of Electrocardiogram","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-08-29 16:29:55","doi":"10.21203/rs.3.rs-3216881/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2023-09-19T08:31:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-08-24T17:28:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"5a4a9f65-45a9-4949-817c-ed87aaea9383","date":"2023-08-24T17:09:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"8599c768-4803-4637-9799-51c95906d861","date":"2023-08-24T15:07:08+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-08-24T14:58:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-08-24T14:53:54+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2023-08-24T05:27:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-08-24T05:19:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cardiovascular Disorders","date":"2023-07-30T05:06:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c603199b-68cb-438b-94c8-b9ed42a0027d","owner":[],"postedDate":"August 29th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-01-15T15:10:06+00:00","versionOfRecord":{"articleIdentity":"rs-3216881","link":"https://doi.org/10.1186/s12872-023-03649-2","journal":{"identity":"bmc-cardiovascular-disorders","isVorOnly":false,"title":"BMC Cardiovascular Disorders"},"publishedOn":"2024-01-13 15:02:12","publishedOnDateReadable":"January 13th, 2024"},"versionCreatedAt":"2023-08-29 16:29:55","video":"","vorDoi":"10.1186/s12872-023-03649-2","vorDoiUrl":"https://doi.org/10.1186/s12872-023-03649-2","workflowStages":[]},"version":"v1","identity":"rs-3216881","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3216881","identity":"rs-3216881","version":["v1"]},"buildId":"rHA-KDH7Qsr4HCuvH75dn","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}