Evaluation of ECG Abnormalities in Patients with Asymptomatic Type 2 Diabetes Mellitus

Association of major and minor ECG abnormalities with traditional cardiovascular risk factors in the general population: a large scale study

Cardiovascular disease (CVD) can be determined and quantified using the electrocardiogram (ECG) analysis. Identification of the risk factors associated with ECG abnormalities may advise prevention approaches to decrease CVD burden. In this study we aimed to investigate the association between CVD risk factors and minor and major ECG abnormalities in a general Iranian adult population. This study was conducted in 2010 and covered a population of 9035 males and females aged 35 to 65 years recruiting from the phase I of Mashhad Stroke and Heart Atherosclerotic Disorder (MASHAD) cohort study. The participants were drawn by a stratified cluster random sampling technique. The Bivariate and multinomial logistic regression analysis were conducted considering gender stratification to explore the association of ECG abnormalities with traditional cardiovascular risk factors. There was a significant association between minor and major ECG abnormalities and hypertension (HTN), type 2 diabetes (T2DM), smoking, and physical activity (p < 0.005). There was a significant trend, in both genders, for increasing major abnormalities as the number of CVD risk factors increased. But, only in women, the minor abnormalities increase in frequency as the number of CVD risk factors increased. The results of multinomial logistic regression showed that men with HTN [ARRR = 1.25, 95% CI 0.99, 1.57] and T2DM [ARRR = 1.31, 95% CI 0.99, 1.74] had the highest likelihood to have major abnormalities, although these are not statistically significant. For women, those with HTN had the highest likelihood to have major [ARRR = 1.36, 95% CI 1.13, 1.63] and minor [ARRR = 1.35, 95% CI 1.15, 1.58] abnormalities. Also, women aged > 60 years were more likely to have major [ARRR = 2.01, 95% CI 1.49, 2.74] and minor [ARRR = 1.59, 95% CI 1.20, 2.10] abnormalities compared to women aged < 45 years. Age and HTN were significantly associated with major and minor ECG abnormalities in women, and, on the other hand, HTN and T2DM were associated with major abnormalities in men. Taken together, these findings suggest that healthcare providers should advise preventive approaches to the asymptomatic adults with both major and minor electrocardiographic abnormalities that may predict cardiovascular risk.

Dapagliflozin Pretreatment Prevents Cardiac Electrophysiological Changes in a Diet and Streptozotocin Induction of Type 2 Diabetes in Rats: A Potential New First-Line?

Purpose

Dapagliflozin exerts cardioprotective effects in Type 2 Diabetes Mellitus (T2DM). However, whether these effects prevent electrocardiographic changes associated with T2DM altogether remain unknown. Our aim was to investigate the prophylactic effect of dapagliflozin pretreatment on the rat ECG using a high-fat, high-fructose (HFHf) diet and a low dose streptozotocin (STZ) model of T2DM.

Methods

Twenty-five (25) rats were randomized into five (5) groups: normal control receiving a normal diet while the other groups received an 8-week HFHf and 40mg/kg STZ on day 42, and either: saline for the diabetic control (1 mg/kg/d), low dose (1.0 mg/kg/d) and high dose dapagliflozin (1.6 mg/kg/d), or metformin (250 mg/kg/d). Oral glucose tolerance (OGT), electrocardiograms (ECGs), paracardial adipose mass, and left ventricular fibrosis were determined. Data were analyzed using GraphPad version 9.0.0.121, with the level of significance at p < 0.05.

Results

Compared to the diabetic control group, a high dose of dapagliflozin preserved the OGT (p = 0.0001), QRS-duration (p = 0.0263), QT-interval (p = 0.0399), and QTc intervals (p = 0.0463). Furthermore, the high dose dapagliflozin group had the lowest paracardial adipose mass (p = 0.0104) and fibrotic area (p = 0.0001). In contrast, while metformin showed favorable effects on OGT (p = 0.0025), paracardial adiposity (p = 0.0153) and ventricular fibrosis (p = 0.0291), it did not demonstrate significant antiarrhythmic effects.

Conclusion

Pretreatment with higher doses of Dapagliflozin exhibits prophylactic cardioprotective characteristics against diabetic cardiomyopathy that include antifibrotic and antiarrhythmic qualities. This suggests that higher doses of dapagliflozin could be a more effective initial therapeutic option in T2DM.

Assessing Elevated Blood Glucose Levels Through Blood Glucose Evaluation and Monitoring Using Machine Learning and Wearable Photoplethysmography Sensors: Algorithm Development and Validation

BACKGROUND

Diabetes mellitus is the most challenging and fastest-growing global public health concern. Approximately 10.5% of the global adult population is affected by diabetes, and almost half of them are undiagnosed. The growing at-risk population exacerbates the shortage of health resources, with an estimated 10.6% and 6.2% of adults worldwide having impaired glucose tolerance and impaired fasting glycemia, respectively. All current diabetes screening methods are invasive and opportunistic and must be conducted in a hospital or laboratory by trained professionals. At-risk participants might remain undetected for years and miss the precious time window for early intervention to prevent or delay the onset of diabetes and its complications.

OBJECTIVE

We aimed to develop an artificial intelligence solution to recognize elevated blood glucose levels (≥7.8 mmol/L) noninvasively and evaluate diabetic risk based on repeated measurements.

METHODS

This study was conducted at KK Women's and Children's Hospital in Singapore, and 500 participants were recruited (mean age 38.73, SD 10.61 years; mean BMI 24.4, SD 5.1 kg/m2). The blood glucose levels for most participants were measured before and after consuming 75 g of sugary drinks using both a conventional glucometer (Accu-Chek Performa) and a wrist-worn wearable. The results obtained from the glucometer were used as ground-truth measurements. We performed extensive feature engineering on photoplethysmography (PPG) sensor data and identified features that were sensitive to glucose changes. These selected features were further analyzed using an explainable artificial intelligence approach to understand their contribution to our predictions.

RESULTS

Multiple machine learning models were trained and assessed with 10-fold cross-validation, using participant demographic data and critical features extracted from PPG measurements as predictors. A support vector machine with a radial basis function kernel had the best detection performance, with an average accuracy of 84.7%, a sensitivity of 81.05%, a specificity of 88.3%, a precision of 87.51%, a geometric mean of 84.54%, and F score of 84.03%.

CONCLUSIONS

Our findings suggest that PPG measurements can be used to identify participants with elevated blood glucose measurements and assist in the screening of participants for diabetes risk.

Patterns and associated factors of electrocardiographic abnormality among type 2 diabetic patients in Amhara National Regional State Referral Hospitals, Ethiopia: a multicenter institution-based cross-sectional study

BACKGROUND

Cardiovascular diseases are the most causes of mortality and morbidity among diabetes mellitus (DM) patients. Electrocardiographic (ECG) changes are common in the early course of the disease. Little is known about the electrocardiographic abnormalities among type 2 DM patients in Ethiopia. This study determined the overall prevalence, its patterns, and the associated factors of ECG abnormalities among people living with T2DM in Amhara National Regional State referral hospitals, Ethiopia.

METHODS

A multicenter institution-based cross-sectional study was conducted from 01 April to 30 May 2021. A simple random sampling and systematic sampling techniques were employed to select the referral hospitals and study participants, respectively. A digital electrocardiograph was used to measure the ECG parameters and the other data were collected using an interviewer-administered questionnaire. Epi-data version-4.6 and Stata-14 were used for data entry and statistical analysis, respectively. The descriptive statistics were presented with tables and graphs. A binary logistic regression model was fitted to identify associated factors of ECG abnormality. In the final model, statistical significance was decided at p≤0.05, and the strength of association was indicated using an adjusted odds ratio with 95% CI.

RESULTS

Two-hundred and fifty-eight participants (response rate = 99.6%) were included for the analysis. The prevalence of overall ECG abnormality was 45% (95% CI: 39, 51%). On the basis of the electrocardiographic patterns, 57 (21.1%; 95% CI: 14.6, 32.6%) were presented with T-wave abnormality, 36 (14%; 95% CI: 10.1, 18.8%) left axis deviation, and 24 (9.3% [6.3, 13.5%]) sinus tachycardia. Higher monthly income (> 90$) (AOR = 0.51 [0.31, 0.83]), over 10 years duration of DM (AOR = 4.5[1.05, 18.94]), hypertension (AOR = 3.9 [1.6, 9.40]), fasting blood sugar of ≥ 130 mg/dl (AOR = 5.01[2.13, 12.20]), and overweight (AOR = 2.65[1.17, 5.98]) were statistically significant factors of overall ECG abnormality.

CONCLUSIONS

Nearly, half of the participants had at least one ECG abnormality. Higher-income, prolonged disease duration, hypertension, higher fasting blood sugar, and overweight were significantly associated with ECG abnormality. The findings of this study suggest the need to institute routine ECG screening for all T2DM patients to reduce ECG abnormalities and further complications.

Assessment of electrocardiogram abnormality and associated factors among apparently healthy adult type 2 diabetic patients on follow-up at Jimma Medical Center, Southwest Ethiopia: Cross-sectional study

Background

Diabetes mellitus is a group of metabolic disorders causing long-term damage to the cardiovascular system which remains asymptomatic among diabetic patients. An electrocardiograph is a simple and first-line tool in the screening of cardiovascular diseases.

Objective

To assess electrocardiogram abnormality and associated factors among apparently healthy adult type 2 diabetes patients on follow-up at Jimma Medical Center, 2019.

Materials and methods

Institutional based cross-sectional study was conducted from April 1 to May 30, 2019, at Jimma Medical Center among selected type 2 diabetes patients. Systematic random sampling was employed to select the study participants. The World Health Organization stepwise approach and interviewer-administered semi-structured questionnaires were employed to collect basic data. Resting Electrocardiography was done using a standard 12-lead electrocardiograph machine. The collected data were checked for completeness, coded, entered into the Epi-data Version 4.0.2. and exported to SPSS Version 21. Descriptive statistics like frequencies, percentages, mean and standard deviations were carried out. Binary and multiple logistic regression was done and a p value of less than 0.05 was used as a level of significance.

Results

A total of 344 type 2 diabetes patients were interviewed and underwent electrocardiography making a 100% response rate. Electrocardiographic abnormality was identified among 209 (61%) of the respondents. Not attending formal education [AOR = 3.07, 95%, CI = 1.37–6.87], solid oil use, [AOR = 1.79, 95%, CI = 1.07–2.98], body mass index ≥ 25 kg/m² [AOR = 2.74, 95%, CI = 1.67–4.50] and long duration of diabetes ≥ 10 years [AOR = 3.36, 95%, CI = 1.46–7.71] were associated with electrocardiogram abnormality.

Conclusions

and recommendation

In this study, the majority (3/5th) of the participant had electrocardiogram abnormality. Not attending formal education, longer duration of diabetes ≥ 10 years, solid oil use, and increased body mass index ≥ 25 kg/m² were independent predictors of electrocardiographic abnormality. Integrating electrocardiogram screening in routine diabetic management can pick cardiac complications of diabetes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-021-02110-6.

Relationship Between Sarcopenia and Electrocardiographic Abnormalities in Older People: The Bushehr Elderly Health Program

Background: Sarcopenia is characterized by low skeletal muscle mass and function, which is associated with cardiovascular risk factors and may even be related to adverse cardiovascular events and mortality. This study aimed to evaluate whether sarcopenia is related to electrocardiographic (ECG) abnormalities in a large sample of older adults.

Methods: We performed a cross-sectional study based on the data collected during the Bushehr Elderly Health (BEH) cohort study. Body composition was measured by dual X-ray absorptiometry (DXA) and muscle strength was measured using a digital dynamometer for each hand of every participant. A person who had low muscle strength, as well as low muscle mass was identified as having sarcopenia. The subjects were classified into three groups according to the Minnesota Code (MC) as major, minor ECG abnormalities and participants with no abnormalities ECG.

Results: Of the 2,426 participants, 354 (14.6%) had major ECG abnormalities and 193 (8%) had minor ECG abnormalities. Sarcopenia was associated with an increased risk of major ECG abnormality in all models. After adjustment for confounders of CHD in full model, the OR for major ECG abnormality was 1.47 (95% CI 1.11–1.95) in those with sarcopenia. Low muscle strength and low muscle performance were both with an increased risk of major ECG abnormality in all models. Sarcopenia and low muscle strength increased 28% and 62% risk of any ECG abnormality in the full models [sarcopenia: 1.28(1.01–1.63), low muscle strength: 1.62(1.30–2.03)], respectively.

Conclusions: This study showed that sarcopenia and its components are associated with ECG abnormalities in Iranian older people. Although some older adults have higher cardiovascular risk factors, these data showed that further factors such as sarcopenia may be identified as a particular risk factor for future cardiovascular events. Therefore, sarcopenia could be added to the screening of the older population to reduce the risk of cardiovascular events.