Gender Differences in Risks of Coronary Heart Disease and Stroke in Patients with Type 2 Diabetes Mellitus and Their Association with Metabolic Syndrome in China

Comparison between multiple logistic regression and machine learning methods in prediction of abnormal thallium scans in type 2 diabetes

BACKGROUND

The prevalence of type 2 diabetes (T2D) has been increasing dramatically in recent decades, and 47.5% of T2D patients will die of cardiovascular disease. Thallium-201 myocardial perfusion scan (MPS) is a precise and non-invasive method to detect coronary artery disease (CAD). Most previous studies used traditional logistic regression (LGR) to evaluate the risks for abnormal CAD. Rapidly developing machine learning (Mach-L) techniques could potentially outperform LGR in capturing non-linear relationships.

AIM

To aims were: (1) Compare the accuracy of Mach-L methods and LGR; and (2) Found the most important factors for abnormal TMPS.

METHODS

556 T2D were enrolled in the study (287 men and 269 women). Demographic and biochemistry data were used as independent variables and the sum of stressed score derived from MPS scan was the dependent variable. Subjects with a MPS score ≥ 9 were defined as abnormal. In addition to traditional LGR, classification and regression tree (CART), random forest, Naïve Bayes, and eXtreme gradient boosting were also applied. Sensitivity, specificity, accuracy and area under the receiver operation curve were used to evaluate the respective accuracy of LGR and Mach-L methods.

RESULTS

Except for CART, the other Mach-L methods outperformed LGR, with gender, body mass index, age, low-density lipoprotein cholesterol, glycated hemoglobin and smoking emerging as the most important factors to predict abnormal MPS.

CONCLUSION

Four Mach-L methods are found to outperform LGR in predicting abnormal TMPS in Chinese T2D, with the most important risk factors being gender, body mass index, age, low-density lipoprotein cholesterol, glycated hemoglobin and smoking.

Development and validation of a nomogram to estimate future risk of type 2 diabetes mellitus in adults with metabolic syndrome: prospective cohort study

OBJECTIVES

To develop and validate the 4-year risk of type 2 diabetes mellitus among adults with metabolic syndrome.

DESIGN

Retrospective cohort study of a large multicenter cohort with broad validation.

SETTINGS

The derivation cohort was from 32 sites in China and the geographic validation cohort was from Henan population-based cohort study.

RESULTS

568 (17.63) and 53 (18.67%) participants diagnosed diabetes during 4-year follow-up in the developing and validation cohort, separately. Age, gender, body mass index, diastolic blood pressure, fasting plasma glucose and alanine aminotransferase were included in the final model. The area under curve for the training and external validation cohort was 0.824 (95% CI, 0.759-0.889) and 0.732 (95% CI, 0.594-0.871), respectively. Both the internal and external validation have good calibration plot. A nomogram was constructed to predict the probability of diabetes during 4-year follow-up, and on online calculator is also available for a more convenient usage ( https://lucky0708.shinyapps.io/dynnomapp/ ).

CONCLUSION

We developed a simple diagnostic model to predict 4-year risk of type 2 diabetes mellitus among adults with metabolic syndrome, which is also available as web-based tools ( https://lucky0708.shinyapps.io/dynnomapp/ ).

Evaluation of Eight Anthropometric Indices for Identification of Metabolic Syndrome in Adults with Diabetes

PURPOSE

Several previous reports have highlighted the association between adiposity and risk of metabolic syndrome (MetS). Although it is necessary to identify which adiposity indices are best suited to identify MetS, no such study has been completed in diabetic patients. The aim of this study was to evaluate the ability of eight anthropometric indices to identify MetS in diabetic, middle-aged and elderly Chinese patients.

PATIENTS AND METHODS

A cross-sectional study was conducted in 906 type 2 diabetic patients in Guangxi.

RESULTS

The highest odds ratios for the identification of MetS were identified with CUN-BAE (OR = 28.306). The largest areas under the curve (AUCs) were observed for WHtR and BRI in men aged 40-59; CUN-BAE in men aged 60 and over; WHtR, BRI, and TyG in women aged 40-59; and BMI for women aged 60 and over. The weakest indicator for the screening of MetS in type 2 diabetes was the ABSI.

CONCLUSION

The most effective anthropometric indicator for the identification of MetS varied across sex and age subgroups.

Predictors of abnormality in thallium myocardial perfusion scans for type 2 diabetes

Type 2 diabetes mellitus (T2DM) increases coronary artery disease (CAD) risk. In this study, we used T2DM clinical variables to predict abnormality in thallium-201 myocardial perfusion scans (Th-201 scans). These clinical variables were summed stress score (SSS), summed rest score, and summed difference score (SDS), with data obtained from 368 male and 428 female participants with T2DM. Multiple linear regression results were as follows. In male participants, body mass index (BMI) and creatinine (Cr) were associated with SSS (β = 0.224, p < 0.001; β = 0.140, p = 0.022, respectively), and only BMI was associated with SDS (β = 0.174, p = 0.004). In female participants, BMI and high-density lipoprotein cholesterol level were associated with SSS (β = 0.240, p < 0.001; β =  - 0.120, p = 0.048, respectively), and only BMI was correlated with SDS (β = 0.123, p = 0.031). Our multivariate logistic regression indicated that in male and female participants, BMI was the only independent indicator of high SSS (SSS ≥ 9). In this study, we demonstrated that male patients have a higher SSS and SDS than female patients do in Th-201 scans for T2DM in a Chinese population. For male and female patients, BMI was the strongest predictor of abnormality in Th-201 scans. Our results can help clinicians identify patients with T2DM at high risk of CAD.

Smoking Is a Risk Factor of Coronary Heart Disease through HDL-C in Chinese T2DM Patients: A Mediation Analysis

Objective

To investigate associations between smoking and cardiovascular and cerebrovascular complications in type 2 diabetes mellitus (T2DM) patients.

Methods

This is a cross-sectional study. Of 971 T2DM patients aged 14–93 years old in this study, 182 had ever smoked and 789 never smoked. Propensity score matching (PSM) reduced the confounding bias between groups. Logistic regression analysis was performed on matched data to evaluate coronary heart disease (CHD) and stroke risk. In addition, the mediation analysis was conducted among smoking exposure, HDL-C, and CHD.

Results

A total of 139 pairs of patients who had never and ever smoked were matched. Logistic regression analysis showed that compared with patients who never smoked, those who smoked > 20 cigarettes per day (CPD) had a higher risk of CHD (odds ratio [OR]: 3.09, 95% confidence interval [CI]: 1.21–7.89). Additionally, after adjusting for age, sex, origin, occupation, smoking status, body mass index, waist circumference, and diabetes duration, the OR for CHD with >20 years of cumulative smoking (pack-years) was 2.21 (95% CI: 1.05–4.65). Furthermore, we observed a significant dose-response relationship between CPD and lower high-density lipoprotein cholesterol (HDL-C) (P < 0.001). Moreover, the mediation analysis showed that the indirect effect mediated by HDL-C accounted for 86% (effect = 0.0187, 95% CI: 0.0100–0.0316).

Conclusions

Smoking may be a risk factor for CHD in T2DM patients. T2DM patients should stop smoking or reduce the CPD to prevent the onset of CHD. Moreover, to prevent CHD complications, monitoring HDL-C levels in T2DM patients who smoke may be necessary.

Clinical Characteristics and Prognosis of Young Patients with Coronary Heart Disease

Background

The objective of this study was to investigate the clinical characteristics and prognosis of coronary heart disease (CHD) in young patients.

Material/Methods

We included 972 CHD patients (≤50 years old) with coronary artery stenting who were prospectively enrolled and followed for 1 year. Clinical characteristics, risk factors, and predictors of outcomes were evaluated.

Results

The prevalence of current smoker, hypertension, diabetes mellitus, dyslipidemia and positive family history of CHD were 18.9%, 34.3%, 14.5%, 4.4%, and 44.2%, respectively. Most of the patients underwent coronary stenting due to stable angina (48.8%) and unstable angina (UA; 48.1%). After 1-year follow-up, 64 patients (6.6%) experienced clinical outcomes and the most common event was UA (n=56). Compared to patients without clinical outcomes, those with outcomes were more likely to be male, have higher systolic blood pressure, more likely to have hypertension and diabetes mellitus, and more likely to be presented as unstable angina. Multivariate regression analysis showed only age (hazard ratio [HR]: 1.12 and 95% confidence interval [CI]: 1.07–1.26), smoking (HR: 1.15 and 95% CI: 1.06–1.23), presence of hypertension (HR: 1.19 and 95% CI: 1.13–1.31), and diabetes mellitus (HR: 1.16 and 95% CI: 1.09–1.28), more vessels with stenosis (HR: 1.27 and 95% CI: 1.20–1.48) and presented with acute coronary syndrome (HR: 1.35 and 95% CI: 1.21–1.55) were independently associated with clinical outcomes.

Conclusions

Most of the young (≤50 years of age) CHD patients had poor management of risk factors and better controlling these risk factors would be helpful for the primary and secondary prevention of premature CHD in Guangdong province.

Is type 2 diabetes mellitus a coronary heart disease equivalent or not? Do not just enjoy the debate and forget the patient!

In the last several years there has been a large debate whether patients with type 2 diabetes (T2DM) should be treated as those with high or very high cardiovascular risk, and whether T2DM should be considered as equivalent to coronary heart disease (CHD). It all started in the 2001 in National Cholesterol Education Program - Adult Treatment Panel III recommendations, and the knowledge has changed on this issue at least several times. But the main problem is that due to these inconsistencies and different approaches to the cardiovascular risk of T2DM patients, we have more and more patients with T2DM not effectively treated, and diabetologists mostly focus on glucose (glucocentric approach), often forgetting about the overall cardiovascular risk of those patients. In this review we discuss the above-mentioned topic, try to give some practical suggestions, and raise the issue of whether we should start a discussion on treating all patients with T2DM as those at very high cardiovascular risk, or to at least to try to unify the definition and find such variables/risk factors which are easy to measure to help physicians to treat those patients optimally. We have obviously discussed these issues in the context of new European Society of Cardiology (ESC)/European Association for the Study of Diabetes (EASD) Guidelines 2019.

Predicting the risk of stroke among patients with type 2 diabetes: a systematic review and meta-analysis of C-statistics

OBJECTIVE

Stroke is a major cause of disability and death worldwide. People with diabetes are at a twofold to fivefold increased risk for stroke compared with people without diabetes. This study systematically reviews the literature on available stroke prediction models specifically developed or validated in patients with diabetes and assesses their predictive performance through meta-analysis.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

A detailed search was performed in MEDLINE, PubMed and EMBASE (from inception to 22 April 2019) to identify studies describing stroke prediction models.

ELIGIBILITY CRITERIA

All studies that developed stroke prediction models in populations with diabetes were included.

DATA EXTRACTION AND SYNTHESIS

Two reviewers independently identified eligible articles and extracted data. Random effects meta-analysis was used to obtain a pooled C-statistic.

RESULTS

Our search retrieved 26 202 relevant papers and finally yielded 38 stroke prediction models, of which 34 were specifically developed for patients with diabetes and 4 were developed in general populations but validated in patients with diabetes. Among the models developed in those with diabetes, 9 reported their outcome as stroke, 23 reported their outcome as composite cardiovascular disease (CVD) where stroke was a component of the outcome and 2 did not report stroke initially as their outcome but later were validated for stroke as the outcome in other studies. C-statistics varied from 0.60 to 0.92 with a median C-statistic of 0.71 (for stroke as the outcome) and 0.70 (for stroke as part of a composite CVD outcome). Seventeen models were externally validated in diabetes populations with a pooled C-statistic of 0.68.

CONCLUSIONS

Overall, the performance of these diabetes-specific stroke prediction models was not satisfactory. Research is needed to identify and incorporate new risk factors into the model to improve models' predictive ability and further external validation of the existing models in diverse population to improve generalisability.

Relationship between body-roundness index and metabolic syndrome in type 2 diabetes

Background: The present study evaluated the relationship between body-roundness index (BRI) and metabolic syndrome (MetS) in type 2 diabetes. Methods: A cross-sectional study was conducted on 585 type 2 diabetes in Qinhuangdao. MetS was defined as per the Chinese Diabetes Society. Results: The BRI was strongly associated with the odds of having MetS in both males and females after adjustment for age, history of diabetes, and body-mass index (P<0.05). AUC of the BRI were 0.824 for males and 0.775 for females (P<0.001). The optimal cutoff points for the BRI were 3.85 in males (sensitivity 76.5%, specificity 82.1%) and 4.05 in females (sensitivity 76.4%, specificity 70.3%). Conclusion: The BRI was correlated with MetS and was an effective indicator for the screening of MetS in type 2 diabetes.

Ischemic stroke across sexes: What is the status quo?

Stroke prevalence is expected to increase in the next decades due to the aging of the Western population. Ischemic stroke (IS) shows an age- and sex-dependent distribution in which men represent the most affected population within 65 years of age, being passed by post-menopausal women in older age groups. Furthermore, a sexual dimorphism concerning risk factors, presentation and treatment of IS has been widely recognized. In order to address these phenomena, a number of issue have been raised involving both socio-economical and biological factors. The latter can be either dependent on sex hormones or due to intrinsic factors. Although women have poorer outcomes and are more likely to die after a cerebrovascular event, they are still underrepresented in clinical trials and this is mirrored by the lack of sex-tailored therapies. A greater effort is needed in the future to ensure improved treatment and quality of life to both sexes.

Ischemic stroke across sexes: what is the status quo?

Stroke prevalence is expected to increase in the next decades due to the aging of the Western population. Ischemic stroke (IS) shows an age- and sex-dependent distribution in which men represent the most affected population within 65 years of age, being passed by post-menopausal women in older age groups. Furthermore, a sexual dimorphism concerning risk factors, presentation and treatment of IS has been widely recognized. In order to address these phenomena, a number of issue have been raised involving both socio-economical and biological factors. The latter can be either dependent on sex hormones or due to intrinsic factors. Although women have poorer outcomes and are more likely to die after a cerebrovascular event, they are still underrepresented in clinical trials and this is mirrored by the lack of sex-tailored therapies. A greater effort is needed in the future to ensure improved treatment and quality of life to both sexes.

Investigation of Gender Differences and Exclusive Criteria in a Diabetic Acute Ischemic Stroke Population Treated with Recombinant Tissue-Type Plasminogen Activator (rtPA)

BACKGROUND

Many studies have reported that women who survive stroke have less favorable outcomes than men in the use of rtPA, while others reported worse outcomes in men than women. The gender difference in the exclusion criteria in a diabetic stroke population is not fully understood. This issue was investigated in this study.

METHOD

In a diabetic stroke population from a stroke registry of data collected between January 2010 to June 30, 2016, the gender difference was determined using demographics and clinical factors. Comparison was determined using univariate analysis while multivariable model was used to adjust for the effect of confounding variables.

RESULTS

In a diabetic stroke population of 439 patients, more females were excluded than males (P < 0.0001, OR = 2.323). The male exclusion was associated with atrial fibrillation (P = 0.011, OR = 3.697), carotid artery stenosis (P = 0.023, OR = 5.001), and cholesterol reducer (P = 0.037, OR = 0.409). In the female diabetic stroke population, exclusion from rtPA therapy was associated with language disturbances (P = 0.039, OR = 0.372), history of previous stroke (P = 0.005, OR = 3.276), antihypertensive medication use (P = 0.013, OR = 0.163), and antidiabetic medication use (P = 0.031, OR = 0.324).

CONCLUSION

In a stroke population, women have a worse outcome than men in an untreated acute ischemic stroke population, but when treated there is no significant difference, suggesting a better treatment outcome for women compared to men. In a diabetic stroke population, the clinical variables for the exclusion criteria for women and men are significantly different, even after adjustment for confounding variables.

Three novel obese indicators perform better in monitoring management of metabolic syndrome in type 2 diabetes

The present study evaluated the performance of three novel obese indicators, visceral adiposity index (VAI), lipid accumulation product (LAP) and waist circumference-triglyceride index (WTI), for identifying metabolic syndrome(MetS) in type 2 diabetes. A cross-sectional study was conducted on 711 type 2 diabetes in Qinhuangdao. The MetS was defined as the definition of Chinese Diabetes Society. Receiver operating characteristic curve analyses were performed to assess the accuracy of three obese indicators as diagnostic tests for MetS. The prevalence of MetS was 71.3%. In men, among all three obese indicators, the LAP had the highest area under curve (AUC) value (AUC = 0.894), followed by VAI (AUC = 0.860) and WTI (AUC = 0.855). In women, among all three obese indicators, the LAP had the highest AUC value (AUC = 0.906), followed by WTI (AUC = 0.887) and VAI (AUC = 0.881). However. there was no significant difference between the three obese indicators(P > 0.05). Three obese indicators were effective indicators for the screening of MetS, LAP and WTI are more simple.