Data mining approaches for type 2 diabetes mellitus prediction using anthropometric measurements

BACKGROUND

The aim of this study was to evaluate the anthropometric measurements most associated with type 2 diabetes mellitus (T2DM) using machine learning approaches.

METHODS

A prospective study was designed for a total population of 9354 (43% men and 57% women) aged 35-65. Anthropometric measurements include weight, height, demispan, Hip Circumference (HC), Mid-arm Circumference (MAC), Waist Circumference (WC), Body Roundness Index (BRI), Body Adiposity Index (BAI), A Body Shape Index (ABSI), Body Mass Index (BMI), Waist-to-height Ratio (WHtR), and Waist-to-hip Ratio (WHR) were completed for all participants. The association was assessed using logistic regression (LR) and decision tree (DT) analysis. Receiver operating characteristic (ROC) curve was performed to evaluate the DT's accuracy, sensitivity, and specificity using R software.

RESULTS

Traditionally, 1461 women and 875 men with T2DM (T2DM group). According to the LR, in males, WC and BIA (p-value < 0.001) and in females, demispan and WC (p-value < 0.001) had the highest correlation with T2DM development risk. The DT indicated that WC has the most crucial effect on T2DM development risk, followed by HC, and BAI.

CONCLUSIONS

Our results showed that in both men and women, WC was the most important anthropometric factor to predict T2DM.

The positive short-term effect of dexamethasone on ataxia symptoms in a patient with ataxia-telangiectasia: A case report

Oral dexamethasone was administered at a dose of 0.075 mg/kg/day for a boy with ataxia-telangiectasia. The SARA score was improved by 7.0 points after dexamethasone treatment over a period of 28 days. The body weight was increased by 1.4 kg after 4 weeks leading to dose titration to 0.05 mg/kg/day.

Prevalence of combined and noncombined dyslipidemia in an Iranian population

BACKGROUND

Combination of dyslipidemic phenotypes, including elevated plasma levels of low-density lipoprotein cholesterol (LDL-C), elevated plasma triglycerides (TG), and decreased low-density lipoprotein cholesterol (HDL-C) concentrations, is important because of the association of individual phenotypes with increased risk of cardiovascular disease (CVD). We investigated the prevalence of combined dyslipidemias and their effects on CVD risk in an Iranian large population.

METHOD

A total of 9847 individuals were recruited as part of the Mashhad Stroke and Heart Atherosclerotic Disorders (MASHAD) cohort study. Anthropometric parameters and biochemical indices were measured in all of the subjects. Different types of combined dyslipidemias including high TG + low HDL-C, high TG + low HDL-C + high LDL-C, low HDL-C + high LDL-C, high TG + high LDL-C, and finally high TG + high LDL-C + low HDL-C were considered. Ten-year CVD risk was calculated using the QRISK2 risk algorithm and adjustments were made as suggested by the Joint British Societies' (JBS2). Logistic regression analyses were performed to determine the association between different combined dyslipidemias and categorical QRISK.

RESULTS

A total of 3952 males and 5895 females were included in this current study. Among the included subjects, 83.4% had one form of dyslipidemia, and 16.6% subjects were not dyslipidemic. The mean age was 48.88 ± 7.9 and 47.02 ± 8.54 years for dyslipidemic and nondyslipidemic groups, respectively. The results showed that the frequency of dyslipidemia was 98%, 87.1%, and 90% in subjects with metabolic syndrome, CVD, and diabetes, respectively. Our results suggested that around 15.7% of study population were at 10 years CVD risk (high ≥20) and it was higher in men than women (P < .001). Moreover, risk of CVD was higher in TG↑ & HDL↓ & LDL↑ group than other groups.

CONCLUSION

Prevalence of dyslipidemia was 83.4% among Iranian adults. The results showed that individuals with increased plasma TG and LDL-C, and low HDL-C levels had the highest 10 years CVD risk compared to other combined dyslipidemic phenotypes.