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.

Mucormycosis in pre-COVID-19 and COVID-19 era: A study of prevalence, risk factors and clinical features.

Objective: Mucormycosis is a rare yet devastating fungal disease with a frequently fatal outcome. The purpose of this study was to compare the prevalence of mucormycosis, evaluate its risk factors, and assess the patients' outcomes in pre-COVID-19 and COVID-19 era. Methods: In this retrospective observational study, clinical data of 158 patients with confirmed histopathological diagnosis of mucormycosis were collected from the medical records departments of Imam Reza and Ghaem hospitals, Mashhad, Iran during 2018-2021. The collected data were risk factors associated with mucormycosis including age, gender, underlying diseases, details of corticosteroid administration, and complications such as blindness and mortality. Results: Of 158 studied patients, 48 patients were diagnosed in the pre-pandemic period whereas 110 cases were admitted during the pandemic era. COVID-19 associated mucormycosis (CAM) was observed in 58.1% of the pandemic cases. In the pre-pandemic period, cancer (89.5% vs. 39%, p < .001) was significantly more prevalent while during the pandemic era, the prevalence of diabetes mellitus (16.7% vs. 51%, p < .001) was remarkably higher. Moreover, the mortality rate of mucormycosis was considerably reduced after the pandemic (64.6%-45.4%), especially in CAM patients (35.9%). Conclusion: The COVID-19 pandemic has led to an increased prevalence of mucormycosis, due to the convergence of interlinked risk factors such as diabetes mellitus, corticosteroid therapy, and COVID-19. Therefore, clinicians must be aware of the probable occurrence of mucormycosis in the first or second week of COVID-19 infection in vulnerable patients and use the steroids cautiously. Level of evidence: 4 Laryngoscope Investigative Otolaryngology, 2022.