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Objective and background: The early detection of diabetic ketoacidosis (DKA) in patients with type 2 diabetes (T2D) plays a crucial role in enhancing outcomes. We developed a nomogram prediction model for screening DKA in T2D patients. At the same time, the input variables were adjusted to reduce misdiagnosis. Methods: We obtained data on T2D patients from Mimic-IV V0.4 and Mimic-III V1.4 databases. A nomogram model was developed using the training data set, internally validated, subjected to sensitivity analysis, and further externally validated with data from T2D patients in Aviation General Hospital. Results: Based on the established model, we analyzed 1885 type 2 diabetes patients, among whom 614 with DKA. We further additionally identified risk factors for DKA based on literature reports and multivariate analysis. We identified age, glucose, chloride, calcium, and urea nitrogen as predictors in our model. The logistic regression model demonstrated an area under the curve (AUC) of 0.86 (95%CI: 0.85–0.90]. To validate the model, we collected data from 91 T2D patients, including 15 with DKA, at our hospital. The external validation of the model yielded an AUC of 0.68 (95%CI: 0.67–0.70). The calibration plot confirmed that our model was adequate for predicting patients with DKA. The decision-curve analysis revealed that our model offered net benefits for clinical use. Conclusions: Our model offers a convenient and accurate tool for predicting whether DKA is present. Excluding input variables that may potentially hinder patient compliance increases the practical application significance of our model. [ABSTRACT FROM AUTHOR]

Background: Type 2 diabetes mellitus (T2DM) is often linked to chronic inflammation, which can be influenced by both lifestyle and dietary choices. However, the relationship between the inflammatory potential of diet and lifestyle factors and the risk of developing T2DM remains unclear. The present study aimed to investigate the associations of the empirical dietary inflammatory index (EDII), dietary inflammatory score (DIS), and lifestyle inflammatory score (LIS) with the risk of T2DM among Iranian adults. Methods: The current study was conducted on 5714 individuals from Yazd Health Study (YaHS) who were followed up for a mean period of six years. YaHS is a prospective cohort study which has been conducted since 2014. Dietary intakes were collected at baseline using the food frequency questionnaire. The relative risk (RR) of T2DM was calculated by Cox regression analysis across tertiles of EDII, DIS, and LIS, adjusted for potential confounders. Results: The mean ± SD for the age and body mass index of the study population were 47.0 ± 9.2 years and 26.7 ± 5.1 Kg.m2, respectively. A significant association between LIS and the risk of T2DM was observed (RR: 4.05, 95% CI: 2.61–6.27 P-trend < 0.001). Individuals in the highest compared to the lowest tertile of EDII-LIS (RR: 3.07, 95%CI: 2.01–4.68; P for trend < 0.001) and DIS-LIS (RR: 2.42, 95%CI: 1.69–3.49; P for trend < 0.001) had a higher risk of T2DM. However, no significant association was found between EDII and DIS scores and the risk of T2DM. Conclusion: Greater adherence to LIS, EDII-LIS, and DIS-LIS scores was associated with a higher risk of T2DM, while no significant association was found between EDII and DIS with T2DM risk. [ABSTRACT FROM AUTHOR]

Objective: Diabetic patients are often comorbid with dyslipidemia, however, the relationship between high-density lipoprotein cholesterol(HDL-C) and diabetic retinopathy (DR) in the adult diabetic population remains to be fully elucidated.The aim of this study is to evaluate the associations between HDL-C and DR in the United States adults with diabetes. Methods: A total of 1708 participants from the National Health and Nutrition Examination Survey (NHANES) 2005–2008 were enrolled in the present study. Fundus images of all study subjects were captured and evaluated using a digital camera and an ophthalmic digital imaging system, and the diagnosis of DR was made by the severity scale of the Early Treatment Diabetic Retinopathy Study (ETDRS).Roche Diagnostics were used to measure serum HDL-C concentration. The relationship of DR with HDL-C was investigated using multivariable logistic regression. The potential non-line correlation was explored with smooth curve fitting approach. Results: The fully-adjusted model showed that HDL-C positively correlated with DR(OR:1.69, 95%CI: 1.25–2.31).However, an inverted U-shaped association between them was observed by applying the smooth curve fitted method. The inflection point of HDL-C(1.99mmol/l) was calculated by utilizing the two-piecewise logistic regression model. In the subgroup analysis, the inverted U-shaped nonlinear correlation between HDL-C and DR was also found in female, Non-Hispanic White, and lower age groups. Conclusion: Our study revealed an inverted U-shaped positive relationship between HDL-C and DR.The findings may provide us with a more comprehensive understanding of the association between HDL-C and DR. [ABSTRACT FROM AUTHOR]