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Objective: To develop and validate an interactive nomogram to predict healthcare-associated infections (HCAIs) in the intensive care unit (ICU). Methods: A multicenter retrospective study was conducted to review 2017 data from six hospitals in Guizhou Province, China. A total of 1,782 ICU inpatients were divided into either a training set (n = 1,189) or a validation set (n = 593). The patients’ demographic characteristics, basic clinical features from the previous admission, and their need for bacterial culture during the current admission were extracted from electronic medical records of the hospitals to predict HCAI. Univariate and multivariable analyses were used to identify independent risk factors of HCAI in the training set. The multivariable model’s performance was evaluated in both the training set and the validation set, and an interactive nomogram was constructed according to multivariable regression model. Moreover, the interactive nomogram was used to predict the possibility of a patient developing an HCAI based on their prior admission data. Finally, the clinical usefulness of the interactive nomogram was estimated by decision analysis using the entire dataset. Results: The nomogram model included factor development (local economic development levels), length of stay (LOS; days of hospital stay), fever (days of persistent fever), diabetes (history of diabetes), cancer (history of cancer) and culture (the need for bacterial culture). The model showed good calibration and discrimination in the training set [area under the curve (AUC), 0.871; 95% confidence interval (CI), 0.848–0.894] and in the validation set (AUC, 0.862; 95% CI, 0.829–0.895). The decision curve demonstrated the clinical usefulness of our interactive nomogram. Conclusions: The developed interactive nomogram is a simple and practical instrument for quantifying the individual risk of HCAI and promptly identifying high-risk patients. [ABSTRACT FROM AUTHOR]

Objectives: The C1q complement/TNF-related protein (CTRP) superfamily, which includes the adipokine adiponectin, has been shown in animal models to have positive metabolic and cardiovascular effects. We sought to investigate circulating CTRP1, CTRP9, CTRP12 and CTRP13 concentrations in persons with type 2 diabetes mellitus (T2DM), with age and BMI matched controls, and to examine the effects of a 2 hour 75g oral glucose tolerance test (OGTT) on serum CTRP1, CTRP9, CTRP12 and CTRP13 levels in persons with T2DM. Design: Cross-sectional study [newly diagnosed T2DM (n = 124) and control (n = 139) participants]. Serum CTRP1, CTRP9, CTRP12 and CTRP13 were measured by ELISA. Results: Systolic and diastolic blood pressure, total cholesterol (TCH), Low-density lipoprotein (LDL)-cholesterol, triglycerides, TCH/High-density lipoprotein (HDL) ratio, triglycerides/HDL ratio, glucose, insulin, homeostatic model assessment–insulin resistance (HOMA-IR), C-reactive protein and endothelial lipase were significantly higher, whereas leptin and adiponectin were significantly lower in T2DM participants. Serum CTRP1 were significantly higher and CTRP12 significantly lower in T2DM participants. Age, diastolic blood pressure, glucose and CTRP12 were predictive of serum CTRP1; leptin was predictive of serum CTRP9; glucose and CTRP1 were predictive of serum CTRP12; endothelial lipase was predictive of serum CTRP13. Finally, serum CTRP1 were significantly higher and CTRP12 significantly lower in T2DM participants after a 2 hour 75g OGTT. Conclusions: Our data supports CTRP1 and CTRP12 as potential novel biomarkers for the prediction and early diagnosis of T2DM. Furthermore, pharmacological agents that target CTRP1 and CTRP12 could represent a new strategy in the treatment of T2DM. [ABSTRACT FROM AUTHOR]

Background: Increasing evidence suggests that miR-126 participates in the glucose homeostasis through its target molecules. Although bioinformatics analysis predicts that miR-126 can bind with the insulin receptor substrate-2(IRS-2) mRNA at the “seed sequence”, but there are still no definitely reports to support it. In this study, we provided evidences that IRS-2 was one of the target genes of miR-126. And miR-126 has a proliferation inhibiting effects in INS-1 β cells, mainly through the suppression of IRS-2. Methods: The 3’-UTR of IRS-2 regulated by miR-126 was analyzed by the luciferase assay and western blot. Furthermore, proliferation of INS-1 β cells stimulated by glucose was tested, and the association between IRS-2 and miR-126 were analyzed. Results: We found that mutation of only three of the 6 “seed sequences” can eliminate the inhibition effect of miR-126. In INS-1 β cells, administration of miR-126 suppresses the proliferation, together with the unbalanced down-regulation of IRS-2 and IRS-1. Over-expression of IRS-2 can reverse the proliferation effect of miR-126, while not of IRS-1. These results suggested that miR-126 inhibited the β-cell proliferation via the inhibition of IRS-2 instead of IRS-1.Additionally, we also found that high glucose and insulin could stimulate the rapid production of endogenous miR-126 within 6 hours, together with the short term suppression of IRS-1 and IRS-2 expression, and intensify the unbalanced expression of IRS-1 and IRS-2. Conclusions: IRS-2 was one of the targets of miR-126. MiR-126 inhibited the β-cell proliferation through IRS-2 instead of IRS-1. MiR-126 may take part in the glucose homeostasis both through its target IRS-2 and IRS-1. The unbalance between IRS-1 and IRS-2 caused by miR-126 may play an important role in type 2 diabetes. [ABSTRACT FROM AUTHOR]