Additional file 1 of Prognostic value of soluble ST2, high-sensitivity cardiac troponin, and NT-proBNP in type 2 diabetes: a 15-year retrospective study
Creators: name: Sabbatinelli, Jacopo
name: Giuliani, Angelica
name: Bonfigli, Anna Rita
name: Ramini, Deborah
name: Matacchione, Giulia
name: Campolucci, Carla
name: Ceka, Artan
name: Tortato, Elena
name: Rippo, Maria Rita
name: Procopio, Antonio Domenico
name: Moretti, Marco
name: Olivieri, Fabiola
Publisher: name: figshare
Year: 2022
Subjects: subject: Medicine
subject: Genetics
subject: FOS: Biological sciences
subject: Physiology
subject: 39999 Chemical Sciences not elsewhere classified
subject: FOS: Chemical sciences
subject: Immunology
subject: FOS: Clinical medicine
subject: 69999 Biological Sciences not elsewhere classified
subject: 19999 Mathematical Sciences not elsewhere classified
subject: FOS: Mathematics
subject: Developmental Biology
subject: Cancer
subject: Science Policy

description: Additional file 1: Table S1. Comparison of raw and log-transformed sST2, hs-cTnI, and NT-proBNP serum levels between healthy control subjects (CTR) and patients with type 2 diabetes mellitus (T2DM). Data are median (IQR). P-values for Mann-Whitney U test. Table S2. Correlation matrix between selected clinical/biochemical variables and serum sST2, hs-cTnI, and NT-proBNP in CTR (n=115) and T2DM (n=568) subjects. Table S3. Results of the MANCOVA model in which log-transformed concentrations of sST2, NT-proBNP, and hs-cTnI were used as dependent variables and each T2DM complication as factor. Age, sex, and HbA1c were used as covariates. Univariate tests for post-hoc comparisons are reported. Arrows indicate significant increase of the dependent variable with complications/treatments. Table S4. C-statistics, with 95% confidence intervals, of the Cox regression models for predicting all-cause mortality in T2DM patients. Table S5. Logistic regression model predicting likelihood of developing the composite endpoint death or MACE in T2DM patients without previous history of MACE. Model summary, χ²=107, df=12, p&lt;0.001, Nagelkerke’s R2=0.284. Table S6. Summary of multiple Cox regression analysis for Architect hs-cTnI levels, categorized according to the best cutoffs (4.4 ng/L and 7.5 ng/L) and to the cardiovascular risk categories defined by the manufacturer, for the prediction of survival in T2DM patients. Crude, adjusted (for sex, age, smoking status, hypertension, T2DM duration, BMI, HbA1c, blood lipids, eGFR, and hs-CRP), and multimarker hazard ratios (HR) with 95% confidence intervals are shown. Significant predictors are in bold Figure S1. Kaplan-Meier survival estimates with 95% confidence intervals for patients with T2DM grouped according to the absence (No) or presence (Yes) of T2DM complications. Figure S2. Distribution of serum sST2, Dimension Vista hs-cTnI, and NT-proBNP serum among healthy controls (CTR) and patients with type 2 diabetes (T2DM). Figure S3. A Histogram showing the distribution of raw Architect hs-cTnI serum levels among patients with type 2 diabetes (T2DM). B Passing-Bablok regression between the Siemens Dimension Vista TNIH and the Abbott Architect i-STAT assays for the measurement of hs-cTnI. Regression line with 95% CI is displayed in blue. Line of identity is in red. C–D Bland-Altman plots showing differences between Dimension Vista TNIH and Abbott’s Architect i-STAT hs-cTnI assays for all samples C, and for mean hscTnI values &lt;40 ng/L D. Lower and upper levels of agreement with 95% CI are displayed in red and green, respectively. Figure S4. A Performance of the model based on the internal validation. Model area under the curves (AUCs) at each year are displayed. The solid line represents the mean of the AUC, the dashed line represents the median of the AUC. The darker interval in the plot shows the 25% and 75% quantiles of AUC, the lighter interval shows the minimum and maximum of AUC. B Internal ed external calibration plots showing the observed against the predicted 15 year survival probability for patients with type 2 diabetes grouped according to risk quartiles. The grey diagonal line represents perfect calibration