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Practical cardiovascular risk calculator for asymptomatic patients with type 2 diabetes mellitus: PRECISE-DM risk score.

ABSTRACT: BACKGROUND:Obstructive coronary artery disease (OCAD) is a significant predictor of adverse clinical events in asymptomatic patients with type 2 diabetes mellitus (T2DM). HYPOTHESIS:We sought to develop an easy-to-use risk scoring system to predict OCAD and long-term clinical outcome in asymptomatic patients with T2DM (PRECISE-DM). METHODS:A total of 2799 asymptomatic patients with T2DM and no prior coronary disease were consecutively enrolled. OCAD was defined as ?50% coronary artery stenosis on coronary computed tomography angiography (CCTA). A new risk scoring system was developed in 933 patients undergoing CCTA (derivation cohort) and its performance to predict OCAD and major adverse cardiac and cerebrovascular event (MACCE) was compared with other risk estimates. The scoring system was externally validated in 1899 patients not undergoing CCTA (validation cohort). RESULTS:The PRECISE-DM scoring system was created using seven variables that were associated with increased risk of OCAD, with scores ranging from 0 to 9. The scoring system predicted presence of OCAD with a C-statistic of 0.680 and risk of MACCE with a C-statistic of 0.708. The UKPDS risk engine and the Framingham risk score showed unreliable performance in prediction of OCAD (C-statistics 0.531 and 0.577, respectively). Calcium score was highly predictive for OCAD (C-statistic 0.825) but showed only modest accuracy in predicting MACCE (C-statistic 0.675). In the external validation cohort, the PRECISE-DM score showed acceptable discrimination for prediction of MACCE (C-statistic 0.707). CONCLUSIONS:The PRECISE-DM scoring system accurately predicted presence of OCAD and risk of MACCE in asymptomatic patients with T2DM.

SUBMITTER: Choi Y

PROVIDER: S-EPMC7462187 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Practical cardiovascular risk calculator for asymptomatic patients with type 2 diabetes mellitus: PRECISE-DM risk score.

Choi Young Y Yang Yeoree Y Hwang Byung-Hee BH Lee Eun Young EY Yoon Kun Ho KH Chang Kiyuk K Jaffer Farouc A FA Cho Jae-Hyoung JH

Clinical cardiology 20200713 9

<h4>Background</h4>Obstructive coronary artery disease (OCAD) is a significant predictor of adverse clinical events in asymptomatic patients with type 2 diabetes mellitus (T2DM).<h4>Hypothesis</h4>We sought to develop an easy-to-use risk scoring system to predict OCAD and long-term clinical outcome in asymptomatic patients with T2DM (PRECISE-DM).<h4>Methods</h4>A total of 2799 asymptomatic patients with T2DM and no prior coronary disease were consecutively enrolled. OCAD was defined as ≥50% coro ...[more]

PMID: 32656853

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Project description:BackgroundsCardiac autonomic neuropathy is a common but always overlooked. More convenient diagnostic methods are needed.HypothesisCardiac autonomic neuropathy risk score evaluated by SUDOSCAN has a fine diagnostic efficacy detecting cardiac autonomic neuropathy.MethodsThis is a cross-sectional study among patients with diabetes mellitus. Subjects undertook SUDOSCAN tests and cardiac autonomic reflex tests, including heart rate variability due to Valsalva maneuver, heart rate response due to deep breathing and heart rate response due to standing up. Presenting 2 abnormal results was defined as cardiac autonomic neuropathy.ResultsSubjects with cardiac autonomic neuropathy has significantly higher cardiac autonomic neuropathy risk score (32.88±1.60 vs 27.64±1.24,P = 0.010). Cardiac autonomic neuropathy risk score was correlated significantly with the heart rate response due to deep breathing(P = 0.004). Multiple regression analysis including significant variables showed an independent association of cardiac autonomic neuropathy risk score and heart rate response due to deep breathing (P = 0.031) and age (P = 0.000). In receiver operating characteristic curve analysis evaluating the relationship between cardiac autonomic neuropathy risk score and cardiac autonomic neuropathy, The cut-off value was 20.5, with the sensitivity of 90.48%, the specificity of 29.5%, and the positive predictive value of 46.9%. In two-step diagnostic methods, Setting 20.5 as the cut-off value of cardiac autonomic neuropathy risk score and abnormal heart rate response due to standing up as the second diagnostic step's positive result, and setting 16.5 as the cut-off value of cardiac autonomic neuropathy risk score and abnormal heart rate response due to deep breathing as the second diagnostic step's positive result, both achieved good diagnostic efficacy.ConclusionCardiac autonomic neuropathy risk score evaluated by SUDOSCAN is a good screening test for cardiac autonomic neuropathy. The two-step diagnostic methods could be considered as surrogate diagnostic methods.

Project description:BACKGROUND:Individuals with diabetes often have high levels of atherogenic lipoproteins and cholesterol reflected by elevated low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol (non-HDL-C), apolipoprotein B (ApoB), and LDL particle number (LDL-PN). The presence of atherosclerotic cardiovascular disease (ASCVD) increases the risk of future cardiovascular events. We evaluated the efficacy and safety of the proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitor, alirocumab, among individuals with type 2 diabetes (T2DM), high LDL-C or non-HDL-C, and established ASCVD receiving maximally tolerated statin in ODYSSEY DM-DYSLIPIDEMIA (NCT02642159) and DM-INSULIN (NCT02585778). METHODS:In DM-DYSLIPIDEMIA, individuals with T2DM and mixed dyslipidemia (non-HDL-C???100 mg/dL; n?=?413) were randomized to open-label alirocumab 75 mg every 2 weeks (Q2W) or usual care (UC) for 24 weeks, with UC options selected before stratified randomization. In DM-INSULIN, insulin-treated individuals with T2DM (LDL-C???70 mg/dL; n?=?441) were randomized in a double-blind fashion to alirocumab 75 mg Q2W or placebo for 24 weeks. Study participants also had a glycated hemoglobin?<?9% (DM-DYSLIPIDEMIA) or?<?10% (DM-INSULIN). Alirocumab dose was increased to 150 mg Q2W at week 12 if week 8 LDL-C was???70 mg/dL (DM-INSULIN) or non-HDL-C was???100 mg/dL (DM-DYSLIPIDEMIA). Lipid reductions and safety were assessed in patients with ASCVD from these studies. RESULTS:This analysis included 142 DM-DYSLIPIDEMIA and 177 DM-INSULIN participants with ASCVD, including 95.1% and 86.4% with coronary heart disease, and 32.4% and 49.7% with microvascular diabetes complications, respectively. At week 24, alirocumab significantly reduced LDL-C, non-HDL-C, ApoB, and LDL-PN from baseline versus control. This translated into a greater proportion of individuals achieving non-HDL-C?<?100 mg/dL (64.6% alirocumab/23.8% UC [DM-DYSLIPIDEMIA]; 65.4% alirocumab/14.9% placebo [DM-INSULIN]) and ApoB?<?80 mg/dL (75.1% alirocumab/35.4% UC and 76.8% alirocumab/24.8% placebo, respectively) versus control at week 24 (all P?<?0.0001). In pooling these studies, 66.4% (alirocumab) and 67.0% (control) of individuals reported treatment-emergent adverse events. The adverse event pattern was similar with alirocumab versus controls. CONCLUSIONS:Among individuals with T2DM and ASCVD who had high non-HDL-C/LDL-C levels despite maximally tolerated statin, alirocumab significantly reduced atherogenic cholesterol and LDL-PN versus control. Alirocumab was generally well tolerated. Trial registration Clinicaltrials.gov. NCT02642159. Registered 30 December 2015 and Clinicaltrials.gov. NCT02585778. Registered 23 October 2015.

Project description:OBJECTIVE:To develop and validate a novel, machine learning-derived model to predict the risk of heart failure (HF) among patients with type 2 diabetes mellitus (T2DM). RESEARCH DESIGN AND METHODS:Using data from 8,756 patients free at baseline of HF, with <10% missing data, and enrolled in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial, we used random survival forest (RSF) methods, a nonparametric decision tree machine learning approach, to identify predictors of incident HF. The RSF model was externally validated in a cohort of individuals with T2DM using the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT). RESULTS:Over a median follow-up of 4.9 years, 319 patients (3.6%) developed incident HF. The RSF models demonstrated better discrimination than the best performing Cox-based method (C-index 0.77 [95% CI 0.75-0.80] vs. 0.73 [0.70-0.76] respectively) and had acceptable calibration (Hosmer-Lemeshow statistic ?2 = 9.63, P = 0.29) in the internal validation data set. From the identified predictors, an integer-based risk score for 5-year HF incidence was created: the WATCH-DM (Weight [BMI], Age, hyperTension, Creatinine, HDL-C, Diabetes control [fasting plasma glucose], QRS Duration, MI, and CABG) risk score. Each 1-unit increment in the risk score was associated with a 24% higher relative risk of HF within 5 years. The cumulative 5-year incidence of HF increased in a graded fashion from 1.1% in quintile 1 (WATCH-DM score ?7) to 17.4% in quintile 5 (WATCH-DM score ?14). In the external validation cohort, the RSF-based risk prediction model and the WATCH-DM risk score performed well with good discrimination (C-index = 0.74 and 0.70, respectively), acceptable calibration (P ?0.20 for both), and broad risk stratification (5-year HF risk range from 2.5 to 18.7% across quintiles 1-5). CONCLUSIONS:We developed and validated a novel, machine learning-derived risk score that integrates readily available clinical, laboratory, and electrocardiographic variables to predict the risk of HF among outpatients with T2DM.

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Practical cardiovascular risk calculator for asymptomatic patients with type 2 diabetes mellitus: PRECISE-DM risk score.

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Practical cardiovascular risk calculator for asymptomatic patients with type 2 diabetes mellitus: PRECISE-DM risk score.

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