The gut hormone GLP-2 predicts cardiovascular risk in patients with acute myocardial infarction

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
F Kahles ◽  
R.W Mertens ◽  
M.V Rueckbeil ◽  
M.C Arrivas ◽  
J Moellmann ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Cardiovascular Disease ◽  
Acute Myocardial Infarction ◽  
Receiver Operating Characteristic Curve ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Funding Source ◽  
Cardiovascular Prognosis ◽  
Operating Characteristic Curve ◽  
Hs Crp

Abstract Background GLP-1 and GLP-2 (glucagon-like peptide-1/2) are gut derived hormones that are co-secreted from intestinal L-cells in response to food intake. While GLP-1 is known to induce postprandial insulin secretion, GLP-2 enhances intestinal nutrient absorption and is clinically used for the treatment of patients with short bowel syndrome. The relevance of the GLP-2 system for cardiovascular disease is unknown. Purpose The aim of this study was to assess the predictive capacity of GLP-2 for cardiovascular prognosis in patients with myocardial infarction. Methods Total GLP-2 levels, NT-proBNP concentrations and the Global Registry of Acute Coronary Events (GRACE) score were assessed at time of admission in 918 patients with myocardial infarction, among them 597 patients with NSTEMI and 321 with STEMI. The primary composite outcome of the study was the first occurrence of cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke (3-P-MACE) with a median follow-up of 311 days. Results Kaplan-Meier survival plots (separated by the median of GLP-2 with a cut-off value of 4.4 ng/mL) and univariable cox regression analyses found GLP-2 values to be associated with adverse outcome (logarithmized GLP-2 values HR: 2.87; 95% CI: 1.75–4.68; p<0.0001). Further adjustment for age, sex, smoking, hypertension, hypercholesterolemia, diabetes mellitus, family history of cardiovascular disease, hs-Troponin T, NT-proBNP and hs-CRP levels did not affect the association of GLP-2 with poor prognosis (logarithmized GLP-2 values HR: 2.96; 95% CI: 1.38–6.34; p=0.0053). Receiver operating characteristic curve (ROC) analyses illustrated that GLP-2 is a strong indicator for cardiovascular events and proved to be comparable to other established risk markers (area under the curve of the combined endpoint at 6 months; GLP-2: 0.72; hs-Troponin: 0.56; NT-proBNP: 0.70; hs-CRP: 0.62). Adjustment of the GRACE risk estimate by GLP-2 increased the area under the receiver-operating characteristic curve for the combined triple endpoint after 6 months from 0.70 (GRACE) to 0.75 (GRACE + GLP-2) in NSTEMI patients. Addition of GLP-2 to a model containing GRACE and NT-proBNP led to a further improvement in model performance (increase in AUC from 0.72 for GRACE + NT-proBNP to 0.77 for GRACE + NT-proBNP + GLP-2). Conclusions In patients admitted with acute myocardial infarction, GLP-2 levels are associated with adverse cardiovascular prognosis. This demonstrates a strong yet not appreciated crosstalk between the heart and the gut with relevance for cardiovascular outcome. Future studies are needed to further explore this crosstalk with the possibility of new treatment avenues for cardiovascular disease. Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): German Society of Cardiology (DGK), German Research Foundation (DFG)

P1757GLP-1 levels predict cardiovascular risk in patients with acute myocardial infarction

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
F Kahles ◽  
M V Rueckbeil ◽  
R W Mertens ◽  
A C Foldenauer ◽  
M C Arrivas ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Cardiovascular Risk ◽  
Receiver Operating Characteristic Curve ◽  
Operating Characteristic ◽  
Troponin T ◽  
Characteristic Curve ◽  
Adverse Outcomes ◽  
Operating Characteristic Curve ◽  
Grace Score

Abstract Background Glucagon-like peptide 1 (GLP-1) is a gut incretin hormone, which induces post-prandial glucose-dependent insulin secretion. GLP-1 receptor agonists improve cardiovascular outcomes in patients with diabetes at high cardiovascular risk. We recently found GLP-1 levels to be increased in patients with acute myocardial infarction. Purpose The aim of this study was to assess the predictive capacity of GLP-1 for cardiovascular outcome in patients with myocardial infarction. Methods Total GLP-1 levels, NT-proBNP concentrations and the Global Registry of Acute Coronary Events (GRACE) score were assessed at time of admission in 918 patients with myocardial infarction presenting with acute chest pain. Among these 597 patients presented with NSTEMI and 321 with STEMI. The primary composite outcome of the study was the first occurrence of cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke with a median follow-up of 311 days. Results Kaplan-Meier survival plots (separated by tertiles with cut-off values 35.44 and 53.45) and univariate cox regression analyses found GLP-1 values to be associated with adverse outcome (combined endpoint and all-cause mortality) (logarithmized GLP-1 values HR: 5.459; p<0.0001). Further adjustment for age, sex, previous cardiovascular disease, diabetes, hypertension, hypercholesterinemia, kreatinin, CRP, troponin T and NT-proBNP levels did not affect the association of GLP-1 with adverse outcomes (p=0.0341). Receiver operating characteristic curve analyses illustrated that GLP-1 is a strong indicator for early events (area under the curve of the combined endpoint at 7 days: 0.79; 14 days: 0.81; 30 days: 0.80 and 183 days: 0.64), which proved to be superior to Troponin T, serum creatinin, NT-proBNP and CRP within the first 100 days. Adjustment of the GRACE risk estimate by GLP-1 increased the area under the receiver-operating characteristic curve (AUC) after 1 month from 0.86 to 0.89 in NSTEMI patients. Addition of GLP-1 to a model containing GRACE and NT-proBNP led to a further improvement in model performance (increase in AUC from 0.88 for GRACE + NT-proBNP to 0.90 for GRACE + NT-proBNP + GLP-1). Conclusion GLP-1 is a new biomarker of cardiovascular risk and adverse outcomes in patients with acute myocardial infarction and improves the predictive value of the GRACE score in patients with NSTEMI.

Preoperative skeletal muscle density is associated with postoperative mortality in patients with cardiovascular disease

2019 ◽  
Vol 30 (4) ◽  
pp. 515-522 ◽  
Author(s):  
Masashi Yamashita ◽  
Kentaro Kamiya ◽  
Atsuhiko Matsunaga ◽  
Tadashi Kitamura ◽  
Nobuaki Hamazaki ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Skeletal Muscle ◽  
Receiver Operating Characteristic Curve ◽  
Prognostic Model ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Postoperative Mortality ◽  
Youden Index ◽  
Muscle Density ◽  
Operating Characteristic Curve

Abstract OBJECTIVES Although skeletal muscle density (SMD) is useful for predicting mortality, the cut-off in an acute clinical setting is unclear, especially in patients with cardiovascular disease (CVD). This study was performed to determine the preoperative SMD cut-off using the psoas muscle and to investigate the effect on postoperative outcomes, including sarcopaenia, in CVD patients. METHODS Preoperative psoas SMD was measured by abdominal computed tomography in CVD patients. Postoperative sarcopaenia was defined according to the criteria of the Asia Working Group for Sarcopaenia. The Youden index was used to test the predictive accuracy of survival models. The prognostic capability was evaluated using multivariable survival and receiver operating characteristic curve analyses. RESULTS Continuous data were available for 1068 patients (mean age 65.5 years; 63.6% male). A total of 105 (9.8%) deaths occurred during the 1.99-year median follow-up period (interquartile range 0.71–4.15). The psoas SMD cut-off estimated by the Youden index was 45 Hounsfield units with high sensitivity and moderate specificity for all-cause mortality and was consistent in various stratified analyses. After adjusting for the existing prognostic model, EuroSCORE II, preoperative and postoperative physical status, psoas SMD cut-off was predicted for mortality (hazard ratio 2.42, 95% confidence interval 1.32–4.45). The psoas SMD cut-off was also significantly associated with postoperative sarcopaenia and provided additional prognostic information to EuroSCORE II on receiver operating characteristic curve analysis (area under the curve 0.627 vs 0.678, P = 0.011). CONCLUSIONS Reduced psoas SMD was associated with postoperative mortality and added information prognostic for mortality to the existing prognostic model in CVD patients.

scholarly journals Risk Factors for Nonischemic St-segment Elevation in Patients With Electrocardiographic Left Ventricular Hypertrophy

2021 ◽  
Author(s):  
Haisen Guo ◽  
Weidai Zhang ◽  
Jiawei Zhang ◽  
Chumin Ni ◽  
Zhixiong Cai ◽  
...  
Keyword(s):  
Risk Factors ◽  
Myocardial Infarction ◽  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
St Segment Elevation ◽  
St Segment ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Abstract Background ST-segment elevation (STE) is not a specific change for ST-segment elevation myocardial infarction (STEMI). This may lead to a mistaken diagnosis of STEMI and false-positive cardiac catheterization laboratory activation. We aimed to investigate risk factors for STE secondary to electrocardiographic LVH in order to provide more information for differential diagnosis.Methods A total of 1,590 inpatients with electrocardiographic LVH without confounding factors (such as myocardial infarction) were enrolled in this study. Data on potential risk factors and patient characteristics were collected. Logistic regression analysis and receiver operating characteristic curve (ROC) were used to identify the risk of STE in patients with LVH.Results After reviewing the ECGs, 1590 cases of electrocardiographic LVH were divided into an ST-segment elevation group (STE group, 81 cases) and non-ST segment elevation group (1509 cases). Eighty-seven cases were randomly selected from the non-ST segment elevation group to form a new non-ST segment elevation group (non-STE group, 87 cases) for further analysis. The mean age of the 168 participants (119 men, 70.83%) was 62.33 ± 16.27. Multivariate analysis showed that stroke, infection, and the value of SV1+RV5 were significantly associated with STE secondary to LVH. The area under the receiver operating characteristic curve showed that the optimal value of SV1+RV5 cut-off for predicting STE was 4.805 (sensitivity: 40.74%; specificity: 80.46%; AUC: 0.634; 95% CI: 0.550–0.719; P < 0.05).Conclusions A value of SV1+RV5 larger than 4.8 mV, stroke, and infection are independent risk factors for STE in patients with electrocardiographic LVH.

scholarly journals Biomarkers Enhance Discrimination and Prognosis of Type 2 Myocardial Infarction

Circulation ◽  
2020 ◽  
Vol 142 (16) ◽  
pp. 1532-1544
Author(s):  
Yu Horiuchi ◽  
Nicholas Wettersten ◽  
Mitul P. Patel ◽  
Christian Mueller ◽  
Sean-Xavier Neath ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Major Adverse Cardiovascular Event ◽  
Adverse Cardiovascular Event ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Background: The observed incidence of type 2 myocardial infarction (T2MI) is expected to increase with the implementation of increasingly sensitive cTn assays. However, it remains to be determined how to diagnose, risk-stratify, and treat patients with T2MI. We aimed to discriminate and risk-stratify T2MI using biomarkers. Methods: Patients presenting to the emergency department with chest pain, enrolled in the CHOPIN study (Copeptin Helps in the early detection Of Patients with acute myocardial INfarction), were retrospectively analyzed. Two cardiologists adjudicated type 1 MI (T1MI) and T2MI. The prognostic ability of several biomarkers alone or in combination to discriminate T2MI from T1MI was investigated using receiver operating characteristic curve analysis. The biomarkers analyzed were cTnI, copeptin, MR-proANP (midregional proatrial natriuretic peptide), CT-proET1 (C-terminal proendothelin-1), MR-proADM (midregional proadrenomedullin), and procalcitonin. The prognostic utility of these biomarkers for all-cause mortality and major adverse cardiovascular event (a composite of acute myocardial infarction, unstable angina pectoris, reinfarction, heart failure, and stroke) at 180-day follow-up was also investigated. Results: Among the 2071 patients, T1MI and T2MI were adjudicated in 94 and 176 patients, respectively. Patients with T1MI had higher levels of baseline cTnI, whereas those with T2MI had higher baseline levels of MR-proANP, CT-proET1, MR-proADM, and procalcitonin. The area under the receiver operating characteristic curve for the diagnosis of T2MI was higher for CT-proET1, MR-proADM, and MR-proANP (0.765, 0.750, and 0.733, respectively) than for cTnI (0.631). Combining all biomarkers resulted in a similar accuracy to a model using clinical variables and cTnI (0.854 versus 0.884, P =0.294). Addition of biomarkers to the clinical model yielded the highest area under the receiver operating characteristic curve (0.917). Other biomarkers, but not cTnI, were associated with mortality and major adverse cardiovascular event at 180 days among all patients, with no interaction between the diagnosis of T1MI or T2MI. Conclusions: Assessment of biomarkers reflecting pathophysiologic processes occurring with T2MI might help differentiate it from T1MI. All biomarkers measured, except cTnI, were significant predictors of prognosis, regardless of the type of myocardial infarction.

A validated novel preoperative index to predict the extent of intraperitoneal contamination in patients with acute abdominal pathology: A cohort study

2019 ◽  
Vol 30 (7-8) ◽  
pp. 221-228
Author(s):  
Shahab Hajibandeh ◽  
Shahin Hajibandeh ◽  
Nicholas Hobbs ◽  
Jigar Shah ◽  
Matthew Harris ◽  
...  
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Validation Cohort ◽  
Characteristic Curve ◽  
Curve Analysis ◽  
Emergency Laparotomy ◽  
Contamination Index ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Aims To investigate whether an intraperitoneal contamination index (ICI) derived from combined preoperative levels of C-reactive protein, lactate, neutrophils, lymphocytes and albumin could predict the extent of intraperitoneal contamination in patients with acute abdominal pathology. Methods Patients aged over 18 who underwent emergency laparotomy for acute abdominal pathology between January 2014 and October 2018 were randomly divided into primary and validation cohorts. The proposed intraperitoneal contamination index was calculated for each patient in each cohort. Receiver operating characteristic curve analysis was performed to determine discrimination of the index and cut-off values of preoperative intraperitoneal contamination index that could predict the extent of intraperitoneal contamination. Results Overall, 468 patients were included in this study; 234 in the primary cohort and 234 in the validation cohort. The analyses identified intraperitoneal contamination index of 24.77 and 24.32 as cut-off values for purulent contamination in the primary cohort (area under the curve (AUC): 0.73, P < 0.0001; sensitivity: 84%, specificity: 60%) and validation cohort (AUC: 0.83, P < 0.0001; sensitivity: 91%, specificity: 69%), respectively. Receiver operating characteristic curve analysis also identified intraperitoneal contamination index of 33.70 and 33.41 as cut-off values for feculent contamination in the primary cohort (AUC: 0.78, P < 0.0001; sensitivity: 87%, specificity: 64%) and validation cohort (AUC: 0.79, P < 0.0001; sensitivity: 86%, specificity: 73%), respectively. Conclusions As a predictive measure which is derived purely from biomarkers, intraperitoneal contamination index may be accurate enough to predict the extent of intraperitoneal contamination in patients with acute abdominal pathology and to facilitate decision-making together with clinical and radiological findings.

scholarly journals Evaluation of factors that predict the success rate of trial of labor after the cesarean section

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yang Mi ◽  
Pengfei Qu ◽  
Na Guo ◽  
Ruimiao Bai ◽  
Jiayi Gao ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Cesarean Section ◽  
Receiver Operating Characteristic Curve ◽  
Success Rate ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Predictive Ability ◽  
Training Set ◽  
History Of ◽  
Operating Characteristic Curve

Abstract Background For most women who have had a previous cesarean section, vaginal birth after cesarean section (VBAC) is a reasonable and safe choice, but which will increase the risk of adverse outcomes such as uterine rupture. In order to reduce the risk, we evaluated the factors that may affect VBAC and and established a model for predicting the success rate of trial of the labor after cesarean section (TOLAC). Methods All patients who gave birth at Northwest Women’s and Children’s Hospital from January 2016 to December 2018, had a history of cesarean section and voluntarily chose the TOLAC were recruited. Among them, 80% of the population was randomly assigned to the training set, while the remaining 20% were assigned to the external validation set. In the training set, univariate and multivariate logistic regression models were used to identify indicators related to successful TOLAC. A nomogram was constructed based on the results of multiple logistic regression analysis, and the selected variables included in the nomogram were used to predict the probability of successfully obtaining TOLAC. The area under the receiver operating characteristic curve was used to judge the predictive ability of the model. Results A total of 778 pregnant women were included in this study. Among them, 595 (76.48%) successfully underwent TOLAC, whereas 183 (23.52%) failed and switched to cesarean section. In multi-factor logistic regression, parity = 1, pre-pregnancy BMI < 24 kg/m2, cervical score ≥ 5, a history of previous vaginal delivery and neonatal birthweight < 3300 g were associated with the success of TOLAC. The area under the receiver operating characteristic curve in the prediction and validation models was 0.815 (95% CI: 0.762–0.854) and 0.730 (95% CI: 0.652–0.808), respectively, indicating that the nomogram prediction model had medium discriminative power. Conclusion The TOLAC was useful to reducing the cesarean section rate. Being primiparous, not overweight or obese, having a cervical score ≥ 5, a history of previous vaginal delivery or neonatal birthweight < 3300 g were protective indicators. In this study, the validated model had an approving predictive ability.

A conditional approach for the receiver operating characteristic curve construction to evaluate diagnostic test performance in a family-matched case–control design

2021 ◽  
pp. 096228022199595
Author(s):  
Yalda Zarnegarnia ◽  
Shari Messinger
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Case Control ◽  
Paired Data ◽  
Characteristic Curves ◽  
Receiver Operating Characteristic Curves ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Receiver operating characteristic curves are widely used in medical research to illustrate biomarker performance in binary classification, particularly with respect to disease or health status. Study designs that include related subjects, such as siblings, usually have common environmental or genetic factors giving rise to correlated biomarker data. The design could be used to improve detection of biomarkers informative of increased risk, allowing initiation of treatment to stop or slow disease progression. Available methods for receiver operating characteristic construction do not take advantage of correlation inherent in this design to improve biomarker performance. This paper will briefly review some developed methods for receiver operating characteristic curve estimation in settings with correlated data from case–control designs and will discuss the limitations of current methods for analyzing correlated familial paired data. An alternative approach using conditional receiver operating characteristic curves will be demonstrated. The proposed approach will use information about correlation among biomarker values, producing conditional receiver operating characteristic curves that evaluate the ability of a biomarker to discriminate between affected and unaffected subjects in a familial paired design.

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