Role of B-Type Natriuretic Peptide and N-Terminal Prohormone BNP as Predictors of Cardiovascular Morbidity and Mortality in Patients With a Recent Coronary Event and Type 2 Diabetes Mellitus

The relative and combined ability of stress hyperglycemia ratio and N-terminal pro-B-type natriuretic peptide to predict all-cause mortality in diabetic patients with multivessel coronary artery disease

BACKGROUND

Stress hyperglycemia ratio (SHR) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) are independently associated with increased mortality risk in diabetic patients with coronary artery disease (CAD). However, the role of these biomarkers in patients with diabetes and multivessel disease (MVD) remains unknown. The present study aimed to assess the relative and combined abilities of these biomarkers to predict all-cause mortality in patients with diabetes and MVD.

METHODS

This study included 1148 diabetic patients with MVD who underwent coronary angiography at Tianjin Chest Hospital between January 2016 and December 2016. The patients were divided into four groups according to their SHR (SHR-L and SHR-H) and NT-proBNP (NT-proBNP-L and NT-proBNP-H) levels. The primary outcome was all-cause mortality. Multivariate Cox regression analyses were performed to evaluate the association of SHR and NT-proBNP levels with all-cause mortality.

RESULTS

During a mean 4.2 year follow-up, 138 patients died. Multivariate analysis showed that SHR and NT-proBNP were strong independent predictors of all-cause mortality in diabetic patients with MVD (SHR: HR hazard ratio [2.171; 95%CI 1.566-3.008; P < 0.001; NT-proBNP: HR: 1.005; 95%CI 1.001-1.009; P = 0.009). Compared to patients in the first (SHR-L and NT-proBNP-L) group, patients in the fourth (SHR-H and NT-proBNP-H) group had the highest mortality risk (HR: 12.244; 95%CI 5.828-25.721; P < 0.001). The areas under the curve were 0.615(SHR) and 0.699(NT-proBNP) for all-cause mortality. Adding either marker to the original models significantly improved the C-statistic and integrated discrimination improvement values (all P < 0.05). Moreover, combining SHR and NT-proBNP levels into the original model provided maximal prognostic information.

CONCLUSIONS

SHR and NT-proBNP independently and jointly predicted all-cause mortality in diabetic patients with MVD, suggesting that strategies to improve risk stratification in these patients should incorporate SHR and NT-porBNP into risk algorithms.

Impact of age on the predictive value of NT-proBNP in patients with diabetes mellitus stabilised after an acute coronary syndrome

AIMS

To assess the impact of age on the prognostic value of NT-proBNP concentration in patients with type-2 diabetes mellitus (T2DM) stabilised after an Acute Coronary Syndrome (ACS).

METHODS

The AleCardio study compared aleglitazar with placebo in 7226 patients with T2DM and recent ACS. Patients with heart failure were excluded. Median follow-up was 104 weeks. Baseline NT-proBNP plasma concentration was measured centrally. Multivariable Cox regression was used to determine the mortality predictive information provided by NT-proBNP across age groups.

RESULTS

Median age was 61y (IQR 54, 67). NT-proBNP concentration increased by quartile (Q) of age (median 264, 318, 391, and 588 pg/ml). Compared to Q1, patients in Q4 of NT-proBNP had higher (p < 0.001) adjusted HR for all-cause (aHR 6.9; 95 % CI 4.0-12) and cardiovascular (11; 5.4-23) death. Within each age Q, baseline NT-proBNP in patients who died was 3 times higher than in survivors (all p < 0.001). When age and NT-proBNP levels were modeled as continuous variables, their interaction term was nonsignificant. The relative prognostic information provided by NT-proBNP (percent of total X2) increased from 38 % in age Q1 to 75 % in age Q4 for mortality, and from 50 % to 88 % for CV death.

CONCLUSIONS

Among patients with T2DM stabilised after an ACS, NT-proBNP level predicts death irrespective of age.

Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis

BACKGROUND

Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with Type 2 diabetes (T2D).

METHODS

We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies.

RESULTS

Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort.

CONCLUSIONS

Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.

Cardioprotective and Antifibrotic Effects of Low-Dose Renin-Angiotensin-Aldosterone System Inhibitors in Type 1 Diabetic Rat Model

Diabetic cardiovascular complications are associated with up to 50% mortality, and current therapies are not effective enough. Renin-angiotensin-aldosterone system inhibitors (RAASis) are the standard of care for diabetic patients with hypertension and albuminuria. Based on our previous studies reporting the renoprotective effects of low-dose RAASis, here, we hypothesized that low-dose RAASi treatment has cardioprotective and antifibrotic benefits in type 1 diabetes mellitus (T1DM). After five weeks of T1DM, adult male Wistar rats received low doses of ramipril, losartan, or eplerenone for two weeks. Heart rate, blood pressure, and pulse wave velocity (PWV) were recorded. Aortic intima-media thickness (IMT), collagen accumulation, and myocardial fibrosis were assessed. All RAASis reduced PWV elevation, prevented the progression of myocardial fibrosis, and normalized B-type natriuretic peptide, troponin I, and fibroblast growth factor 23 levels without affecting blood pressure. Interestingly, only eplerenone reversed the decline in Klotho levels and reduced IMT and fibrosis in the media of the aorta. Our comparative analysis suggests that mineralocorticoid receptor antagonists, particularly eplerenone, may offer superior efficacy in halting both the arterial and the myocardial injuries in T1DM compared to angiotensin-converting enzyme inhibitors or angiotensin II type 1 receptor blockers.

Effect of body mass index on N-terminal pro-brain natriuretic peptide values in patients with heart failure

BACKGROUND

N-terminal pro-B-type natriuretic peptide (NT-proBNP) is a biomarker used for the diagnosis of heart failure. There is a relationship between NT-proBNP levels and body mass index (BMI). The study aimed to explore the impact of BMI on NT-proBNP concentrations and to examine whether other factors independent of or combined with BMI affect NT-proBNP values in patients with heart failure.

RESULTS

A total of 293 participants were recruited. The mean age was 68.9 ± 13.2 years, males accounted for 46.4% of the total cohort, the mean BMI was 23.1 ± 4.0 kg/m2, and the median NT-proBNP level was 3776 (1672-8806) pg/ml. There was an inverse relationship between BMI and log NT-proBNP (r = - 0.29; p < 0.001, Spearman correlation). Each standard deviation increase in BMI (4 kg/m2) was associated with a 7% decrease in NT-proBNP values in the total cohort. The independent inverse determinants of NT-proBNP other than BMI were male gender and eGFR, while the variables directly correlated to NT-proBNP were LVEF ≤ 40% and NYHA class III-IV heart failure.

CONCLUSIONS

There is an inverse association between BMI and NT-proBNP levels. However, the correlation is weak, and there are other variables that have a significant impact on the NT-proBNP values as well. The NT-proBNP levels are still valuable in the diagnosis of heart failure regardless of BMI status.

Precision Prognostics for Cardiovascular Disease in Type 2 Diabetes: A Systematic Review and Meta-analysis

Background Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with type 2 diabetes (T2D). Methods We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies. Results Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort. Conclusions Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.

Predicting and preventing heart failure in type 2 diabetes

The burden of heart failure among people with type 2 diabetes is increasing globally. People with comorbid type 2 diabetes and heart failure often have worse outcomes than those with only one of these conditions-eg, higher hospitalisation and mortality rates. Therefore, it is essential to implement optimal heart failure prevention strategies for people with type 2 diabetes. A detailed understanding of the pathophysiology underlying the occurrence of heart failure in type 2 diabetes can aid clinicians in identifying relevant risk factors and lead to early interventions that can help prevent heart failure. In this Review, we discuss the pathophysiology and risk factors of heart failure in type 2 diabetes. We also review the risk assessment tools for predicting heart failure incidence in people with type 2 diabetes as well as the data from clinical trials that have assessed the efficacy of lifestyle and pharmacological interventions. Finally, we discuss the potential challenges in implementing new management approaches and offer pragmatic recommendations to help overcome these challenges.

Daily exercise improves the long-term prognosis of patients with acute coronary syndrome

Objective

To demonstrate the effect of daily exercise on the incidence of major adverse cardiovascular events (MACE) for patients with acute coronary syndrome (ACS).

Methods

A cohort of 9,636 patients with ACS were consecutively enrolled in our retrospective study between November 2015 and September 2017, which were used for model development. 6,745 patients were assigned as the derivation cohort and 2,891 patients were assigned as the validation cohort. The least absolute shrinkage and selection operator (LASSO) regression and COX regression were used to screen out significant variables for the construction of the nomogram. Multivariable COX regression analysis was employed for the development of a model represented by a nomogram. The nomogram was then evaluated for performance traits such as discrimination, calibration, and clinical efficacy.

Results

Among 9,636 patients with ACS (mean [SD] age, 60.3 [10.4] years; 7,235 men [75.1%]), the 5-year incidence for MACE was 0.19 at a median follow-up of 1,747 (1,160–1,825) days. Derived from the LASSO regression and COX regression, the nomogram has included 15 factors in total including age, previous myocardial infarction (MI), previous percutaneous coronary intervention (PCI), systolic pressure, N-terminal Pro-B-type natriuretic peptide (NT-proBNP), high-density lipoprotein cholesterol (HDL), serum creatinine, left ventricular end-diastolic diameter (LVEDD), Killip class, the Synergy between Percutaneous Coronary Intervention with Taxus and Cardiac Surgery (SYNTAX) score, left anterior descending (LAD) stenosis (≥50%), circumflex (LCX) stenosis (≥50%), right coronary artery (RCA) stenosis (≥50%), exercise intensity, cumulative time. The 5-year area under the ROC curve (AUC) of derivation and validation cohorts were 0.659 (0.643–0.676) and 0.653 (0.629–0.677), respectively. The calibration plots showed the strong concordance performance of the nomogram model in both two cohorts. Moreover, decision curve analysis (DCA) also showed the usefulness of nomogram in clinical practice.

Conclusion

The present work provided a prediction nomogram predicting MACE for patients with ACS after incorporating the already known factors and the daily exercise, which demonstrated the effectiveness of daily exercise on the improvement of prognosis for patients with ACS.

Association of N-terminal pro-B-type natriuretic peptide (NT-proBNP) and acute kidney disease in patients undergoing coronary angiography: a cohort study

BACKGROUND

Acute kidney disease (AKD) following coronary angiography (CAG) indicates a higher risk of chronic kidney disease and follow-up cardiovascular comorbidities. However, the predictive risk factor of AKD is not clear. We sought to verify whether preoperative N-terminal pro-B-type natriuretic peptide (NT-proBNP) level was associated with AKD in patients undergoing CAG.

METHOD

We analyzed 7602 patients underwent CAG in this multi-center registry cohort study. Cardiorenal ImprovemeNt II (CIN-II) in five Chinese tertiary hospitals from 2007 to 2020. The primary outcome was AKD, defined as a ≥ 50% increase of serum creatinine within 7-90 days. Multivariable logistic regressions were used to assess the association between NT-proBNP and AKD.

RESULT

1009 patients (13.27%) eventually developed AKD, who were more likely to be female, older, and with comorbidities of chronic heart failure and anemia. After adjusting to the potential confounders, the NT-proBNP level remained an independent predictor of AKD (lnNT-proBNP OR: 1.20, 95% CI 1.13-1.28, p < 0.005). Restricted cubic spline analysis demonstrated a linear relationship between elevated NT-proBNP and AKD (p for trend < 0.001). In the subgroup analysis, elevated NT-proBNP level in patients with percutaneous coronary intervention (p for interaction < 0.001) or without previous congestive heart failure (p for interaction = 0.0346) has a more significant value of AKD prediction.

CONCLUSION

Pre-operative NT-proBNP level was independently associated with the risk of AKD in patients following CAG. Perioperative strategies are warranted to prevent AKD in patients with elevated NT-proBNP levels.

Conventional Biomarkers for Predicting Clinical Outcomes in Patients with Heart Disease

Atherosclerosis is the main cause of cardiovascular disease worldwide. The progression of coronary atherosclerosis leads to coronary artery disease, with impaired blood flow to the myocardium and subsequent development of myocardial ischemia. Acute coronary syndromes and post-myocardial infarction heart failure are two of the most common complications of coronary artery disease and are associated with worse outcomes. In order to improve the management of patients with coronary artery disease and avoid major cardiovascular events, several risk assessment tools have been developed. Blood and imaging biomarkers, as well as clinical risk scores, are now available and validated for clinical practice, but research continues. The purpose of the current paper is to provide a review of recent findings regarding the use of humoral biomarkers for risk assessment in patients with heart disease.

Importance of NT-proBNP and conventional risk factors for prediction of death in older adults with and without diabetes mellitus- A report from the Atherosclerosis Risk in Communities (ARIC) study

In this community-based cohort of 5861 individuals followed for median 7.2 years, the discriminatory ability of NT-proBNP alone in predicting mortality was similar to that of multiple conventional markers of risk in people without diabetes. In people with diabetes, NT-proBNP alone discriminated risk of mortality better than conventional risk factors.

Effects of DPP4 Inhibitor in Platelet Reactivity and Other Cardiac Risk Markers in Patients with Type 2 Diabetes and Acute Myocardial Infarction

Background: The management of acute myocardial infarction (AMI) presents several challenges in patients with diabetes, among them the higher rate of recurrent thrombotic events, hyperglycemia and risk of subsequent heart failure (HF). The objective of our study was to evaluate effects of DPP-4 inhibitors (DPP-4i) on platelet reactivity (main objective) and cardiac risk markers. Methods: We performed a single-center double-blind randomized trial. A total of 70 patients with type 2 diabetes (T2DM) with AMI Killip ≤2 on dual-antiplatelet therapy (aspirin plus clopidogrel) were randomized to receive sitagliptin 100 mg or saxagliptin 5 mg daily or matching placebo. Platelet reactivity was assessed at baseline, 4 days (primary endpoint) and 30 days (secondary endpoint) after randomization, using VerifyNow Aspirin™ assay, expressed as aspirin reaction units (ARUs); B-type natriuretic peptide (BNP) in pg/mL was assessed at baseline and 30 days after (secondary endpoint). Results: Mean age was 62.6 ± 8.8 years, 45 (64.3%) male, and 52 (74.3%) of patients presented with ST-segment elevation MI. For primary endpoint, there were no differences in mean platelet reactivity (p = 0.51) between the DPP-4i (8.00 {−65.00; 63.00}) and placebo (−14.00 {−77.00; 52.00}) groups, as well in mean BNP levels (p = 0.14) between DPP-4i (−36.00 {−110.00; 15.00}) and placebo (−13.00 {−50.00; 27.00}). There was no difference between groups in cardiac adverse events. Conclusions: DPP4 inhibitor did not reduce platelet aggregation among patients with type 2 diabetes hospitalized with AMI. Moreover, the use of DPP-4i did not show an increase in BNP levels or in the incidence of cardiac adverse events. These findings suggests that DPP-4i could be an option for management of T2DM patients with acute MI.

Protein Biomarkers and Cardiovascular Outcomes in People With Type 2 Diabetes and Acute Coronary Syndrome: The ELIXA Biomarker Study

OBJECTIVE

To use protein biomarkers to identify people with type 2 diabetes at high risk of cardiovascular outcomes and death.

RESEARCH DESIGN AND METHODS

Biobanked serum from 4,957 ELIXA (Evaluation of Lixisenatide in Acute Coronary Syndrome) trial participants was analyzed. Forward-selection Cox models identified independent protein risk factors for major adverse cardiovascular events (MACE) and death that were compared with a previously validated biomarker panel.

RESULTS

NT-proBNP and osteoprotegerin predicted both outcomes. In addition, trefoil factor 3 predicted MACE, and angiopoietin-2 predicted death (C = 0.70 and 0.79, respectively, compared with 0.63 and 0.66 for clinical variables alone). These proteins had all previously been identified and validated. Notably, C statistics for just NT-proBNP plus clinical risk factors were 0.69 and 0.78 for MACE and death, respectively.

CONCLUSIONS

NT-proBNP and other proteins independently predict cardiovascular outcomes in people with type 2 diabetes following acute coronary syndrome. Adding other biomarkers only marginally increased NT-proBNP's prognostic value.

From Classic to Modern Prognostic Biomarkers in Patients with Acute Myocardial Infarction

Despite all the important advances in its diagnosis and treatment, acute myocardial infarction (AMI) is still one of the most prominent causes of morbidity and mortality worldwide. Early identification of patients at high risk of poor outcomes through the measurement of various biomarker concentrations might contribute to more accurate risk stratification and help to guide more individualized therapeutic strategies, thus improving prognoses. The aim of this article is to provide an overview of the role and applications of cardiac biomarkers in risk stratification and prognostic assessment for patients with myocardial infarction. Although there is no ideal biomarker that can provide prognostic information for risk assessment in patients with AMI, the results obtained in recent years are promising. Several novel biomarkers related to the pathophysiological processes found in patients with myocardial infarction, such as inflammation, neurohormonal activation, myocardial stress, myocardial necrosis, cardiac remodeling and vasoactive processes, have been identified; they may bring additional value for AMI prognosis when included in multi-biomarker strategies. Furthermore, the use of artificial intelligence algorithms for risk stratification and prognostic assessment in these patients may have an extremely important role in improving outcomes.

Molecular Mechanism of Induction of Bone Growth by the C-Type Natriuretic Peptide

The skeletal development process in the body occurs through sequential cellular and molecular processes called endochondral ossification. Endochondral ossification occurs in the growth plate where chondrocytes differentiate from resting, proliferative, hypertrophic to calcified zones. Natriuretic peptides (NPTs) are peptide hormones with multiple functions, including regulation of blood pressure, water-mineral balance, and many metabolic processes. NPTs secreted from the heart activate different tissues and organs, working in a paracrine or autocrine manner. One of the natriuretic peptides, C-type natriuretic peptide-, induces bone growth through several mechanisms. This review will summarize the knowledge, including the newest discoveries, of the mechanism of CNP activation in bone growth.

Clinical Prediction Models for Heart Failure Hospitalization in Type 2 Diabetes: A Systematic Review and Meta-Analysis

Background Clinical prediction models have been developed for hospitalization for heart failure in type 2 diabetes. However, a systematic evaluation of these models' performance, applicability, and clinical impact is absent. Methods and Results We searched Embase, MEDLINE, Web of Science, Google Scholar, and Tufts' clinical prediction registry through February 2021. Studies needed to report the development, validation, clinical impact, or update of a prediction model for hospitalization for heart failure in type 2 diabetes with measures of model performance and sufficient information for clinical use. Model assessment was done with the Prediction Model Risk of Bias Assessment Tool, and meta-analyses of model discrimination were performed. We included 15 model development and 3 external validation studies with data from 999 167 people with type 2 diabetes. Of the 15 models, 6 had undergone external validation and only 1 had low concern for risk of bias and applicability (Risk Equations for Complications of Type 2 Diabetes). Seven models were presented in a clinically useful manner (eg, risk score, online calculator) and 2 models were classified as the most suitable for clinical use based on study design, external validity, and point-of-care usability. These were Risk Equations for Complications of Type 2 Diabetes (meta-analyzed c-statistic, 0.76) and the Thrombolysis in Myocardial Infarction Risk Score for Heart Failure in Diabetes (meta-analyzed c-statistic, 0.78), which was the simplest model with only 5 variables. No studies reported clinical impact. Conclusions Most prediction models for hospitalization for heart failure in patients with type 2 diabetes have potential concerns with risk of bias or applicability, and uncertain external validity and clinical impact. Future research is needed to address these knowledge gaps.

NT-proBNP as a predictor of death and cardiovascular events in patients with type 2 diabetes

Existing risk prediction scores based on clinical and laboratory variables have been considered inaccurate in patients with Type 2 Diabetes Mellitus (T2DM). Circulating concentrations of natriuretic peptides have been used to aid in the diagnosis and to predict outcomes in heart failure. However, there is a growing body of evidence for the use of natriuretic peptides measurements, mainly N-terminal pro-B-type natriuretic peptide (NT-proBNP), as a tool in risk stratification for individuals with T2DM. Studies have demonstrated the ability of NT-proBNP to improve outcomes prediction when incorporated into multivariate models. More recently, evidence has emerged of the discriminatory power of NT-proBNP, demonstrating, as a single variable, a similar and even superior ability to multivariate risk models for the prediction of death and cardiovascular events in individuals with T2DM. Natriuretic peptides are synthesized and released from the myocardium as a counter-regulatory response to increased cardiac wall stress, sympathetic tone, and vasoconstriction, acting on various systems and affecting different biological processes. In this article, we present a review of the accumulated knowledge about these biomarkers, underscoring the strength of the evidence of their predictive ability for fatal and non-fatal outcomes. It is likely that, by influencing the functioning of many organs, these biomarkers integrate information from different systems. Although not yet recommended by guidelines, measurement of natriuretic peptides, and particularly NT-proBNP, should be strongly considered in the risk stratification of individuals with T2DM.

Risk Estimates of Imminent Cardiovascular Death and Heart Failure Hospitalization Are Improved Using Serial Natriuretic Peptide Measurements in Patients With Coronary Artery Disease and Type 2 Diabetes

Background

Baseline and temporal changes in natriuretic peptide (NP) concentrations have strong prognostic value with regard to long‐term cardiovascular risk stratification. To increase the clinical utility of NP sampling for patient management, we wanted to assess the incremental predictive value of 2 serial NP measurements compared with a single measurement and provide absolute risk estimates for cardiovascular death or heart failure hospitalization (HFH) within 6 months based on 2 serial NP measurements.

Methods and Results

Consecutive NP samples obtained from 5393 patients with a recent coronary event and type 2 diabetes enrolled in the ELIXA (Evaluation of Cardiovascular Outcomes in Patients With Type 2 Diabetes After Acute Coronary Syndrome During Treatment With Lixisenatide) trial were used to construct best logistic regression models with outcome of cardiovascular death or HFH (136 events). Absolute risk estimates of cardiovascular death or HFH within 6 months using either BNP (B‐type natriuretic peptide) or NT‐proBNP (N‐terminal pro‐BNP) serial measurements were depicted based on the concentrations of 2 serial NP measurements. During the 6‐month follow‐up periods, the incidence rate (±95% CIs) of cardiovascular death or HFH for patients was 14.0 (11.8‒16.6) per 1000 patient‐years. Risk prediction depended on NP concentrations from both prior and current sampling. NP sampling 6 months apart improved the predictive value and reclassification of patients compared with a single sample (AUROC [Area Under the Receiver Operating Characteristic curve]: BNP, P=0.003. NT‐proBNP, P<0.0001), with a majority of moderate‐risk patients (6‐month risk between 1% and 10%) being reclassified on the basis of the second NP sample.

Conclusions

Serial NP measurements improved prediction of imminent cardiovascular death or HFH in patients with coronary artery disease and type 2 diabetes. The absolute risk estimates provided may aid clinicians in decision‐making and help patients understand their short‐term risk profile.

SGLT2 inhibitor dapagliflozin prevents atherosclerotic and cardiac complications in experimental type 1 diabetes

Introduction

Cardiovascular disease (CVD) is two to five times more prevalent in diabetic patients and is the leading cause of death. Therefore, identification of novel therapeutic strategies that reduce the risk of CVD is a research priority. Clinical trials showed that reduction in the relative risk of heart failure by sodium-glucose cotransporter 2 inhibitors (SGLT2i) are partly beyond their glucose lowering effects, however, the molecular mechanisms are still elusive. Here we investigated the role of SGLT2i dapagliflozin (DAPA) in the prevention of diabetes-induced cardiovascular complications.

Methods

Type 1 diabetes was induced with streptozotocin (65 mg/bwkg, ip.) in adult, male Wistar rats. Following the onset of diabetes rats were treated for six weeks with DAPA (1 mg/bwkg/day, po.).

Results

DAPA decreased blood glucose levels (D: 37±2.7 vs. D+DAPA: 18±5.6 mmol/L; p<0.05) and prevented metabolic decline. Aortic intima-media thickening was mitigated by DAPA. DAPA abolished cardiac hypertrophy, and myocardial damage. Cardiac inflammation and fibrosis were also moderated after DAPA treatment.

Conclusions

These data support the preventive and protective role of SGLT2i in diabetes-associated cardiovascular disease. SGLT2i may provide novel therapeutic strategy to hinder the development of cardiovascular diseases in type 1 diabetes, thereby improve the outcomes.

Biomarkers as MEDiators of racial disparities in risk factors (BioMedioR): Rationale, study design, and statistical considerations

PURPOSE

Relative to White adults, Black adults have a substantially higher prevalence of hypertension and diabetes, both key risk factors for stroke, cardiovascular disease, cognitive impairment, and dementia. Blood biomarkers have shown promise in identifying contributors to racial disparities in many chronic diseases.

METHODS

We outline the study design and related statistical considerations for a nested cohort study, the Biomarker Mediators of Racial Disparities in Risk Factors (BioMedioR) study, within the 30,239-person biracial REasons for Geographic And Racial Differences in Stroke (REGARDS) study (2003-present). Selected biomarkers will be assessed for contributions to racial disparities in risk factor development over median 9.4 years of follow-up, with initial focus on hypertension, and diabetes. Here we outline study design decisions and statistical considerations for the sampling of 4,400 BioMedioR participants.

RESULTS

The population for biomarker assessment was selected using a random sample study design balanced across race and sex to provide the optimal opportunity to describe association of biomarkers with the development of hypertension and diabetes. Descriptive characteristics of the BioMedioR sample and analytic plans are provided for this nested cohort study.

CONCLUSIONS

This nested biomarker study will examine pathways with the target to help explain racial differences in hypertension and diabetes incidence.

Involvement of Ceramides in Non-Alcoholic Fatty Liver Disease (NAFLD) Atherosclerosis (ATS) Development: Mechanisms and Therapeutic Targets

Non-alcoholic fatty liver disease (NAFLD) and atherosclerosis (ATS) are worldwide known diseases with increased incidence and prevalence. These two are driven and are interconnected by multiple oxidative and metabolic functions such as lipotoxicity. A gamut of evidence suggests that sphingolipids (SL), such as ceramides, account for much of the tissue damage. Although in humans they are proving to be accurate biomarkers of adverse cardiovascular disease outcomes and NAFLD progression, in rodents, pharmacological inhibition or depletion of enzymes driving de novo ceramide synthesis prevents the development of metabolic driven diseases such as diabetes, ATS, and hepatic steatosis. In this narrative review, we discuss the pathways which generate the ceramide synthesis, the potential use of circulating ceramides as novel biomarkers in the development and progression of ATS and related diseases, and their potential use as therapeutic targets in NAFDL-ATS development which can further provide new clues in this field.

Plasma biomarkers outperform echocardiographic measurements for cardiovascular risk prediction in kidney transplant recipients: results of the HOME ALONE study

Background

Since kidney transplant recipients (KTRs) have a high cardiovascular disease burden, adequate risk prediction is of importance. Whether echocardiographic parameters and plasma biomarkers, natriuretic peptides [N-terminal pro-B-type natriuretic peptide (NT-proBNP)] and troponin T provide complementary or overlapping prognostic information on cardiovascular events remains uncertain.

Methods

The prospective Heterogeneity of Monocytes and Echocardiography Among Allograft Recipients in Nephrology (HOME ALONE) study followed 177 KTRs for 5.4 ± 1.7 years. Predefined endpoints were hospitalization for acute decompensated heart failure or all-cause death (HF/D) and major atherosclerotic cardiovascular events or all-cause death (MACE/D). At baseline, plasma NT-proBNP, plasma troponin T and echocardiographic parameters [left atrial volume index, left ventricular (LV) mass index, LV ejection fraction, and LV filling pressure] were assessed.

Results

Among all echocardiographic and plasma biomarkers measured, only NT-proBNP was consistently associated with HF/D in univariate and multivariate {third versus first tertile: hazard ratio [HR] 4.20 [95% confidence interval (CI) 1.02–17.27]} analysis, and only troponin T was consistently associated with MACE/D in univariate and multivariate [third versus first tertile: HR 8.15 (95% CI 2.75–24.18)] analysis.

Conclusion

Our data suggest that plasma biomarkers are robust and independent predictors of heart failure and atherosclerotic cardiovascular events after kidney transplantation, whereas standard echocardiographic follow-up does not add to risk prediction.

Prognostic Significance of Preprocedural N-Terminal Pro-B-Type Natriuretic Peptide Assessment in Diabetic Patients With Multivessel Coronary Disease Undergoing Revascularization

Background and Aims: The N-terminal pro-B-type natriuretic peptide (NT-proBNP) may predict adverse cardiovascular outcomes in patients with diabetes. However, its prognostic value in patients with multivessel disease (MVD) undergoing coronary revascularization remains unclear. This study aimed to evaluate the prognostic significance of preprocedural NT-proBNP levels in diabetic patients with MVD undergoing coronary revascularization.

Methods: A total of 886 consecutive diabetic patients with MVD who underwent coronary revascularization were enrolled in this study. Patients were divided into quartiles according to their pre-procedural NT-proBNP levels. Kaplan-Meier curves and Cox regression analyses were performed to evaluate the risk of cardiovascular events, including all-cause death, cardiovascular death, myocardial infarction (MI), stroke, and major adverse cardiovascular events (MACE), according to the NT-proBNP quartiles.

Results: During a median follow-up period of 4.2 years, 111 patients died (with 82 being caused by cardiovascular disease), 133 had MI, 55 suffered from stroke, and 250 experienced MACE. Kaplan-Meier curves demonstrated that NT-proBNP levels were significantly associated with higher incidences of all-cause death, cardiovascular death, MI, and MACE (log-rank test, P < 0.001, respectively). Multivariate Cox regression analysis revealed that NT-proBNP level was an independent predictor of adverse outcomes, including all-cause death (HR, 1.968; 95% CI, 1.377–2.812; P < 0.001), cardiovascular death (HR, 1.940; 95% CI, 1.278–2.945; P = 0.002), MI (HR, 1.722; 95% CI, 1.247–2.380; P = 0.001), and MACE (HR, 1.356; 95% CI, 1.066–1.725; P = 0.013). The role of NT-proBNP in predicting adverse outcomes was similar in patients with stable angina pectoris and acute coronary syndrome. Moreover, preprocedural NT-proBNP alone discriminated against the SYNTAX II score for predicting all-cause death [area under the curve (AUC), 0.662 vs. 0.626, P = 0.269], cardiovascular death (AUC, 0.680 vs. 0.622, P = 0.130), MI (AUC, 0.641 vs. 0.579, P = 0.050), and MACE (AUC, 0.593 vs. 0.559, P = 0.171). The addition of NT-proBNP to the SYNTAX II score showed a significant net reclassification improvement, integrated discrimination improvement, and improved C-statistic (all P < 0.05).

Conclusion: NT-proBNP levels were an independent prognostic marker for adverse outcomes in diabetic patients with MVD undergoing coronary revascularization, suggesting that preprocedural NT-proBNP measurement might help in the risk stratification of high-risk patients.

Circulating Biomarkers for Cardiovascular Disease Risk Prediction in Patients With Cardiovascular Disease

Cardiovascular disease (CVD) is the leading cause of death globally. Risk assessment is crucial for identifying at-risk individuals who require immediate attention as well as to guide the intensity of medical therapy to reduce subsequent risk of CVD. In the past decade, many risk prediction models have been proposed to estimate the risk of developing CVD. However, in patients with a history of CVD, the current models that based on traditional risk factors provide limited power in predicting recurrent cardiovascular events. Several biomarkers from different pathophysiological pathways have been identified to predict cardiovascular events, and the incorporation of biomarkers into risk assessment may contribute to enhance risk stratification in secondary prevention. This review focuses on biomarkers related to cardiovascular and metabolic diseases, including B-type natriuretic peptide, high-sensitivity cardiac troponin I, adiponectin, adipocyte fatty acid-binding protein, heart-type fatty acid-binding protein, lipocalin-2, fibroblast growth factor 19 and 21, retinol-binding protein 4, plasminogen activator inhibitor-1, 25-hydroxyvitamin D, and proprotein convertase subtilisin/kexin type 9, and discusses the potential utility of these biomarkers in cardiovascular risk prediction among patients with CVD. Many of these biomarkers have shown promise in improving risk prediction of CVD. Further research is needed to assess the validity of biomarker and whether the strategy for incorporating biomarker into clinical practice may help to optimize decision-making and therapeutic management.

Mirror mirror on the wall, who is going to be readmitted after all?

In the jungle of biomarkers that predicts long-term outcome, there are many discrepancies and there is more evidence from single-center retrospective studies rather than clinical trials. While some of these biomarkers such as high sensitivity troponin levels, creatine kinase (CK), and CK-MB have demonstrated a good pattern for patients' follow-up, other biomarkers are still struggling to get validated and internationally renown due to the small number of patients included in the studies and their retrospective nature. In this context, Brown and colleagues must be congratulated as they have marked the pathway for future clinical trials.

NT-proBNP versus routine clinical risk factors as a predictor of cardiovascular events or death in people with dysglycemia - A brief report from the ORIGIN trial

In patients with diabetes and cardiovascular or renal comorbidities, circulating levels of the N-terminal fragment of prohormone B-type natriuretic peptide (NT-proBNP) have similar discriminatory ability as multivariate models for prediction of cardiovascular events or death. We validated this finding in patients with dysglycemia not selected for co-existing cardiorenal diseases.

Heart Failure and Diabetes Mellitus: Biomarkers in Risk Stratification and Prognostication

Heart failure (HF) and type 2 diabetes mellitus (T2DM) have a synergistic effect on cardiovascular (CV) morbidity and mortality in patients with established CV disease (CVD). The aim of this review is to summarize the knowledge regarding the discriminative abilities of conventional and novel biomarkers in T2DM patients with established HF or at higher risk of developing HF. While conventional biomarkers, such as natriuretic peptides and high-sensitivity troponins demonstrate high predictive ability in HF with reduced ejection fraction (HFrEF), this is not the case for HF with preserved ejection fraction (HFpEF). HFpEF is a heterogeneous disease with a high variability of CVD and conventional risk factors including T2DM, hypertension, renal disease, older age, and female sex; therefore, the extrapolation of predictive abilities of traditional biomarkers on this population is constrained. New biomarker-based approaches are disputed to be sufficient for improving risk stratification and the prediction of poor clinical outcomes in patients with HFpEF. Novel biomarkers of biomechanical stress, fibrosis, inflammation, oxidative stress, and collagen turn-over have shown potential benefits in determining prognosis in T2DM patients with HF regardless of natriuretic peptides, but their role in point-to-care and in routine practice requires elucidation in large clinical trials.

Prognostic value of NT-proBNP in patients with chronic coronary syndrome and normal left ventricular systolic function according to glucose status: a prospective cohort study

Background

The prognostic value of N-terminal pro-brain natriuretic peptide (NT-proBNP) in patients with coronary artery disease (CAD) with different glucose status has not been established. This study sought to evaluate the significance of NT-proBNP in predicting major adverse cardiovascular events (MACEs) in patients with chronic coronary syndrome (CCS) and normal left-ventricular systolic function (LVSF) according to different glucose status, especially in those with abnormal glucose metabolism.

Methods

A total of 8062 patients with CCS and normal LVSF were consecutively enrolled in this prospective study. Baseline plasma NT-proBNP levels were measured. The follow-up data of all patients were collected. Kaplan-Meier and Cox regression analyses were used to assess the risk of MACEs according to NT-proBNP tertiles stratified by glucose status.

Results

Over an average follow-up of 59.13 ± 18.23 months, 569 patients (7.1 %) suffered from MACEs, including cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke. Kaplan-Meier analysis showed that high NT-proBNP levels had a significant association with MACEs in subjects with prediabetes mellitus (pre-DM) or DM, but not in patients with normoglycemia. Multivariate Cox regression analysis revealed that NT-proBNP remained an independent predictor of MACEs in patients with pre-DM [hazard ratio (HR): 2.56, 95% confidence interval (CI): 1.34–4.91] or DM (HR: 2.34, 95% CI: 1.32–4.16). Moreover, adding NT-proBNP to the original Cox model including traditional risk factors significantly increased the C-statistic by 0.035 in pre-DM and DM, respectively.

Conclusions

The present study indicated that NT-proBNP could well predict worse outcomes in dysglycemic patients with CCS and normal LVSF, suggesting that NT-proBNP may help with risk stratification in this population.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-021-01271-0.

Promising Novel Biomarkers in Cardiovascular Diseases

Cardiovascular diseases remain the most common causes of death globally, according to the World Health Organization. In recent years, a great number of biomarkers have been investigated, whereas only some have gained value in the diagnosis, prognosis, and risk stratification of different cardiovascular illnesses. As numerous studies have investigated the diagnostic yield of novel biomarkers in various disease entities every year, this review aims to provide an overview of the current status of four promising representatives. In particular, this manuscript refers to soluble suppression of tumorigenicity 2 (sST2), heart-type fatty acid binding protein (H-FABP), growth differentiation factor (GDF-15) and soluble urokinase-type plasminogen activator receptor (suPAR). These markers are of special interest as they are thought to provide an accurate estimate of cardiovascular risk in certain patient populations, especially those with pre-existing diseases, such as obesity or diabetes mellitus. We sought to give an overview of their function, individual diagnostic and predictive value and determination in the laboratory. A review of the literature regarding the aforementioned cardiovascular biomarkers yielded manifold results with respect to their individual diagnostic and prognostic value. Yet, the clinical relevance of these findings remains unclear, warranting further studies to identify their optimal use in clinical routine.

Induced bioresistance via BNP detection for machine learning-based risk assessment

Machine Learning (ML) is a powerful tool for big data analysis that shows substantial potential in the field of healthcare. Individual patient data can be inundative, but its value can be extracted by ML's predictive power and ability to find trends. A great area of interest is early diagnosis and disease management strategies for cardiovascular disease (CVD), the leading cause of death in the world. Treatment is often inhibited by analysis delays, but rapid testing and determination can help improve frequency for real time monitoring. In this research, an ML algorithm was developed in conjunction with a flexible BNP sensor to create a quick diagnostic tool. The sensor was fabricated as an ion-selective field effect transistor (ISFET) in order to be able to quickly gather large amounts of electrical data from a sample. Artifical samples were tested to characterize the sensors using linear sweep voltammetry, and the resulting data was utilized as the initial training set for the ML algorithm, an implementation of quadratic discriminant analysis (QDA) written in MATLAB. Human blood serum samples from 30 University of Pittsburgh Medical Center (UPMC) patients were tested to evaluate the effective sorting power of the algorithm, yielding 95% power in addition to ultra fast data collection and determination.

Involvement of the BNP/NPR-A/BKCa pathway in rat trigeminal ganglia following chronic constriction injury

Accumulating evidence indicates that the brain natriuretic peptide (BNP) and its receptor (natriuretic peptide receptor, NPR) are widely distributed in a variety of tissues including trigeminal ganglion (TG). Furthermore, recent studies support the involvement of the BNP-NPR-A pathway in acute and chronic pain. To investigate the role of this pathway in chronic pain, an infraorbital nerve-chronic constriction injury (ION-CCI) model of trigeminal neuralgia (TN) was produced in the rat. The time course of changes in mechanical pain threshold was examined. We observed an upregulation of BNP and NPR-A and a downregulation of large-conductance Ca²⁺-activated K⁺ (BKCa) mRNA and protein in rats subjected to ION-CCI. Patch clamping experiments in vitro found that BKCa currents were significantly reduced in rats subjected to ION-CCI. BNP increased BKCa currents in ION-CCI rats. These results suggest that BNP and NPR-A might serve as endogenous pain relievers in ION-CCI rats. Modulation of the BNP/NPR-A/BKCa channel pathway in TG may be a viable strategy for the treatment of TN.NEW & NOTEWORTHY BNP has been known to activate its receptor, NPR-A, to modulate inflammatory pain. However, the potential modulatory roles of BNP in TN have not been investigated in detail. We established an ION-CCI model of TN in the rat and observed an upregulation of BNP and NPR-A and a downregulation of BKCa in rats subjected to ION-CCI. Moreover, BNP can increase BKCa currents in ION-CCI rats. Thus, BNP and NPR-A might have inhibitory effects on trigeminal neuralgia through activating the BNP/NPR-A/BKCa channel pathway.

Performance of the recommended ESC/EASD cardiovascular risk stratification model in comparison to SCORE and NT-proBNP as a single biomarker for risk prediction in type 2 diabetes mellitus

BACKGROUND

Recently, the European Society of Cardiology (ESC) and European Association for the Society of Diabetes (EASD) introduced a new cardiovascular disease (CVD) risk stratification model to aid further treatment decisions in individuals with diabetes. Our study aimed to investigate the prognostic performance of the ESC/EASD risk model in comparison to the Systematic COronary Risk Evaluation (SCORE) risk model and N-terminal pro-B-type natriuretic peptide (NT-proBNP) in an unselected cohort of type 2 diabetes mellitus (T2DM).

METHODS AND RESULTS

A total of 1690 T2DM patients with a 10-year follow up for fatal CVD and all-cause death and a 5-year follow up for CVD and all-cause hospitalizations were analyzed. According to ESC/EASD risk criteria 25 (1.5%) patients were classified as moderate, 252 (14.9%) high, 1125 (66.6%) very high risk and 288 (17.0%) were not classifiable. Both NT-proBNP and SCORE risk model were associated with 10-year CVD and all-cause death and 5-year CVD and all-cause hospitalizations while the ESC/EASD model was only associated with 10-year all-cause death and 5-year all-cause hospitalizations. NT-proBNP and SCORE showed significantly higher C-indices than the ESC/EASD risk model for CVD death [0.80 vs. 0.53, p < 0.001; 0.64 vs. 0.53, p = 0.001] and all-cause death [0.73, 0.66 vs. 0.52, p < 0.001 for both]. The performance of SCORE improved in a subgroup without CVD aged 40-64 years compared to the unselected cohort, while NT-proBNP performance was robust across all groups.

CONCLUSION

The new introduced ESC/EASD risk stratification model performed limited compared to SCORE and single NT-proBNP assessment for predicting 10-year CVD and all-cause fatal events in individuals with T2DM.

Combined B-type Natriuretic Peptide as strong predictor of short-term mortality in patients after Liver Transplantation

Background: B-type natriuretic peptide (BNP) is a well-known predictor for prognosis in patients with cardiac and renal diseases. However, there is a lack of studies in patients with advanced hepatic disease, especially patients who underwent liver transplantation (LT). We evaluated whether BNP could predict the prognosis of patients who underwent LT. Material and Methods: The data from a total of 187 patients who underwent LT were collected retrospectively. The serum levels of BNP were acquired at four time points, the pre-anhepatic (T1), anhepatic (T2), and neohepatic phases (T3), and on postoperative day 1 (T4). The patients were dichotomized into survival and non-survival groups for 1-month mortality after LT. Combined BNP (cBNP) was calculated based on conditional logistic regression analysis of pairwise serum BNP measurements at two time points, T2 and T4. The area under the receiver operating characteristic curve (AUROC) was analyzed to determine the diagnostic accuracy and cut-off value of the predictive models, including cBNP. Results: Fourteen patients (7.5 %) expired within one month after LT. The leading cause of death was sepsis (N = 9, 64.3 %). The MELD and MELD-Na scores had an acceptable predictive ability for 1-month mortality (AUROC = 0.714, and 0.690, respectively). The BNPs at each time point (T1 - T4) showed excellent predictive ability (AUROC = 0.864, 0.962, 0.913, and 0.963, respectively). The cBNP value had an outstanding predictive ability for 1-month mortality after LT (AUROC = 0.976). The optimal cutoff values for cBNP at T2 and T4 were 137 and 187, respectively. Conclusions: The cBNP model showed the improved predictive ability for mortality within 1-month of LT. It could help clinicians stratify mortality risk and be a useful biomarker in patients undergoing LT.

Association of the Serum Osteoprotegerin Level With Target Organ Damage in Patients at High Risk of Coronary Artery Disease

BACKGROUND

There is little data as to whether osteoprotegerin (OPG) is associated with target organ damage (TOD), so we evaluated the association in patients at high risk of coronary artery disease (CAD).Methods and Results:A total of 349 patients who underwent invasive coronary angiography (ICA) for suspected CAD were prospectively recruited. During the index admission, 6 TOD parameters were collected: extent of CAD, glomerular filtration rate (GFR), left ventricular mass index (LVMI), E/e', brachial-ankle pulse wave velocity (baPWV), and ankle-brachial index (ABI). Serum OPG levels were measured using enzyme-linked immunosorbent assay. The OPG level was significantly higher in patients with ≥1 TOD parameter than in those without (314±186 vs. 202±74 pg/mL, P<0.001). For each TOD parameter, the serum OPG level was significantly higher in patients with TOD than in those without (P<0.05 for each) except for ABI. In correlation analysis, OPG was significantly associated with GFR, LVMI, E/e', baPWV and ABI (P<0.05 for each). The OPG concentration increased proportionally with increasing TOD (P<0.001). Higher OPG concentrations (≥198 pg/mL) was significantly associated with the presence of TOD (odds ratio 3.22; 95% confidence interval 1.51-6.85; P=0.002) even after controlling for potential confounders.

CONCLUSIONS

Serum OPG level was significantly associated with a variety of TOD in patients undergoing ICA. OPG may be a useful marker for TOD and in the risk stratification of patients at high risk of CAD.

Blood pressure and mortality in patients with type 2 diabetes and a recent coronary event in the ELIXA trial

BACKGROUND

The relationship between blood pressure and mortality in type 2 diabetes (T2DM) is controversial, with concern for increased risk associated with excessively lowered blood pressure.

METHODS

We evaluated whether prior cardiovascular disease (CVD) altered the relationship between baseline blood pressure and all-cause mortality in 5852 patients with T2DM and a recent acute coronary syndrome (ACS) who participated in the ELIXA (Evaluation of Lixisenatide in Acute Coronary Syndrome) trial. Risk of death was assessed in Cox models adjusted for age, sex, race, heart rate, BMI, smoking, diabetes duration, insulin use, HbA1c, eGFR, brain natriuretic peptide (BNP), urine albumin/creatinine ratio, treatment allocation and prior coronary revascularization.

RESULTS

Although overall there was no significant association between systolic blood pressure (SBP) and mortality (hazard ratio per 10 mmHg lower SBP 1.05 (95% CI 0.99-1.12) P = 0.10), lower SBP was significantly associated with higher risk of death (hazard ratio per 10 mmHg lower SBP 1.13 (95% CI 1.04-1.22) P = 0.002) in 2325 patients with additional CVD (index ACS+ at least one of the following prior to randomization: myocardial infarction other than the index ACS, stroke or heart failure). In 3527 patients with only the index ACS no significant association was observed (hazard ratio per 10 mmHg lower SBP 0.95 (0.86-1.04) P = 0.26; P for interaction 0.005).

CONCLUSIONS

The association between blood pressure and mortality was modified by additional CVD history in patients with type 2 diabetes and a recent coronary event. When blood pressures measured after an acute coronary event are used to assess the risk of death in patients with type 2 diabetes, the cardiovascular history needs to be taken into consideration. Trial registration ClinicalTrials.gov number NCT01147250, first posted June 22, 2010.

Prognostic Impact of B-Type Natriuretic Peptide on Long-Term Clinical Outcomes in Patients with Non-ST-Segment Elevation Acute Myocardial Infarction Without Creatine Kinase Elevation

Although B-type natriuretic peptide (BNP) has gradually gained recognition as an indicator in risk stratification for patients with acute myocardial infarction (AMI), the prognostic impact on long-term clinical outcomes in patients with non-ST-segment elevation acute myocardial infarction (NSTEMI) without creatine kinase (CK) elevation remains unclear.This prospective multicenter study assessed 3,283 consecutive patients with AMI admitted to 28 institutions in Japan between 2012 and 2014. We analyzed 218 patients with NSTEMI without CK elevation (NSTEMI-CK) for whom BNP was available. In the NSTEMI-CK group, patients were assigned to high- and low-BNP groups according to BNP values (cut-off BNP, 100 pg/mL). The primary endpoint was defined as a composite of all-cause death, non-fatal myocardial infarction, non-fatal stroke, cardiac failure, and urgent revascularization for unstable angina up to 3 years. Primary endpoints were observed in 60 (33.3%) events among patients with NSTEMI-CK. Kaplan-Meier analysis revealed a significantly higher event rate for primary endpoints among patients with high BNP (log-rank P < 0.001). After adjusting for covariates, a higher BNP level was significantly associated with long-term clinical outcomes in NSTEMI-CK (adjusted hazard ratio, 4.86; 95% confidence interval, 2.18-12.44; P < 0.001).The BNP concentration is associated with adverse long-term clinical outcomes among patients with NSTEMI-CK who are considered low risk. Careful clinical management may be warranted for secondary prevention in patients with NSTEMI-CK with high BNP levels.

NT-proBNP by Itself Predicts Death and Cardiovascular Events in High-Risk Patients With Type 2 Diabetes Mellitus

Background NT-proBNP (N-terminal pro-B-type natriuretic peptide) improves the discriminatory ability of risk-prediction models in type 2 diabetes mellitus (T2DM) but is not yet used in clinical practice. We assessed the discriminatory strength of NT-proBNP by itself for death and cardiovascular events in high-risk patients with T2DM. Methods and Results Cox proportional hazards were used to create a base model formed by 20 variables. The discriminatory ability of the base model was compared with that of NT-proBNP alone and with NT-proBNP added, using C-statistics. We studied 5509 patients (with complete data) of 8561 patients with T2DM and cardiovascular and/or chronic kidney disease who were enrolled in the ALTITUDE (Aliskiren in Type 2 Diabetes Using Cardiorenal Endpoints) trial. During a median 2.6-year follow-up period, 469 patients died and 768 had a cardiovascular composite outcome (cardiovascular death, resuscitated cardiac arrest, nonfatal myocardial infarction, stroke, or heart failure hospitalization). NT-proBNP alone was as discriminatory as the base model for predicting death (C-statistic, 0.745 versus 0.744, P=0.95) and the cardiovascular composite outcome (C-statistic, 0.723 versus 0.731, P=0.37). When NT-proBNP was added, it increased the predictive ability of the base model for death (C-statistic, 0.779 versus 0.744, P<0.001) and for cardiovascular composite outcome (C-statistic, 0.763 versus 0.731, P<0.001). Conclusions In high-risk patients with T2DM, NT-proBNP by itself demonstrated discriminatory ability similar to a multivariable model in predicting both death and cardiovascular events and should be considered for risk stratification. Registration URL: https://www.clini​caltr​ials.gov; Unique identifier: NCT00549757.

Prediction of the long-term risk of adverse cardiovascular events after an episode of acute coronary syndrome in patients with type 2 diabetes

Aim. To determine independent predictors of adverse cardiovascular events (ACE) and to develop a long-term (12 months) prognostic model after an episode of acute coronary syndrome (ACS) in patients with type 2 diabetes (T2D).

Material and methods. The study included 120 T2D patients hospitalized due to ACS in the period from January 2016 to February 2017. All patients underwent standard diagnostic tests. Twelve months after ACS, the incidence of ACE in T2D patients was assessed: cardiovascular mortality, myocardial infarction, emergency surgical revascularization. Additionally, we analyzed composite endpoint (CEP), including all of the adverse outcomes listed. Patients were divided into 2 groups: group 1 (n=34) — patients with ACE; group 2 (n=86) — patients without ACE. Factors associated with the CEP were then included in the logistic regression to determine independent predictors of ACE. In order to predict the development of CEP in patients with ACS and T2D, a logit model was created. To process the model, a ROC analysis was performed.

Results. Independent factors associated with ACE for 12 months in T2D patients after an ACS were established: MI of moderate severity (D.M. Aronov classification); hypertriglyceridemia; decreased heart rate variability (SDNN <0 ms); segments with significant coronary stenosis in the amount of ≥3; no surgical revascularization during acute MI. Based on independent factors, a logit model was developed for assessing 12-month risk of ACE in T2D patients after an ACS.

Conclusion. The developed risk prediction model for T2D patients after ACS, based on accessible diagnostic tests, allows to determine the probability of ACE within 12 months.

Cardiac Biomarkers in Patients with Cancer: Considerations, Clinical Implications, and Future Avenues

PURPOSE OF THE REVIEW

As the number of cancer survivors increases due to early screening and modern (antineoplastic) treatments, cancer treatment associated cardiotoxicity (CTAC) is becoming an increasing health burden that affects survival and quality of life among cancer survivors. Thus, clinicians need to identify adverse events early, in an effort to take suitable measures before the occurrence of permanent or irreversible cardiac dysfunction.

RECENT FINDINGS

Cardiac troponin (cTn) and B-type natriuretic peptide (BNP) have been proven to detect subclinical cardiotoxicity during antineoplastic treatment. As such, these cardio-specific biomarkers could predict which patients are at risk of developing CTAC even before the start of therapy. Nevertheless, there are inconsistent data from published studies, and the recommendations regarding the use of these biomarkers and their validity are mostly based on expert consensus opinion. In this review, we summarize available literature that evaluates biomarkers of CTAC, and we encourage strategies that integrate circulating biomarkers and cardiac imaging in identifying cancer patients that are at high risk.

Body Composition Indices and Cardiovascular Risk in Type 2 Diabetes. CV Biomarkers are not Related to Body Composition

Background

This study aims to explore the correlations of body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), waist-to-hip ratio (WHR) and body composition with levels of asymmetric dimethylarginine (ADMA), endothelin 1(ET-1), N-terminal brain natriuretic pro-peptide (NT-proBNP) and calculated cardiovascular risks.

Methods

102 women and 67 men with type 2 diabetes participated. Serum levels of NT-proBNP were measured by electro-hemi-luminescence while ELISA were used for ADMA and ET-1. Cardiovascular risks were calculated using the Framingham Risk Score (FRS), the UKPDS 2.0 and the ADVANCE risk engines. Statistical analysis was performed on an IBM SPSS 19.0.

Results

The BMI outperformed all other indices of obesity (WC, WHtR, WHR), as well as body composition parameters (body fat%, fat mass, fat free mass and total body water) in relation to the estimated risks for coronary heart disease and stroke, based on different calculators. The correlations of the obesity indices with the serum cardiovascular biomarkers were not significant except for BMI and fat mass versus ET-1, and for fat free mass and total body water versus ADMA.

Conclusions

The WC, WHR, WHtR, BF%, FM and FFM apparently do not add significant information related to the levels of cardiovascular biomarkers or the calculated CV-risks.

Impact of EMpagliflozin on cardiac function and biomarkers of heart failure in patients with acute MYocardial infarction-The EMMY trial

BACKGROUND

Sodium glucose cotransporter 2 (SGLT2) inhibitors are established antidiabetic drugs with proven cardiovascular benefit. Although growing evidence suggests beneficial effects on myocardial remodeling, fluid balance and cardiac function, the impact of empagliflozin initiated early after acute myocardial infarction (AMI) has not been investigated yet. Therefore, the impact of EMpagliflozin on cardiac function and biomarkers of heart failure in patients with acute MYocardial infarction (EMMY) trial was designed to investigate the efficacy and safety of empagliflozin in diabetic and non-diabetic patients after severe AMI.

METHODS

Within a multicenter, randomized, double-blind, placebo-controlled, phase 3b trial we will enroll patients with AMI and characteristics suggestive of severe myocardial necrosis are randomized in a 1:1 ratio to empagliflozin (10 mg once daily) or matching placebo. The primary endpoint is the impact of empagliflozin on changes in NT-proBNP within 6 months after AMI. Secondary endpoints include changes in echocardiographic parameters, levels of ketone body concentrations, HbA1c levels and body weight, respectively. Hospitalization rate due to heart failure or other causes, the duration of hospital stay and all-cause mortality will be assessed as exploratory secondary endpoints.

DISCUSSION

The EMMY trial will test empagliflozin in patients with AMI regardless of their diabetic status. The EMMY trial may therefore underpin the concept of SGLT2 inhibition to improve cardiac remodeling, pre-and afterload reduction and cardiac metabolism regardless of its antidiabetic effects. Results will provide the rationale for the conduct of a cardiovascular outcome trial to test the effect of empagliflozin in patients with AMI.

Prediction of major adverse cardiac, cerebrovascular events in patients with diabetes after acute coronary syndrome

BACKGROUND AND OBJECTIVES

The risk of major adverse cardiac and cerebrovascular events following acute coronary syndrome is increased in people with diabetes. Predicting out-of-hospital outcomes upon follow-up remains difficult, and no simple, well-validated tools exist for this population at present. We aim to evaluate several factors in a competing risks model for actionable evaluation of the incidence of major adverse cardiac and cerebrovascular events in diabetic outpatients following acute coronary syndrome.

METHODS

Retrospective analysis of consecutive patients admitted for acute coronary syndrome in two centres. A Fine-Gray competing risks model was adjusted to predict major adverse cardiac and cerebrovascular events and all-cause mortality. A point-based score is presented that is based on this model.

RESULTS

Out of the 1400 patients, there were 783 (55.9%) with at least one major adverse cardiac and cerebrovascular event (417 deaths). Of them, 143 deaths were due to non-major adverse cardiac and cerebrovascular events. Predictive Fine-Gray models show that the 'PG-HACKER' risk factors (gender, age, peripheral arterial disease, left ventricle function, previous congestive heart failure, Killip class and optimal medical therapy) were associated to major adverse cardiac and cerebrovascular events.

CONCLUSION

The PG-HACKER score is a simple and effective tool that is freely available and easily accessible to physicians and patients. The PG-HACKER score can predict major adverse cardiac and cerebrovascular events following acute coronary syndrome in patients with diabetes.

High-sensitivity troponin I and B-type natriuretic peptide biomarkers for prediction of cardiovascular events in patients with coronary artery disease with and without diabetes mellitus

Background

High-sensitivity troponin I (hs-Tnl) and B-type natriuretic peptide (BNP) are promising prognostic markers for coronary artery disease (CAD). This prospective cohort study investigated whether a combination of these cardiac biomarkers with conventional risk factors would add incremental value for the prediction of secondary major adverse cardiovascular events (MACEs) in patients with CAD, with and without type 2 diabetes mellitus (T2DM).

Methods

Baseline plasma level of hs-Tnl and BNP was measured in 2275 Chinese patients with stable CAD. Patients were monitored for new-onset of MACE over a median of 51 months. Cox proportional hazard model and area under the receiver operating characteristic curve (AUC) were used to assess the association of cardiac biomarkers with MACE and their predictive values in relationship with or without T2DM.

Results

During the follow up period 402 (18%) patients experienced a new-onset MACE with hs-Tnl and BNP level significantly higher than in those without MACE. In multivariable analyses, patients with elevated hs-Tnl (hazard ratio, 1.75 [95% CI 1.41–2.17]; P < 0.001) and BNP (hazard ratio, 1.42 [95% CI 1.15–1.75]; P = 0.001) were significantly associated with an increased risk of MACE after adjustment for variables of a risk factor model of age, sex, T2DM and hypertension. The risk factor model had an AUC of 0.64 for MACE prediction. The AUC significantly increased to 0.68 by the addition of hs-Tnl to the risk factor model. Subgroup analyses showed that hs-Tnl and BNP remained significant predictors of MACE in both patients with and without T2DM in multivariable models with higher risk of MACE evident in those without T2DM. Among patients without T2DM, addition of each biomarker yielded greater predictive accuracy than in T2DM patients, with AUC further increased to 0.75 when a combination of hs-Tnl and BNP was added to the risk factor model (age, sex and hypertension).

Conclusions

Elevated hs-Tnl and BNP level are independent predictors of new-onset MACE in CAD patients, irrespective of diabetes status. Among CAD patients without T2DM, a combination of cardiac biomarkers hs-Tnl and BNP yield the greatest predictive value beyond conventional risk factors.

Association of Cyr61-cysteine-rich protein 61 and short-term mortality in patients with acute heart failure and coronary heart disease

Aim: The protein CCN1/CYR61 exerts critical functions in myocardial ischemic injury. We sought to investigate the prognostic value of CCN1 in patients with acute heart failure (AHF) and coronary heart disease (CAD). Methodology: We prospectively enrolled 113 patients with AHF and CAD. Patients were followed for all-cause mortality during a 30-day follow-up. Logistic models were used to estimate the association of CCN1 concentrations with 30-day mortality. Results: In multivariate logistic regression model, CCN1 was a significant predictor of 30-day mortality independent of current markers. Enhanced Feedback for Effective Cardiac Treatment risk score was recommended as one of the selected multivariable risk scores to predict outcome in AHF. CCN1 improved risk stratification for all-cause mortality when added to the Enhanced Feedback for Effective Cardiac Treatment risk scores at 30 days. Conclusion: We found CCN1 is independently associated with 30-day mortality in patients with AHF and CAD.

Cardiovascular Risk Assessment for Noncardiac Surgery: Are We Ready for Biomarkers?

Biomarkers aided perioperative cardiac assessment is a relatively new concept. Cardiac biomarkers with historical significance (aspartate transaminase, dehydrogenase, creatinine kinase and myoglobin) have paved the way for traditional biomarkers (cardiac troponin, C-reactive protein, lipoprotein). Contemporary biomarkers like natriuretic peptides (BNP and ProBNP) are validated risk markers in both acute and chronic cardiac diseases and are showing remarkable promise in predicting serious cardiovascular complications after non-cardiac surgery. This review is intended to provide a critical overview of traditional and contemporary biomarkers for perioperative cardiovascular assessment and management. This review also discusses the potential utility of newer biomarkers like galectin-3, sST-2, GDF-15, TNF-alpha, MiRNAs and many others that can predict inflammation, cardiac remodeling, injury and endogenous stress and need further investigations to establish their clinical utility. Though promising, biomarker led perioperative care is still in infancy and it has not been determined that it can improve clinical outcomes.