Biomarkers for the prediction of heart failure and cardiovascular events in patients with type 2 diabetes: a position statement from the Heart Failure Association of the European Society of Cardiology

Diabetic myocardial disorder. A clinical consensus statement of the Heart Failure Association of the ESC and the ESC Working Group on Myocardial & Pericardial Diseases

The association between type 2 diabetes mellitus (T2DM) and heart failure (HF) has been firmly established; however, the entity of diabetic myocardial disorder (previously called diabetic cardiomyopathy) remains a matter of debate. Diabetic myocardial disorder was originally described as the occurrence of myocardial structural/functional abnormalities associated with T2DM in the absence of coronary heart disease, hypertension and/or obesity. However, supporting evidence has been derived from experimental and small clinical studies. Only a minority of T2DM patients are recognized as having this condition in the absence of contributing factors, thereby limiting its clinical utility. Therefore, this concept is increasingly being viewed along the evolving HF trajectory, where patients with T2DM and asymptomatic structural/functional cardiac abnormalities could be considered as having pre-HF. The importance of recognizing this stage has gained interest due to the potential for current treatments to halt or delay the progression to overt HF in some patients. This document is an expert consensus statement of the Heart Failure Association of the ESC and the ESC Working Group on Myocardial & Pericardial Diseases. It summarizes contemporary understanding of the association between T2DM and HF and discuses current knowledge and uncertainties about diabetic myocardial disorder that deserve future research. It also proposes a new definition, whereby diabetic myocardial disorder is defined as systolic and/or diastolic myocardial dysfunction in the presence of diabetes. Diabetes is rarely exclusively responsible for myocardial dysfunction, but usually acts in association with obesity, arterial hypertension, chronic kidney disease and/or coronary artery disease, causing additive myocardial impairment.

Prioritizing the primary prevention of heart failure: Measuring, modifying and monitoring risk

With the rising incidence of heart failure (HF) and increasing burden of morbidity, mortality, and healthcare expenditures, primary prevention of HF targeting individuals in at-risk HF (Stage A) and pre-HF (Stage B) Stages has become increasingly important with the goal to decrease progression to symptomatic (Stage C) HF. Identification of risk based on traditional risk factors (e.g., cardiovascular health which can be assessed with the American Heart Association's Life's Essential 8 framework), adverse social determinants of health, inherited risk of cardiomyopathies, and identification of risk-enhancing factors, such as patients with viral disease, exposure to cardiotoxic chemotherapy, and history of adverse pregnancy outcomes should be the first step in evaluation for HF risk. Next, use of guideline-endorsed risk prediction tools such as Pooled Cohort Equations to Prevent Heart Failure provide quantification of absolute risk of HF based in traditional risk factors. Risk reduction through counseling on traditional risk factors is a core focus of implementation of prevention and may include the use of novel therapeutics that target specific pathways to reduce risk of HF, such as mineralocorticoid receptor agonists (e.g., fineronone), angiotensin-receptor/neprolysin inhibitors, and sodium glucose co-transporter-2 inhibitors. These interventions may be limited in at-risk populations who experience adverse social determinants and/or individuals who reside in rural areas. Thus, strategies like telemedicine may improve access to preventive care. Gaps in the current knowledge base for risk-based prevention of HF are highlighted to outline future research that may target approaches for risk assessment and risk-based prevention with the use of artificial intelligence, genomics-enhanced strategies, and pragmatic trials to develop a guideline-directed medical therapy approach to reduce risk among individuals with Stage A and Stage B HF.

Abnormal left ventricular systolic reserve function detected by treadmill exercise stress echocardiography in asymptomatic type 2 diabetes

Aims

Subclinical left ventricular (LV) dysfunction may occur in T2DM patients at the early asymptomatic stage, and LV reserve function is a sensitive index to detect subtle LV dysfunction. The purpose of our study is (1) to assess the LV reserve function using treadmill exercise stress echocardiography (ESE) in asymptomatic type 2 diabetes mellitus (T2DM) patients; (2) to explore the link of serum biological parameters and LV reserve function.

Methods

This study included 84 patients with asymptomatic T2DM from September 2021 to July 2022 and 41 sex- and age-matched healthy controls during the corresponding period. All subjects completed treadmill ESE, LV systolic function-related parameters such as global longitudinal strain (GLS) and systolic strain rate (SRs), as well as diastolic function-related parameters such as E wave (E), early diastolic velocity (e'), E/e' ratio, early diastolic SR (SRe), and late diastolic SR (SRa) were compared at rest and immediately after exercise. The difference between LV functional parameters after treadmill exercise and its corresponding resting value was used to compute LV reserve function. In addition, the associations of LV reserve function and serum biological parameters were analyzed.

Results

Patients with T2DM did not significantly vary from the controls in terms of alterations in LV diastolic reserve measures, the changes of LVGLS and SRs (ΔGLS: 2.19 ± 2.72% vs. 4.13 ± 2.79%, P < 0.001 and ΔSRs:0.78 ± 0.33 s-1 vs. 1.02 ± 0.28 s-1, P < 0.001) in the T2DM group were both lower than those in the control group. Glycated hemoglobin (HbA1c), N-terminal pro-brain natriuretic peptide (NTproBNP), waist circumference, and high-sensitive C-reactive protein (hsCRP) were identified as independent predictors of LV systolic reserve by stepwise multiple linear regression analysis.

Conclusion

LV systolic reserve function, as measured by pre- and post-exercise differences in GLS and SRs were significantly impaired in patients with asymptomatic T2DM, whereas diastolic reserve remained normal during exercise and was comparable to that of the control group. This was different from previous findings. High levels of HbA1c, NTproBNP, hsCRP, and increasing waist circumference were independent predictors of LV systolic reserve.

Multimarker Approach as More Reliable Method Than Single Vitamin D in Relationship with Type 2 Diabetes Mellitus in Montenegrin Postmenopausal Women

OBJECTIVE

Previous studies suggested that ethnic differences, sex and obesity could modify the relationship between 25-hydroxyvitamin D [25(OH)D], glycometabolic markers and/or type 2 diabetes mellitus (T2D). We aimed to examine the potential relationship between [25(OH)D] and T2D in postmenopausal women in Montenegro. In addition, we aimed to explore if a set of biomarkers, rather than [25(OH)D] as a single biomarker, could better explain its potential association with T2D.

PATIENTS AND METHODS

A total of 116 postmenopausal, otherwise healthy women and 48 postmenopausal women with T2D were included. Univariable and multivariable binary logistic regression analysis, along with principal component analysis (PCA), were applied to test the associations between examined biomarkers/set of biomarkers with T2D.

RESULTS

Women with T2D had lower serum [25(OH)D] levels than healthy controls (p = 0.024). No independent relationship between [25(OH)D] and T2D was found. PCA extracted three significant factors that were associated with T2D, i.e., age-glycometabolic-related factor (i.e., with positive loadings of age, glucose and insulin; OR = 11.321, p < 0.001), obesity-inflammation- related factor (i.e., with positive loadings of hsCRP and WC, and negative loading of [25(OH)D]; (OR = 2.079, p < 0.001)) and lipid-related factor (i.e., with positive loadings of TG and LDL-c, and negative loading of HDL-c; OR = 1.423, p = 0.044).

CONCLUSIONS

The relationship between [25(OH)D] and T2D is modulated by central obesity (as measured by WC) and inflammation (as measured with hsCRP) in postmenopausal women. Their joint measurement, rather than [25(OH)D] itself, could provide better information for the risk assessment for T2D in postmenopausal women.

Endocan is Related to Increased Cardiovascular Risk in Type 2 Diabetes Mellitus Patients

Aim: Type 2 diabetes mellitus (T2D) patients have an increased risk for cardiovascular disease (CVD). Different algorithms are used for the CVD risk quantification and United Kingdom Prospective Diabetes Study (UKPDS) score was among the most validated. Endocan is a novel endothelial dysfunction marker. The aim was to explore the potential relationship between serum endocan level and UKPDS risk engine score [which enables calculation of the 10-year risk of nonfatal and fatal coronary heart disease (eCHD) and stroke] in T2D patients. Materials and Methods: The study included a cohort of 104 patients with T2D (of them 52.8% men), with median age 66 years and body mass index (BMI) = 30.7 kg/m2. Patients were divided into: low (<15%), moderate (≥15% and <30%), and high-risk UKPDS category (≥30%). Results: In multivariable regression analysis (when adjusted for sex, BMI and/or hip circumference), endocan was the independent predictor for moderate and high estimated risks (nonfatal eCHD, fatal eCHD, and nonfatal stroke risk). In the Model for high nonfatal eCHD [areas under curve (AUC) = 0.895] and high fatal eCHD (AUC = 0.860) endocan indicated good clinical accuracy, and an excellent accuracy in discriminating patients with high risk for nonfatal stroke risk (AUC = 0.945). Conclusion: Endocan was the independent predictor for moderate and high estimated risks (i.e., nonfatal and fatal CHD and nonfatal stroke risk scores) in T2D patients. When included in models with sex and obesity indices endocan demonstrated good clinical accuracy in discriminating T2D patients with high risk for nonfatal and fatal eCHD and nonfatal stroke risk from those patients with low risk.

Cardiorenal Biomarkers, Canagliflozin, and Outcomes in Diabetic Kidney Disease: The CREDENCE Trial

BACKGROUND

People with type 2 diabetes and albuminuria are at an elevated risk for cardiac and renal events. The optimal biomarkers to aid disease prediction and to understand the benefits of sodium-glucose cotransporter-2 inhibition remain unclear.

METHODS

Among 2627 study participants in the CREDENCE trial (Canagliflozin and Renal Events in Diabetes With Established Nephropathy Clinical Evaluation), concentrations of NT-proBNP (N-terminal pro-B-type natriuretic peptide), high-sensitivity cardiac troponin T, growth differentiation factor-15, and IGFBP7 (insulin-like growth factor binding protein 7) were measured. The effect of canagliflozin on biomarker concentrations was evaluated. The prognostic potential of each biomarker on the primary outcome (a composite of end-stage kidney disease [dialysis, transplantation, or a sustained estimated glomerular filtration rate of <15 mL·min-1·1.73 m-2], doubling of the serum creatinine level, or renal death or cardiovascular death) was assessed.

RESULTS

The median (quartiles 1 and 3) concentration of each biomarker was generally elevated: NT-proBNP, 180 ng/L (82, 442 ng/L); high-sensitivity cardiac troponin T, 19 ng/L (12, 29 ng/L); growth differentiation factor-15, 2595 ng/L (1852, 3775 ng/L); and IGFBP7, 121.8 ng/mL (105.4, 141.5 ng/mL). At 1 year, the biomarkers all rose by 6% to 29% in the placebo arm but only by 3% to 10% in the canagliflozin arm (all P<0.01 in multivariable linear mixed-effect models). Baseline concentrations of each biomarker were strongly predictive of cardiac and renal outcomes. When the biomarkers were analyzed together in a multimarker panel, individuals with high risk scores (hazard ratio [HR], 4.01 [95% CI, 2.52-6.35]) and moderate risk scores (HR, 2.39 [95% CI, 1.48-3.87]) showed a higher risk for the primary outcome compared with those with low risk scores. By 1 year, a 50% increase in NT-proBNP (HR, 1.11 [95% CI, 1.08-1.15]), high-sensitivity cardiac troponin T (HR, 1.86 [95% CI, 1.64-2.10]), growth differentiation factor-15 (HR, 1.45 [95% CI, 1.24-1.70]), and IGFBP7 (HR, 3.76 [95% CI, 2.54-5.56]) was associated with risk of the primary outcome.

CONCLUSIONS

Multiple cardiorenal stress biomarkers are strongly prognostic in people with type 2 diabetes and albuminuria. Canagliflozin modestly reduced the longitudinal trajectory of rise in each biomarker. Change in the biomarker level in addition to the baseline level augments the primary outcome prediction.

REGISTRATION

URL: https://www.

CLINICALTRIALS

gov; Unique identifier: NCT02065791.

Biomarkers for the Diagnosis of Heart Failure in People with Diabetes: A Consensus Report from Diabetes Technology Society

Diabetes Technology Society assembled a panel of clinician experts in diabetology, cardiology, clinical chemistry, nephrology, and primary care to review the current evidence on biomarker screening of people with diabetes (PWD) for heart failure (HF), who are, by definition, at risk for HF (Stage A HF). This consensus report reviews features of HF in PWD from the perspectives of 1) epidemiology, 2) classification of stages, 3) pathophysiology, 4) biomarkers for diagnosing, 5) biomarker assays, 6) diagnostic accuracy of biomarkers, 7) benefits of biomarker screening, 8) consensus recommendations for biomarker screening, 9) stratification of Stage B HF, 10) echocardiographic screening, 11) management of Stage A and Stage B HF, and 12) future directions. The Diabetes Technology Society panel recommends 1) biomarker screening with one of two circulating natriuretic peptides (B-type natriuretic peptide or N-terminal prohormone of B-type natriuretic peptide), 2) beginning screening five years following diagnosis of type 1 diabetes (T1D) and at the diagnosis of type 2 diabetes (T2D), 3) beginning routine screening no earlier than at age 30 years for T1D (irrespective of age of diagnosis) and at any age for T2D, 4) screening annually, and 5) testing any time of day. The panel also recommends that an abnormal biomarker test defines asymptomatic preclinical HF (Stage B HF). This diagnosis requires follow-up using transthoracic echocardiography for classification into one of four subcategories of Stage B HF, corresponding to risk of progression to symptomatic clinical HF (Stage C HF). These recommendations will allow identification and management of Stage A and Stage B HF in PWD to prevent progression to Stage C HF or advanced HF (Stage D HF).

Biomarkers and their combination in a prediction of decompensation after an index hospitalization for acute heart failure

Introduction

Heart failure (HF) still remains as one of the most common causes of hospital admission with a high mortality rate.

Aim

To investigate the possible prognostic role of brain natriuretic peptide (BNP), high-sensitivity (hs) cardiac troponin (cTn) I, cystatin C, and cancer antigen 125 (CA125) in the prediction of decompensation after an index hospitalization and to investigate their possible additive prognostic value.

Patients and Methods

Two hundred twenty-two patients hospitalized with acute HF were monitored and followed for 18 months.

Results

BNP at discharge has the highest sensitivity and specificity in the prediction of decompensation. For a cutoff value of 423.3 pg/ml, sensitivity was 64.3% and specificity was 64.5%, with a positive predictive value of 71.6% and an area under the curve (AUC) of 0.69 (P < 0.001). The hazard risk (HR) for decompensation when the discharge BNP was above the cutoff value was 2.18. Cystatin C, at a cutoff value of 1.46 mg/L, had a sensitivity of 57% and specificity of 57.8%, with a positive predictive value of 65.8% and an AUC of 0.59 (P = 0.028). CA125, in the prediction of decompensation in patients with acute heart failure (AHF) and at a cutoff value of 80.5 IU/L, had a sensitivity of 60.5% and specificity of 53.3%, with a positive predictive value of 64.5% and an AUC of 0.59 (P = 0.022). The time till onset of decompensation was significantly shorter in patients with four versus three elevated biomarkers (P = 0.047), with five versus three elevated biomarkers (P = 0.026), and in patients with four versus two elevated biomarkers (P = 0.026). The HR for decompensation in patients with five positive biomarkers was 3.7 (P = 0.001) and in patients with four positive biomarkers was 2.5 (P = 0.014), compared to patients who had fewer positive biomarkers.

Conclusion

BNP, cystatin C, and CA125 are predictors of decompensation, and their combined usage leads to better prediction of new decompensation.

Microbial metabolites in chronic heart failure and its common comorbidities

This study aimed to identify microbial signatures that contribute to the shared etiologies between chronic heart failure (CHF), type 2 diabetes, and chronic kidney disease. The serum levels of 151 microbial metabolites were measured in 260 individuals from the Risk Evaluation and Management of heart failure cohort, and it was found that those metabolites varied by an order of 10⁵ fold. Out of 96 metabolites associated with the three cardiometabolic diseases, most were validated in two geographically independent cohorts. In all three cohorts, 16 metabolites including imidazole propionate (ImP) consistently showed significant differences. Notably, baseline ImP levels were three times higher in the Chinese compared with the Swedish cohorts and increased by 1.1-1.6 fold with each additional CHF comorbidity in the Chinese population. Cellular experiments further supported a causal link between ImP and distinct CHF relevant phenotypes. Additionally, key microbial metabolite-based risk scores were superior in CHF prognosis than the traditional Framingham or Get with the Guidelines-Heart Failure risk scores. Interactive visualization of these specific metabolite-disease links is available on our omics data server (https://omicsdata.org/Apps/REM-HF/).

Meta-Analysis of the Effect of Nursing Intervention on Children with Type 2 Diabetes

Objective

To systematically evaluate the effect of nursing intervention on children with type 2 diabetes.

Methods

The randomized controlled trials (RCTs) on nursing intervention in children with type 2 diabetes in CNKI, VIP, WanFang, Chinese Biomedical Database (CBM), PubMed, The Cochrane Library, Embase, and Science were searched by the computer until July 2022. Two evaluators reviewed the articles, selected the information, and assessed their quality according to the inclusion criteria and exclusion criteria and then carried out meta-analysis with RevMan 5.3.

Results

A total of 5 RCT studies were kept, including 319 patients with type 2 diabetes (≤21 years old), where 162 patients were in the nursing group and 157 patients were in the control group. Meta-analysis revealed that, compared with routine nursing, nursing intervention could effectively control children's fasting blood glucose (FBG) (MD = -1.68, 95% CI (-2.19, -1.17), P < 0.00001), 2 h postprandial blood glucose (2hPG) (MD = -4.01, 95% CI (-4.70, -3.33), P < 0.00001), fasting insulin (FINS) (MD = -7.42, 95% CI (-10.63, -4.20), P < 0.00001), 2 h postprandial insulin (2hINS) (MD = -58.18, 95% CI (-103.24, -13.11), P = 0.01), triglycerides (TG) (MD = -0.41, 95% CI (-0.56, -0.25), P < 0.00001), and systolic blood pressure (SBP) (MD = -8.85, 95% CI (-14.67, -3.03), P = 0.003) and effectively maintain patients' blood glucose at a normal level (MD = -8.85, 95% CI (-14.67, -3.03), P = 0.003), where all the differences were statistically significant.

Conclusion

The existing evidence showed that nursing intervention has a significant effect in controlling normal blood glucose and improving insulin utilization in children with type 2 diabetes, which can effectively improve the therapeutic effect on children.