The Role of N-terminal PRO-Brain Natriuretic Peptide and Echocardiography for Screening Asymptomatic Left Ventricular Dysfunction in a Population at High Risk for Heart Failure. The PROBE-HF Study

Role of Circulating Biomarkers in Diabetic Cardiomyopathy

Type 2 diabetes mellitus (T2DM) is a metabolic disorder that has alarmingly increased in incidence in recent decades. One of the most serious complications of T2DM is diabetic cardiomyopathy (DCM), an often underrecognized yet severe condition that is a leading cause of mortality among diabetic patients. In the early stages of DCM, patients typically show no symptoms and maintain normal systolic and diastolic left ventricle function, making early detection challenging. Currently available clinical markers are often not specific enough to detect the early stage of DCM. Conventional biomarkers of cardiac mechanical stress and injury, such as natriuretic peptides (NPs) and cardiac troponin I (cTnI), have shown limited predictive value for patients with T2DM. NPs have proven efficacy in detecting diastolic dysfunction in diabetic patients when used alongside 2D echocardiography, but their utility as biomarkers is limited to symptomatic individuals. While cTnI is a reliable indicator of general cardiac damage, it is not specific to cardiac injury caused by high glucose levels or T2DM. This underscores the need for research into biomarkers that can enable early diagnosis and management of DCM to reduce mortality rates. Promising novel biomarkers that showed good performance in detecting diastolic dysfunction or heart failure in diabetic patients include galectin-3, ST2, FGF-21, IGFBP-7, GDF-15, and TGF-β. This review summarizes the current understanding of DCM biomarkers, aiming to generate new ideas for the early recognition and treatment of DCM by exploring related pathophysiological mechanisms.

[Laboratory Aspects of Using the Results of NT-Probnp Concentration Immunochemical Determination in the Management of Patients With Heart Failure: Support For Clinical Decision-Making]

The burden of heart failure (HF) has been increasing worldwide in recent decades. Early diagnosis of HF based on the outpatient measurement of natriuretic peptide (NP) concentration will allow timely initiation of the treatment and reducing the incidence of adverse outcomes in HF. Unfortunately, the frequency of NP testing remains low worldwide. At the online expert meeting held on March 15, 2024, the features of the N-terminal pro-brain natriuretic peptide (NT-proBNP) test (Elecsys proBNP by Roche) were discussed along with the interpretation of test results and presentation of results in laboratory reports. The experts addressed the features of the Elecsys proBNP test in patients with suspected HF in various clinical scenarios (chronic and acute HF). The limits of clinical decision for the NT-proBNP test were established depending on the clinical scenario. Changes in the Elecsys proBNP test results depending on the comorbidities were addressed. The experts suggested ways to optimize the format of the Elecsys proBNP test result reports in the Russian Federation, which will accelerate the implementation of the test in clinical practice and optimize the management of HF patients.

Detecting heart stress using NT-proBNP in patients with type 2 diabetes mellitus and hypertension or high-normal blood pressure: a cross-sectional multicentric study

BACKGROUND

We evaluated the prevalence of "heart stress" (HS) based on NT-proBNP cut-points proposed by the 2023 Consensus of the Heart Failure Association (HFA) of the European Society of Cardiology (ESC) in asymptomatic patients with T2DM and hypertension or high-normal blood pressure (BP) eligible for SGLT2 inhibitors (SGLT2i) and/or GLP-1 receptor agonists (GLP1-RA), drugs with proven benefits on reducing the incidence of HF, hospitalizations, cardiovascular events and mortality.

METHODS

A cross-sectional multicentric study was conducted on 192 consecutive outpatients, aged ≥ 55 years, with hypertension or high-normal BP, referred to three diabetology units. NT-proBNP was collected before starting new anti-diabetic therapy. Patients with known HF were excluded, and participants were classified based on the age-adjusted NT-proBNP cut-points.

RESULTS

Mean age: 70.3 ± 7.8 years (67.5% males). Patients with obesity (BMI ≥ 30 Kg/m2): 63.8%. Median NT-proBNP: 96.0 (38.8-213.0) pg/mL. Prevalence of chronic kidney disease (CKD, eGFR < 60 mL/min/1.73m2): 32.1%. Mean arterial BP: 138.5/77.0 ± 15.8/9.9 mmHg. The NT-proBNP values, according to the proposed age-adjusted cut-points, classified 28.6% of patients as "HS likely" (organize elective echocardiography and specialist evaluation), 43.2% as "HS not likely" (a grey area, repeat NT-proBNP at six months) and 28.2% as "very unlikely HS" (repeat NT-proBNP at one year). The presence of CKD and the number of anti-hypertensive drugs, but not glycemic parameters, were independently associated with HS.

CONCLUSIONS

According to NT-proBNP, over a quarter of T2DM patients with hypertension/high-normal BP, among those eligible for SGLT2i and/or GLP1-RA, were already at risk of cardiac damage, even subclinical. Most would receive an indication to echocardiogram and be referred to a specialist, allowing the early implementation of effective strategies to prevent or delay the progression to advanced stages of cardiac disease and overt HF.

Beyond the beat: A pioneering investigation into exercise modalities for alleviating diabetic cardiomyopathy and enhancing cardiac health

Patients with preexisting cardiovascular disease or those at high risk for developing the condition are often offered exercise as a form of therapy. Patients with cancer who are at an increased risk for cardiovascular issues are increasingly encouraged to participate in exercise-based, interdisciplinary programs due to the positive correlation between these interventions and clinical outcomes following myocardial infarction. Diabetic cardiomyopathy (DC) is a cardiac disorder that arises due to disruptions in the homeostasis of individuals with diabetes. One of the primary reasons for mortality in individuals with diabetes is the presence of cardiac structural damage and functional abnormalities, which are the primary pathological features of DC. The aetiology of dilated cardiomyopathy is multifaceted and encompasses a range of processes, including metabolic abnormalities, impaired mitochondrial function, dysregulation of calcium ion homeostasis, excessive cardiomyocyte death, and fibrosis. In recent years, many empirical investigations have demonstrated that exercise training substantially impacts the prevention and management of diabetes. Exercise has been found to positively impact the recovery of diabetes and improve several metabolic problem characteristics associated with DC. One potential benefit of exercise is its ability to increase systolic activity, which can enhance cardiometabolic and facilitate the repair of structural damage to the heart caused by DC, leading to a direct improvement in cardiac health. In contrast, exercise has the potential to indirectly mitigate the pathological progression of DC through its ability to decrease circulating levels of sugar and fat while concurrently enhancing insulin sensitivity. A more comprehensive understanding of the molecular mechanism via exercise facilitates the restoration of DC disease must be understood. Our goal in this review was to provide helpful information and clues for developing new therapeutic techniques for motion alleviation DC by examining the molecular mechanisms involved.

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).

Diagnostic accuracy of natriuretic peptide screening for left ventricular systolic dysfunction in the community: systematic review and meta-analysis

AIMS

Heart failure (HF) is a global health burden and new strategies to achieve timely diagnosis and early intervention are urgently needed. Natriuretic peptide (NP) testing can be used to screen for left ventricular systolic dysfunction (LVSD), but evidence on test performance is mixed, and international HF guidelines differ in their recommendations. Our aim was to summarize the evidence on diagnostic accuracy of NP screening for LVSD in general and high-risk community populations and estimate optimal screening thresholds.

METHODS

We searched relevant databases up to August 2020 for studies with a screened community population of over 100 adults reporting NP performance to diagnose LVSD. Study inclusion, quality assessment, and data extraction were conducted independently and in duplicate. Diagnostic test meta-analysis used hierarchical summary receiver operating characteristic curves to obtain estimates of pooled accuracy to detect LVSD, with optimal thresholds obtained to maximize the sum of sensitivity and specificity.

RESULTS

Twenty-four studies were identified, involving 26 565 participants: eight studies in high-risk populations (at least one cardiovascular risk factor), 12 studies in general populations, and four in both high-risk and general populations combined. For detecting LVSD in screened high-risk populations with N-terminal prohormone brain natriuretic peptide (NT-proBNP), the pooled sensitivity was 0.87 [95% confidence interval (CI) 0.73-0.94] and specificity 0.84 (95% CI 0.55-0.96); for BNP, sensitivity was 0.75 (95% CI 0.65-0.83) and specificity 0.78 (95% CI 0.72-0.84). Heterogeneity between studies was high with variations in positivity threshold. Due to a paucity of high-risk studies that assessed NP performance at multiple thresholds, it was not possible to calculate optimal thresholds for LVSD screening in high-risk populations alone. To provide an indication of where the positivity threshold might lie, the pooled accuracy for LVSD screening in high-risk and general community populations were combined and gave an optimal cut-off of 311 pg/mL [sensitivity 0.74 (95% CI 0.53-0.88), specificity 0.85 (95% CI 0.68-0.93)] for NT-proBNP and 49 pg/mL [sensitivity 0.68 (95% CI 0.45-0.85), specificity 0.81 (0.67-0.90)] for BNP.

CONCLUSIONS

Our findings suggest that in high-risk community populations NP screening may accurately detect LVSD, potentially providing an important opportunity for diagnosis and early intervention. Our study highlights an urgent need for further prospective studies, as well as an individual participant data meta-analysis, to more precisely evaluate diagnostic accuracy and identify optimal screening thresholds in specifically defined community-based populations to inform future guideline recommendations.

Relation of early-stage renal insufficiency and cardiac structure and function in a large population of asymptomatic Asians: a cross-sectional cohort analysis

Background

Few studies have addressed early-stage kidney disease and preclinical cardiac structural and functional abnormalities from a large-scale Asian population. Further, the extent to which measures of myocardial function and whether these associations may vary by testing various formulas of renal insufficiency remains largely unexplored.

Objective

To explore the associations among renal function, proteinuria, and left ventricular (LV) structural and diastolic functional alterations.

Design

A cross-sectional, retrospective cohort study.

Setting

Registered data from a cardiovascular health screening program at MacKay Memorial Hospital from June 2009 to December 2012.

Participants

Asymptomatic individuals.

Measurements

Renal function was evaluated in terms of estimated glomerular filtration rate (eGFR) by both MDRD and CKD-EPI formulas and severity of proteinuria, which were further related to cardiac structure, diastolic function (including LV e' by tissue Doppler), and circulating N-terminal pro-brain natriuretic peptide (NT-proBNP) level.

Results

Among 4942 participants (65.8% men, mean age 49.4 ± 11.2 years), the mean CKD-EPI/MDRD eGFR was 90.6 ± 15.7 and 88.5 ± 16.9 ml/min/1.73m2, respectively. Lower eGFR, estimated either by the MDRD or CKD-EPI method, and higher proteinuria were significantly associated with lower LV e' and higher NT-proBNP (all p<0.05) even after adjusting for clinical covariates. In general, lower eGFR estimated by CKD-EPI and MDRD displayed similar impacts on worsening e' and NT-proBNP, rather than E/e', in multivariate models. Finally, lower LV e' or higher composite diastolic score, rather than E/e', demonstrated remarkable interaction with eGFR level estimated by either CKD-EPI or MDRD on circulating NT-proBNP level (p interaction <0.05).

Limitations

Proteinuria was estimated using a urine dipstick rather than more accurately by the urine protein-to-creatinine ratio. Also, pertaining drug history and clinical hard outcomes were lacking.

Conclusion

Both clinical estimate of renal insufficiency by eGFR or proteinuria, even in a relatively early clinical stage, were tightly linked to impaired cardiac diastolic relaxation and circulating NT-proBNP level. Elevation of NT-proBNP with worsening renal function may be influenced by impaired myocardial relaxation.

Artificial intelligence-enabled electrocardiographic screening for left ventricular systolic dysfunction and mortality risk prediction

Background

Left ventricular systolic dysfunction (LVSD) characterized by a reduced left ventricular ejection fraction (LVEF) is associated with adverse patient outcomes. We aimed to build a deep neural network (DNN)-based model using standard 12-lead electrocardiogram (ECG) to screen for LVSD and stratify patient prognosis.

Methods

This retrospective chart review study was conducted using data from consecutive adults who underwent ECG examinations at Chang Gung Memorial Hospital in Taiwan between October 2007 and December 2019. DNN models were developed to recognize LVSD, defined as LVEF <40%, using original ECG signals or transformed images from 190,359 patients with paired ECG and echocardiogram within 14 days. The 190,359 patients were divided into a training set of 133,225 and a validation set of 57,134. The accuracy of recognizing LVSD and subsequent mortality predictions were tested using ECGs from 190,316 patients with paired data. Of these 190,316 patients, we further selected 49,564 patients with multiple echocardiographic data to predict LVSD incidence. We additionally used data from 1,194,982 patients who underwent ECG only to assess mortality prognostication. External validation was performed using data of 91,425 patients from Tri-Service General Hospital, Taiwan.

Results

The mean age of patients in the testing dataset was 63.7 ± 16.3 years (46.3% women), and 8,216 patients (4.3%) had LVSD. The median follow-up period was 3.9 years (interquartile range 1.5-7.9 years). The area under the receiver-operating characteristic curve (AUROC), sensitivity, and specificity of the signal-based DNN (DNN-signal) to identify LVSD were 0.95, 0.91, and 0.86, respectively. DNN signal-predicted LVSD was associated with age- and sex-adjusted hazard ratios (HRs) of 2.57 (95% confidence interval [CI], 2.53-2.62) for all-cause mortality and 6.09 (5.83-6.37) for cardiovascular mortality. In patients with multiple echocardiograms, a positive DNN prediction in patients with preserved LVEF was associated with an adjusted HR (95% CI) of 8.33 (7.71 to 9.00) for incident LVSD. Signal- and image-based DNNs performed equally well in the primary and additional datasets.

Conclusion

Using DNNs, ECG becomes a low-cost, clinically feasible tool to screen LVSD and facilitate accurate prognostication.

Physicians and Machine-Learning Algorithm Performance in Predicting Left-Ventricular Systolic Dysfunction from a Standard 12-Lead-Electrocardiogram

Early detection of left ventricular systolic dysfunction (LVSD) may prompt early care and improve outcomes for asymptomatic patients. Standard 12-lead ECG may be used to predict LVSD. We aimed to compare the performance of Machine Learning Algorithms (MLA) and physicians in predicting LVSD from a standard 12-lead ECG. By utilizing a dataset of 13,820 pairs of ECGs and echocardiography, a deep residual convolutional neural network was trained for predicting LVSD (ejection fraction (EF) < 50%) from ECG. The ECGs of the test set (n = 850) were assessed for LVSD by the MLA and six physicians. The performance was compared using sensitivity, specificity, and C-statistics. The interobserver agreement between the physicians for the prediction of LVSD was moderate (κ = 0.50), with average sensitivity and specificity of 70%. The C-statistic of the MLA was 0.85. Repeating this analysis with LVSD defined as EF < 35% resulted in an improvement in physicians’ average sensitivity to 84% but their specificity decreased to 57%. The MLA C-statistic was 0.88 with this threshold. We conclude that although MLA outperformed physicians in predicting LVSD from standard ECG, prior to robust implementation of MLA in ECG machines, physicians should be encouraged to use this approach as a simple and readily available aid for LVSD screening.

Real-world performance, long-term efficacy, and absence of bias in the artificial intelligence enhanced electrocardiogram to detect left ventricular systolic dysfunction

Aims

Some artificial intelligence models applied in medical practice require ongoing retraining, introduce unintended racial bias, or have variable performance among different subgroups of patients. We assessed the real-world performance of the artificial intelligence-enhanced electrocardiogram to detect left ventricular systolic dysfunction with respect to multiple patient and electrocardiogram variables to determine the algorithm’s long-term efficacy and potential bias in the absence of retraining.

Methods and results

Electrocardiograms acquired in 2019 at Mayo Clinic in Minnesota, Arizona, and Florida with an echocardiogram performed within 14 days were analyzed (n = 44 986 unique patients). The area under the curve (AUC) was calculated to evaluate performance of the algorithm among age groups, racial and ethnic groups, patient encounter location, electrocardiogram features, and over time. The artificial intelligence-enhanced electrocardiogram to detect left ventricular systolic dysfunction had an AUC of 0.903 for the total cohort. Time series analysis of the model validated its temporal stability. Areas under the curve were similar for all racial and ethnic groups (0.90–0.92) with minimal performance difference between sexes. Patients with a ‘normal sinus rhythm’ electrocardiogram (n = 37 047) exhibited an AUC of 0.91. All other electrocardiogram features had areas under the curve between 0.79 and 0.91, with the lowest performance occurring in the left bundle branch block group (0.79).

Conclusion

The artificial intelligence-enhanced electrocardiogram to detect left ventricular systolic dysfunction is stable over time in the absence of retraining and robust with respect to multiple variables including time, patient race, and electrocardiogram features.

Identification of Five Hub Genes Based on Single-Cell RNA Sequencing Data and Network Pharmacology in Patients With Acute Myocardial Infarction

Acute myocardial infarction (AMI) has a high mortality. The single-cell RNA sequencing (scRNA-seq) method was used to analyze disease heterogeneity at the single-cell level. From the Gene Expression Omnibus (GEO) database (GSE180678), AMI scRNA-seq were downloaded and preprocessed by the Seurat package. Gene expression data came from GSE182923. Cell cluster analysis was conducted. Cell types were identified. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses were performed on hub genes. Drugs were predicted by protein–protein interaction (PPI) and molecular docking. In total, 7 cell clusters were defined based on the scRNA-seq dataset, and the clusters were labeled as 5 cell types by marker genes. Hematopoietic stem cell types as a differential subgroups were higher in AMI than in healthy tissues. From available databases and PPI analysis, 52 common genets were identified. Based on 52 genes, 5 clusters were obtained using the MCODE algorithm, and genes in these 5 clusters involved in immune and inflammatory pathways were determined. Correlation analysis showed that hematopoietic stem cell types were negatively correlated with ATM, CARM1, and CASP8 but positively correlated with CASP3 and PPARG. This was reversed with immune cells. Molecular docking analysis showed that DB05490 had the lowest docking score with PPARG. We identified 5 hub genes (ATM, CARM1, CASP8, CASP3, and PPARG) involved in AMI progression. Compound DB05490 was a potential inhibitor of PPAG.

Brain Natriuretic Peptide Biomarkers in Current Clinical and Therapeutic Scenarios of Heart Failure

Brain natriuretic peptide (BNP) and its inactive N-terminal fragment, NT-proBNP, are serum biomarkers with key roles in the management of heart failure (HF). An increase in the serum levels of these peptides is closely associated with the pathophysiological mechanisms underlying HF such as the presence of structural and functional cardiac abnormalities, myocardial stretch associated with a high filling pressure and neuro-hormonal activation. As BNP and NT-proBNP measurements are possible, several studies have investigated their clinical utility in the diagnosis, prognostic stratification, monitoring and guiding therapy of patients with HF. BNP and NT-proBNP have also been used as criteria for enrollment in randomized trials evaluating the efficacy of new therapeutic strategies for HF. Nevertheless, the use of natriuretic peptides is still limited in clinical practice due to the controversial aspect of their use in different clinical settings. The purpose of this review is to discuss the main issues associated with using BNP and NT-proBNP serum levels in the management of patients with HF under current clinical and therapeutic scenarios.

The Translation and Commercialisation of Biomarkers for Cardiovascular Disease—A Review

As a leading cause of mortality and morbidity worldwide, cardiovascular disease and its diagnosis, quantification, and stratification remain significant health issues. Increasingly, patients present with cardiovascular disease in the absence of known risk factors, suggesting the presence of yet unrecognized pathological processes and disease predispositions. Fortunately, a host of emerging cardiovascular biomarkers characterizing and quantifying ischaemic heart disease have shown great promise in both laboratory settings and clinical trials. These have demonstrated improved predictive value additional to widely accepted biomarkers as well as providing insight into molecular phenotypes beneath the broad umbrella of cardiovascular disease that may allow for further personalized treatment regimens. However, the process of translation into clinical practice – particularly navigating the legal and commercial landscape – poses a number of challenges. Practical and legal barriers to the biomarker translational pipeline must be further considered to develop strategies to bring novel biomarkers into the clinical sphere and apply these advances at the patient bedside. Here we review the progress of emerging biomarkers in the cardiovascular space, with particular focus on those relevant to the unmet needs in ischaemic heart disease.

NT-ProBNP and high-sensitivity troponin T as screening tests for subclinical chronic heart failure in a general population

Aims

The aim of this study was to establish age‐specific and sex‐specific cut‐off values for N‐terminal pro‐brain natriuretic peptide (NT‐proBNP) and high‐sensitivity troponin T (hs‐troponin T) in healthy subjects and assess cardiac biomarkers as screening tools for subclinical heart failure (HF) in a general population.

Methods and results

Altogether, 1936 participants were randomly selected from the general population Tromsø 7 study in Northern Norway. Diagnostic accuracy (sensitivity, specificity, and negative and positive predictive value) of cardiac markers for echocardiographically defined subclinical HF was evaluated. The receiver‐operating characteristic analysis showed that areas under the curve were relatively low (under 0.75) for both NT‐proBNP and hs‐troponin T, suggesting that the diagnostic accuracy of these biomarkers for subclinical HF was not excellent, especially for mild forms of HF and younger age group 40–49 years. Sex‐specific and age‐specific cut‐offs for hs‐troponin T (99th percentiles) and NT‐proBNP (97.5th percentiles) were established in healthy subjects from the same general population. The sex‐specific and age‐specific cut‐offs for NT‐proBNP had higher specificity for subclinical HF compared with the previously established single cut‐off 125 pg/mL. Age‐specific cut‐off for hs‐troponin T (18 ng/L) for men ≥60 years had also higher specificity than the single cut‐off 14 ng/L. These cut‐offs had high specificity, but low sensitivity, that makes hs‐troponin T and NT‐proBNP good biomarkers to rule in HF in case of a positive test, but not good enough to rule out all unrecognized HF due to false negative results.

Conclusions

N‐terminal pro‐brain natriuretic peptide and hs‐troponin T are suboptimal screening tools for subclinical HF in a general population due to low sensitivity.

Artificial Intelligence-Enabled Electrocardiography Predicts Left Ventricular Dysfunction and Future Cardiovascular Outcomes: A Retrospective Analysis

BACKGROUND: The ejection fraction (EF) provides critical information about heart failure (HF) and its management. Electrocardiography (ECG) is a noninvasive screening tool for cardiac electrophysiological activities that has been used to detect patients with low EF based on a deep learning model (DLM) trained via large amounts of data. However, no studies have widely investigated its clinical impacts. OBJECTIVE: This study developed a DLM to estimate EF via ECG (ECG-EF). We further investigated the relationship between ECG-EF and echo-based EF (ECHO-EF) and explored their contributions to future cardiovascular adverse events. METHODS: There were 57,206 ECGs with corresponding echocardiograms used to train our DLM. We compared a series of training strategies and selected the best DLM. The architecture of the DLM was based on ECG12Net, developed previously. Next, 10,762 ECGs were used for validation, and another 20,629 ECGs were employed to conduct the accuracy test. The changes between ECG-EF and ECHO-EF were evaluated. The primary follow-up adverse events included future ECHO-EF changes and major adverse cardiovascular events (MACEs). RESULTS: The sex-/age-matching strategy-trained DLM achieved the best area under the curve (AUC) of 0.9472 with a sensitivity of 86.9% and specificity of 89.6% in the follow-up cohort, with a correlation of 0.603 and a mean absolute error of 7.436. In patients with accurate prediction (initial difference < 10%), the change traces of ECG-EF and ECHO-EF were more consistent (R-square = 0.351) than in all patients (R-square = 0.115). Patients with lower ECG-EF (≤35%) exhibited a greater risk of cardiovascular (CV) complications, delayed ECHO-EF recovery, and earlier ECHO-EF deterioration than patients with normal ECG-EF (>50%). Importantly, ECG-EF demonstrated an independent impact on MACEs and all CV adverse outcomes, with better prediction of CV outcomes than ECHO-EF. CONCLUSIONS: The ECG-EF could be used to initially screen asymptomatic left ventricular dysfunction (LVD) and it could also independently contribute to the predictions of future CV adverse events. Although further large-scale studies are warranted, DLM-based ECG-EF could serve as a promising diagnostic supportive and management-guided tool for CV disease prediction and the care of patients with LVD.

Diabetic cardiomyopathy: Clinical phenotype and practice

Diabetic cardiomyopathy (DCM) is a pathophysiological condition of cardiac structure and function changes in diabetic patients without coronary artery disease, hypertension, and other types of heart diseases. DCM is not uncommon in people with diabetes, which increases the risk of heart failure. However, the treatment is scarce, and the prognosis is poor. Since 1972, one clinical study after another on DCM has been conducted. However, the complex phenotype of DCM still has not been fully revealed. This dilemma hinders the pace of understanding the essence of DCM and makes it difficult to carry out penetrating clinical or basic research. This review summarizes the literature on DCM over the last 40 years and discusses the overall perspective of DCM, phase of progression, potential clinical indicators, diagnostic and screening criteria, and related randomized controlled trials to understand DCM better.

Artificial intelligence-enabled electrocardiogram screens low left ventricular ejection fraction with a degree of confidence

Background

Artificial intelligence-enabled electrocardiogram has become a substitute tool for echocardiography in left ventricular ejection fraction estimation. However, the direct use of artificial intelligence-enabled electrocardiogram may be not trustable due to the uncertainty of the prediction.

Objective

The study aimed to establish an artificial intelligence-enabled electrocardiogram with a degree of confidence to identify left ventricular dysfunction.

Methods

The study collected 76,081 and 11,771 electrocardiograms from an academic medical center and a community hospital to establish and validate the deep learning model, respectively. The proposed deep learning model provided the point estimation of the actual ejection fraction and its standard deviation derived from the maximum probability density function of a normal distribution. The primary analysis focused on the accuracy of identifying patients with left ventricular dysfunction (ejection fraction ≤ 40%). Since the standard deviation was an uncertainty indicator in a normal distribution, we used it as a degree of confidence in the artificial intelligence-enabled electrocardiogram. We further explored the clinical application of estimated standard deviation and followed up on the new-onset left ventricular dysfunction in patients with initially normal ejection fraction.

Results

The area under receiver operating characteristic curves (AUC) of detecting left ventricular dysfunction were 0.9549 and 0.9365 in internal and external validation sets. After excluding the cases with a lower degree of confidence, the artificial intelligence-enabled electrocardiogram performed better in the remaining cases in internal (AUC = 0.9759) and external (AUC = 0.9653) validation sets. For the application of future left ventricular dysfunction risk stratification in patients with initially normal ejection fraction, a 4.57-fold risk of future left ventricular dysfunction when the artificial intelligence-enabled electrocardiogram is positive in the internal validation set. The hazard ratio was increased to 8.67 after excluding the cases with a lower degree of confidence. This trend was also validated in the external validation set.

Conclusion

The deep learning model with a degree of confidence can provide advanced improvements in identifying left ventricular dysfunction and serve as a decision support and management-guided screening tool for prognosis.

Application of artificial intelligence to the electrocardiogram

Artificial intelligence (AI) has given the electrocardiogram (ECG) and clinicians reading them super-human diagnostic abilities. Trained without hard-coded rules by finding often subclinical patterns in huge datasets, AI transforms the ECG, a ubiquitous, non-invasive cardiac test that is integrated into practice workflows, into a screening tool and predictor of cardiac and non-cardiac diseases, often in asymptomatic individuals. This review describes the mathematical background behind supervised AI algorithms, and discusses selected AI ECG cardiac screening algorithms including those for the detection of left ventricular dysfunction, episodic atrial fibrillation from a tracing recorded during normal sinus rhythm, and other structural and valvular diseases. The ability to learn from big data sets, without the need to understand the biological mechanism, has created opportunities for detecting non-cardiac diseases as COVID-19 and introduced challenges with regards to data privacy. Like all medical tests, the AI ECG must be carefully vetted and validated in real-world clinical environments. Finally, with mobile form factors that allow acquisition of medical-grade ECGs from smartphones and wearables, the use of AI may enable massive scalability to democratize healthcare.

Artificial Intelligence-Augmented Electrocardiogram Detection of Left Ventricular Systolic Dysfunction in the General Population

OBJECTIVE

To validate an artificial intelligence-augmented electrocardiogram (AI-ECG) algorithm for the detection of preclinical left ventricular systolic dysfunction (LVSD) in a large community-based cohort.

METHODS

We identified a randomly selected community-based cohort of 2041 subjects age 45 years or older in Olmsted County, Minnesota. All participants underwent a study echocardiogram and ECG. We first assessed the performance of the AI-ECG to identify LVSD (ejection fraction ≤40%). After excluding participants with clinical heart failure, we further assessed the AI-ECG to detect preclinical LVSD among all patients (n=1996) and in a high-risk subgroup (n=1348). Next we modelled an imputed screening program for preclinical LVSD detection where a positive AI-ECG triggered an echocardiogram. Finally, we assessed the ability of the AI-ECG to predict future LVSD. Participants were enrolled between January 1, 1997, and September 30, 2000; and LVSD surveillance was performed for 10 years after enrollment.

RESULTS

For detection of LVSD in the total population (prevalence, 2.0%), the area under the receiver operating curve for AI-ECG was 0.97 (sensitivity, 90%; specificity, 92%); in the high-risk subgroup (prevalence 2.7%), the area under the curve was 0.97 (sensitivity, 92%; specificity, 93%). In an imputed screening program, identification of one preclinical LSVD case would require 88.3 AI-ECGs and 8.7 echocardiograms in the total population and 65.7 AI-ECGs and 5.5 echocardiograms in the high-risk subgroup. The unadjusted hazard ratio for a positive AI-ECG for incident LVSD over 10 years was 2.31 (95% CI, 1.32 to 4.05; P=.004).

CONCLUSION

Artificial intelligence-augmented ECG can identify preclinical LVSD in the community and warrants further study as a screening tool for preclinical LVSD.

Role of novel biomarkers in diabetic cardiomyopathy

Diabetic cardiomyopathy (DCM) is commonly defined as cardiomyopathy in patients with diabetes mellitus in the absence of coronary artery disease and hypertension. As DCM is now recognized as a cause of substantial morbidity and mortality among patients with diabetes mellitus and clinical diagnosis is still inappropriate, various expert groups struggled to identify a suitable biomarker that will help in the recognition and management of DCM, with little success so far. Hence, we thought it important to address the role of biomarkers that have shown potential in either human or animal studies and which could eventually result in mitigating the poor outcomes of DCM. Among the array of biomarkers we thoroughly analyzed, long noncoding ribonucleic acids, soluble form of suppression of tumorigenicity 2 and galectin-3 seem to be most beneficial for DCM detection, as their plasma/serum levels accurately correlate with the early stages of DCM. The combination of relatively inexpensive and accurate speckle tracking echocardiography with some of the highlighted biomarkers may be a promising screening method for newly diagnosed diabetes mellitus type 2 patients. The purpose of the screening test would be to direct affected patients to more specific confirmation tests. This perspective is in concordance with current guidelines that accentuate the importance of an interdisciplinary team-based approach.

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.

Sex, racial differences and healthy aging in normative reference ranges on diastolic function in Ethnic Asians: 2016 ASE guideline revisited

BACKGROUND

Diastolic dysfunction (DD) has shown to be a hallmark pathological intermediate in the development of heart failure with preserved ejection fraction (HFpEF). We aim to establish age- and sex-stratified normal reference values of diastolic indices and to explore racial-differences.

METHODS

We explored age- and sex-related structural/functional alterations from 6023 healthy ethnic Asians (47.1 ± 10.9 years, 61.3% men) according to 2016 American Society of Echocardiography (ASE) diastolic dysfunction (DD) criteria. Racial comparisons were made using data from London Life Sciences Prospective Population (LOLIPOP) study.

RESULTS

Age- and sex-based normative ranges (including mean, median, 10% and 90% lower and upper reference values) were extracted from our large healthy population. In fully adjusted models, advanced age was independently associated with cardiac structural remodeling and worsened diastolic parameters including larger indexed LA volume (LAVi), lower e', higher E/e', and higher TR velocity; all p < 0.001), which were more prominent in women (P interaction: <0.05). Broadly, markedly lower e', higher E/e' and smaller LAVi were observed in ethnic Asians compared to Whites. DD defined by 2016 ASE criteria, despite at low prevalence (0.42%) in current healthy population, increased drastically with advanced age and performed perfectly in excluding abnormal NT-proBNP (≥125 pg/mL) (Specificity: 99.8%, NPV: 97.6%).

CONCLUSION

This is to date the largest cohort exploring the normative reference values using guideline-centered diastolic parameters from healthy Asians, with aging played as central role in diastolic dysfunction. Our observed sex and ethnic differences in defining healthy diastolic cut-offs likely impact future clinical definition for DD in Asians.

Impact of lipophilic vs hydrophilic statins on the clinical outcome and biomarkers of remodelling in heart failure patients: A prospective comparative randomized study

AIMS

There are insufficient direct comparative studies addressing the impact of the type of statin on their respective efficacy in heart failure (HF). The aim of the current study was to compare the effects of lipophilic (atorvastatin) vs hydrophilic (rosuvastatin) on left ventricular function, inflammatory and fibrosis biomarkers in patients with chronic HF.

METHODS

This was a prospective, randomized, comparative, parallel study. A total of 85 patients with chronic HF optimized on guideline directed therapy were randomized to receive either atorvastatin 40 mg (n = 42) or rosuvastatin 20 mg (n = 43) for 6 months. Baseline and follow-up assessment included 2D echocardiography, measurement of N-terminal pro-brain natriuretic peptide, interleukin-6 and soluble suppression of tumorigenicity 2 (sST2) levels, liver enzymes and lipid profile.

RESULTS

The increase in left ventricular ejection fraction was significantly higher in the atorvastatin group compared to the rosuvastatin group (6.5% [3-11] vs 4% [2-5], P = .006). The reduction in left ventricular end diastolic and end systolic volume was comparable between the 2 groups. The decrease in sST2 levels in pg/mL was significantly higher in the atorvastatin compared to the rosuvastatin group (-255 [-383 to -109.8 vs - 151 [-216 to -69], P = .003). There was a significant reduction in N-terminal pro-brain natriuretic peptide and interleukin-6 levels in both groups, yet the reduction was comparable in both groups.

CONCLUSION

The study results suggest that lipophilic atorvastatin is superior to hydrophilic rosuvastatin in increasing left ventricular ejection fraction and reducing fibrosis marker sST2 in HF patients. Trial registration ID: NCT03255044, registered on 21 August 2017.

Artificial Intelligence-Enabled ECG: a Modern Lens on an Old Technology

PURPOSE OF REVIEW

To (i) review the concept of artificial intelligence (AI); (ii) summarize recent developments in artificial intelligence-enabled electrocardiogram (AI-ECG); (iii) address notable inherent limitations and challenges of AI-ECG; and (iv) discuss the future direction of the field.

RECENT FINDINGS

Advancements in machine learning and computing methods have led to application of AI-ECG and potential new applications to patient care. Further study is needed to verify previous findings in diverse populations as well as begin to confront the limitations needed for clinical implementation. Nearly one century after the Nobel Prize was awarded to Willem Einthoven for demonstrating that an electrocardiogram (ECG) could record the electrical signature of the heart, the ECG remains one of the most important diagnostic tests in modern medicine. We now stand at the edge of true ECG innovation. Simultaneous advancements in computing power, wireless technology, digitized data availability, and machine learning have led to the birth of AI-ECG algorithms with novel capabilities and real potential for clinical application. AI has the potential to improve diagnostic accuracy and efficiency by providing fully automated, unbiased, and unambiguous ECG analysis along with promising new findings that may unlock new value in the ECG. These breakthroughs may cause a paradigm shift in clinical workflow as well as patient monitoring and management.

Screening for asymptomatic heart failure with preserved ejection fraction in mongolian population at high risk

Objective The goals of the present study were to assess the prevalence of asymptomatic heart failure with preserved ejection fraction (HFpEF) in subjects at high risk of developing HF and to define the diagnostic accuracy of NT-pro BNP assay compared with echocardiography in this setting.Material and methods This cross-sectional study included subjects aged from 35 to 64 years, with high risk of HF, who had no clinical symptoms of HF. Risk factors of HF were detected by clinical examinations. NT-pro BNP determination was performed using immunoassay analyzer (FIA8000, Getein Bio Medical Inc, China),. The cut-off point for NT-pro BNP was 125 pg/ml. Diagnosis of HFpEF was based on criteria recommended by 2016 ESC heart failure guidelines. Diastolic dysfunction was assessed according to the algorithm proposed in the joint recommendations of the ASE/EACVI.Results 602 patients with risk factors of HF were included in the study, of which 256 (42.5 %) were males and 346 (57.5 %) females. The mean age was 51.71±8.07 years. 83 patients (13.8 %) showed elevated NT-pro BNP levels of ≥125 pg / ml. Our study has shown that NT-pro BNP concentration was positively correlating with age, both systolic and diastolic blood pressure, left ventricular mass and E / e' ratio and negatively correlating with waist circumference, body mass index, left ventricular EF and E / A ratio in asymptomatic population. The likelihood of positive NT-pro BNP test was independently (p&lt;0.05) associated with age, hypertension and diabetes. The diagnosis of asymptomatic HFpEF was confirmed in 12.3 % of studied population. A cutoff value of 125 pg / ml for NT-proBNP concentration showed the following diagnostic re-abilities in identifying asymptomatic HFpEF: sensitivity 85.0 %, specificity 88.6 % and area under curve 0.92 (95 % CI 0.86-0.98).Conclusion Subjects with raised NT-pro BNP level (≥125 pg/ml) were more likely to have a confirmed diagnosis of asymptomatic HFpEF after screening. In summary, in at-risk population, natriuretic peptide based screening combined with echocardiography identifies high prevalence of asymptomatic HFpEF.

Natriuretic peptide-guided treatment for the prevention of cardiovascular events in patients without heart failure

BACKGROUND

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality globally. Early intervention for those with high cardiovascular risk is crucial in improving patient outcomes. Traditional prevention strategies for CVD have focused on conventional risk factors, such as overweight, dyslipidaemia, diabetes, and hypertension, which may reflect the potential for cardiovascular insult. Natriuretic peptides (NPs), including B-type natriuretic peptide (BNP) and N-terminal pro B-type natriuretic peptide (NT-proBNP), are well-established biomarkers for the detection and diagnostic evaluation of heart failure. They are of interest for CVD prevention because they are secreted by the heart as a protective response to cardiovascular stress, strain, and damage. Therefore, measuring NP levels in patients without heart failure may be valuable for risk stratification, to identify those at highest risk of CVD who would benefit most from intensive risk reduction measures.

OBJECTIVES

To assess the effects of natriuretic peptide (NP)-guided treatment for people with cardiovascular risk factors and without heart failure.

SEARCH METHODS

Searches of the following bibliographic databases were conducted up to 9 July 2019: CENTRAL, MEDLINE, Embase, and Web of Science. Three clinical trial registries were also searched in July 2019.

SELECTION CRITERIA

We included randomised controlled trials enrolling adults with one or more cardiovascular risk factors and without heart failure, which compared NP-based screening and subsequent NP-guided treatment versus standard care in all settings (i.e. community, hospital).

DATA COLLECTION AND ANALYSIS

Two review authors independently screened titles and abstracts and selected studies for inclusion, extracted data, and evaluated risk of bias. Risk ratios (RRs) were calculated for dichotomous data, and mean differences (MDs) with 95% confidence intervals (CIs) were calculated for continuous data. We contacted trial authors to obtain missing data and to verify crucial study characteristics. Using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach, two review authors independently assessed the quality of the evidence and GRADE profiler (GRADEPRO) was used to import data from Review Manager to create a 'Summary of findings' table.

MAIN RESULTS

We included two randomised controlled trials (three reports) with 1674 participants, with mean age between 64.1 and 67.8 years. Follow-up ranged from 2 years to mean 4.3 years.For primary outcome measures, effect estimates from a single study showed uncertainty for the effect of NP-guided treatment on cardiovascular mortality in patients with cardiovascular risk factors and without heart failure (RR 0.33, 95% CI 0.04 to 3.17; 1 study; 300 participants; low-quality evidence). Pooled analysis demonstrated that in comparison to standard care, NP-guided treatment probably reduces the risk of cardiovascular hospitalisation (RR 0.52, 95% CI 0.40 to 0.68; 2 studies; 1674 participants; moderate-quality evidence). This corresponds to a risk of 163 per 1000 in the control group and 85 (95% CI 65 to 111) per 1000 in the NP-guided treatment group.When secondary outcome measures were evaluated, evidence from a pooled analysis showed uncertainty for the effect of NP-guided treatment on all-cause mortality (RR 0.90, 95% CI 0.60 to 1.35; 2 studies; 1354 participants; low-quality evidence). Pooled analysis indicates that NP-guided treatment probably reduces the risk of all-cause hospitalisation (RR 0.83, 95% CI 0.75 to 0.92; 2 studies; 1354 participants; moderate-quality evidence). This corresponds to a risk of 601 per 1000 in the control group and 499 (95% CI 457 to 553) per 1000 in the NP-guided treatment group. The effect estimate from a single study indicates that NP-guided treatment reduced the risk of ventricular dysfunction (RR 0.61, 95% CI 0.41 to 0.91; 1374 participants; high-quality evidence). The risk in this study's control group was 87 per 1000, compared with 53 (95% CI 36 to 79) per 1000 with NP-guided treatment. Results from the same study show that NP-guided treatment does not affect change in NP level at the end of follow-up, relative to standard care (MD -4.06 pg/mL, 95% CI -15.07 to 6.95; 1 study; 1374 participants; moderate-quality evidence).

AUTHORS' CONCLUSIONS

This review shows that NP-guided treatment is likely to reduce ventricular dysfunction and cardiovascular and all-cause hospitalisation for patients who have cardiovascular risk factors and who do not have heart failure. Effects on mortality and natriuretic peptide levels are less certain. Neither of the included studies were powered to evaluate mortality. Available evidence shows uncertainty regarding the effects of NP-guided treatment on both cardiovascular mortality and all-cause mortality; very low event numbers resulted in a high degree of imprecision in these effect estimates. Evidence also shows that NP-guided treatment may not affect NP level at the end of follow-up.As both trials included in our review were pragmatic studies, non-blinding of patients and practices may have biased results towards a finding of equivalence. Further studies with more adequately powered sample sizes and longer duration of follow-up are required to evaluate the effect of NP-guided treatment on mortality. As two trials are ongoing, one of which is a large multi-centre trial, it is hoped that future iterations of this review will benefit from larger sample sizes across a wider geographical area.

Current advances in the study of diabetic cardiomyopathy: From clinicopathological features to molecular therapeutics (Review)

The incidence of diabetes mellitus has become a major public health concern due to lifestyle alterations. Moreover, the complications associated with diabetes mellitus deeply influence the quality of life of patients. Diabetic cardiomyopathy (DC) is a type of diabetes mellitus complication characterized by functional and structural damage in the myocardium but not accompanied by coronary arterial disease. Currently, diagnosing and preventing DC is still a challenge for physicians due to its atypical symptoms. For this reason, it is necessary to summarize the current knowledge on DC, especially in regards to the underlying molecular mechanisms toward the goal of developing useful diagnostic approaches and effective drugs based on these mechanisms. There exist several review articles which have focused on these points, but there still remains a lot to learn from published studies. In this review, the features, diagnosis and molecular mechanisms of DC are reviewed. Furthermore, potential therapeutic and prophylactic drugs are discussed.

Screening for cardiac contractile dysfunction using an artificial intelligence-enabled electrocardiogram

Asymptomatic left ventricular dysfunction (ALVD) is present in 3-6% of the general population, is associated with reduced quality of life and longevity, and is treatable when found^1-4. An inexpensive, noninvasive screening tool for ALVD in the doctor's office is not available. We tested the hypothesis that application of artificial intelligence (AI) to the electrocardiogram (ECG), a routine method of measuring the heart's electrical activity, could identify ALVD. Using paired 12-lead ECG and echocardiogram data, including the left ventricular ejection fraction (a measure of contractile function), from 44,959 patients at the Mayo Clinic, we trained a convolutional neural network to identify patients with ventricular dysfunction, defined as ejection fraction ≤35%, using the ECG data alone. When tested on an independent set of 52,870 patients, the network model yielded values for the area under the curve, sensitivity, specificity, and accuracy of 0.93, 86.3%, 85.7%, and 85.7%, respectively. In patients without ventricular dysfunction, those with a positive AI screen were at 4 times the risk (hazard ratio, 4.1; 95% confidence interval, 3.3 to 5.0) of developing future ventricular dysfunction compared with those with a negative screen. Application of AI to the ECG-a ubiquitous, low-cost test-permits the ECG to serve as a powerful screening tool in asymptomatic individuals to identify ALVD.

Noninvasive Cardiac Imaging and the Prediction of Heart Failure Progression in Preclinical Stage A/B Subjects

Heart failure (HF) continues to grow as a cause of morbidity and mortality in our community and presents a significant public health problem, predominantly in individuals ≥65 years of age. Early intervention in asymptomatic HF subjects (Stage A/B) at risk of progression to symptomatic HF (Stage C/D) may provide an opportunity to halt this epidemic. The ability of cardiac imaging to assess cardiac structure and function permits early identification of those at increased risk of developing symptomatic HF. Systolic, diastolic, and structural left ventricular parameters each predict symptomatic HF, but no single parameter has sufficient sensitivity for screening to identify individuals with Stage A/B HF who are at increased risk of disease progression. Transthoracic echocardiography (TTE) has the advantage over other imaging modalities in being able to measure systolic, diastolic, and structural left ventricular parameters, and it identified at least 1 abnormal parameter in >50% of individuals with Stage A/B HF ≥65 years of age. Moreover, identification of at least 1 abnormality according to TTE in individuals with Stage A/B HF ≥65 years of age had 72% to 82% sensitivity for detection of those who subsequently developed symptomatic HF. Therefore, a case can be made for cardiac imaging by using TTE for community-dwelling populations with Stage A/B HF ≥65 years of age to identify those with increased risk of symptomatic HF who can be offered preventative therapies. Further studies are required to determine the best strategy for identifying the risk of symptomatic HF in younger individuals.

Novel Biomarkers of Subclinical Cardiac Dysfunction in the General Population

PURPOSE OF REVIEW

Recognition of subclinical myocardial dysfunction offers clinicians and patients an opportunity for early intervention and prevention of symptomatic cardiovascular disease. We review the data on novel biomarkers in subclinical heart disease in the general population with a focus on pathophysiology, recent observational or trial data, and potential applicability and pitfalls for clinical use.

RECENT FINDINGS

High-sensitivity cardiac troponin and natriuretic peptide assays are powerful markers of subclinical cardiac disease. Elevated levels of these biomarkers signify subclinical cardiac injury and hemodynamic stress and portend an adverse prognosis. Novel biomarkers of myocardial inflammation, fibrosis, and abnormal contraction are gaining momentum as predictors for incident heart failure, providing new insight into pathophysiologic mechanisms of cardiac disease. There has been exciting growth in both traditional and novel biomarkers of subclinical cardiac injury in recent years. Many biomarkers have demonstrated associations with relevant cardiovascular outcomes and may enhance the diagnostic and prognostic power of more conventional biomarkers. However, their use in "prime time" to identify patients with or at risk for subclinical cardiac dysfunction in the general population remains an open question. Strategic investigation into their clinical applicability in the context of clinical trials remains an area of ongoing investigation.

SCReening Evaluation of the Evolution of New Heart Failure Study (SCREEN-HF): early detection of chronic heart failure in the workplace

Objective The aim of the present study was to determine whether asymptomatic heart failure (HF) in the workplace is subject to the health worker effect, making screening using conventional risk factors combined with a cardiac biomarker, namely N-terminal pro B-type natriuretic peptide (NT-proBNP), as useful as in the general population. Methods Between June 2007 and December 2009 a 'well' population deemed at high risk for development of HF was identified through health insurance records. Blood was collected from volunteer participants for analysis of urea, electrolytes and creatinine, a full blood count and NT-proBNP. An echocardiogram was performed on selected participants based on high NT-proBNP concentrations. Results The mean left ventricular ejection fraction (LVEF) was significantly reduced in participants with the highest compared with the lowest NT-proBNP quintile. In multivariate analysis, log-transformed NT-proBNP was independently associated with impaired LVEF and with moderate to severe diastolic dysfunction after adjustment for age, sex, coronary artery disease, diabetes, hypertension and obesity. Conclusions A large burden of asymptomatic left ventricular dysfunction (AVLD) was observed in subjects aged 60 and over with plasma NT-proBNP in the top quintile that was independent of conventional risk factors and work status. HWE does not appear to operate in AVLD. NT-proBNP testing in a population with HF risk factors may cost-effectively identify those at greatest risk of developing HF in a working population and facilitate early diagnosis, treatment and maintenance of work capacity. What is known about the topic? Chronic heart failure (CHF) has several causes, the most common being hypertension and coronary ischaemia. CHF is a major health problem of increasing prevalence that severely impacts quality of life, shortens lives and reduces worker productivity. It is often not diagnosed early enough to take full advantage of ameliorating medication. What does this paper add? Population screening for CHF is not currently advocated. This may be because conventional risk factors must be used in combination and there is no useful biomarker available. Yet evidence (SOLVD (Studies of Left Ventricular Dysfunction trials) recommends early diagnosis. We believe the work place is an area of potential screening where there is little supporting evidence. This paper provides evidence that the biomarker NT-proBNP is a useful new tool that improves cost-effectiveness of screening in a selected population. Specifically, the paper recommends CHF screening in the population with the highest potential health gain (i.e. the working population) by the sector with the highest economic gain (i.e. employers). What are the implications for practitioners? The paper presents important health screening recommendations for medical and health and safety practitioners within a selected population of workers. We feel practitioners should consider screening for incipient heart failure, particularly within Australia's working population, to save lives, provide economic benefit and extend working longevity.

Diagnostic approaches for diabetic cardiomyopathy

Diabetic cardiomyopathy (DCM) is a cardiac dysfunction which affects approximately 12% of diabetic patients, leading to overt heart failure and death. However, there is not an efficient and specific methodology for DCM diagnosis, possibly because molecular mechanisms are not fully elucidated, and it remains asymptomatic for many years. Also, DCM frequently coexists with other comorbidities such as hypertension, obesity, dyslipidemia, and vasculopathies. Thus, human DCM is not specifically identified after heart failure is established. In this sense, echocardiography has been traditionally considered the gold standard imaging test to evaluate the presence of cardiac dysfunction, although other techniques may cover earlier DCM detection by quantification of altered myocardial metabolism and strain. In this sense, Phase-Magnetic Resonance Imaging and 2D/3D-Speckle Tracking Echocardiography may potentially diagnose and stratify diabetic patients. Additionally, this information could be completed with a quantification of specific plasma biomarkers related to related to initial stages of the disease. Cardiotrophin-1, activin A, insulin-like growth factor binding protein-7 (IGFBP-7) and Heart fatty-acid binding protein have demonstrated a stable positive correlation with cardiac hypertrophy, contractibility and steatosis responses. Thus, we suggest a combination of minimally-invasive diagnosis tools for human DCM recognition based on imaging techniques and measurements of related plasma biomarkers.

Screening and Treatment for Subclinical Hypertensive Heart Disease in Emergency Department Patients With Uncontrolled Blood Pressure: A Cost-effectiveness Analysis

OBJECTIVES

Poorly controlled hypertension (HTN) is extremely prevalent and, if left unchecked, subclinical hypertensive heart disease (SHHD) may ensue leading to conditions such as heart failure. To address this, we designed a multidisciplinary program to detect and treat SHHD in a high-risk, predominantly African American community. The primary objective of this study was to determine the cost-effectiveness of our program.

METHODS

Study costs associated with identifying and treating patients with SHHD were calculated and a sensitivity analysis was performed comparing the effect of four parameters on cost estimates. These included prevalence of disease, effectiveness of treatment (regression of SHHD, reversal of left ventricular hypertrophy [LVH], or blood pressure [BP] control as separate measures), echocardiogram costs, and participant time/travel costs. The parent study for this analysis was a single-center, randomized controlled trial comparing cardiac effects of standard and intense (<120/80 mm Hg) BP goals at 1 year in patients with uncontrolled HTN and SHHD. A total of 149 patients (94% African American) were enrolled, 133 (89%) had SHHD, 123 (93%) of whom were randomized, with 88 (72%) completing the study. Patients were clinically evaluated and medically managed over the course of 1 year with repeated echocardiograms. Costs of these interventions were analyzed and, following standard practices, a cost per quality-adjusted life-year (QALY) less than $50,000 was defined as cost-effective.

RESULTS

Total costs estimates for the program ranged from $117,044 to $119,319. Cost per QALY was dependent on SHHD prevalence and the measure of effectiveness but not input costs. Cost-effectiveness (cost per QALY less than $50,000) was achieved when SHHD prevalence exceeded 11.1% for regression of SHHD, 4.7% for reversal of LVH, and 2.9% for achievement of BP control.

CONCLUSIONS

In this cohort of predominantly African American patients with uncontrolled HTN, SHHD prevalence was high and screening with treatment was cost-effective across a range of assumptions. These data suggest that multidisciplinary programs such as this can be a cost-effective mechanism to mitigate the cardiovascular consequences of HTN in emergency department patients with uncontrolled BP.

Current Understanding of the Compensatory Actions of Cardiac Natriuretic Peptides in Cardiac Failure: A Clinical Perspective

Natriuretic peptides play a crucial role in maintaining cardiovascular homeostasis. Among their properties are vasodilation, natriuresis, diuresis, and inhibition of cardiac remodeling. As heart failure progresses, however, natriuretic peptides fail to compensate. Knowledge of their processing and signaling pathways has guided the development of pharmacological therapies aimed at bolstering their effects. The drugs that have achieved the most clinical success have also stirred the most controversy. Nesiritide, the synthetic B-type natriuretic peptide, yielded significant symptomatic relief and improved haemodynamics but its use was plagued with questions surrounding its possibly harmful impact on renal function. More recently, compounds containing inhibitors of neprilysin, the enzyme responsible for degrading natriuretic peptides, have demonstrated morbidity and mortality benefit, but have also been linked to possible negative side effects. Clearly, potentiating the actions of natriuretic peptides for the benefit of patients is not as simple as just raising their serum concentration. This article reviews the current understanding of the compensatory actions of cardiac natriuretic peptides in heart failure and how this knowledge is revolutionizing heart failure therapy.

Increasing aminoterminal-pro-B-type natriuretic peptide precedes the development of arterial hypertension: the multiethnic study of atherosclerosis

BACKGROUND

Longitudinal associations between the aminoterminal pro-B-type natriuretic peptide (NT-proBNP) and incident hypertension are lacking.

METHODS

We tested associations between baseline NT-proBNP (bNT-proBNP) and change in NT-proBNP (ΔNT-proBNP) (visit 3 NT-proBNP - bNT-proBNP, 3.2 years apart) with incident hypertension (SBP ≥ 140 and/or DBP ≥90 mmHg or taking antihypertensive medications). Incident hypertension was evaluated in 5596 individuals in the Multi-Ethnic Study of Atherosclerosis without hypertension at baseline (53% women, age range 45-84 years without overt cardiovascular disease) and follow-up for 9.5 years and in a subgroup (1550) who had bNT-proBNP less than 100 pg/ml and no hypertension at visit 3. Incident hypertension was regressed (proportional hazards) on quintiles of bNT-proBNP (range) (reference <19.2, 19.3-40.8, 40.9-70.9, 71-135.2, and >135.5) and also on ΔNT-proBNP categories (reference <-10, -10 to 10, >10 to 50, and >50 pg/ml). Hazard ratios were adjusted for age, race, sex, education, diabetes, obesity, left ventricle mass/height, SBP and DBP, interleukin-6, salt intake, estimated glomerular filtration rate, and exercise.

RESULTS

Compared with the reference category, hazard ratios (95% confidence interval) for incident hypertension compared with the first quintile of bNT-proBNP were 1.47 (1.13-1.93), 1.57 (1.18-2.09), 1.52 (1.12-2.06), and 2.36 (1.62-3.41). Hazard ratios for incident hypertension by categories of ΔNT-proBNP from 3.2 to 9.5 years follow-up were 0.98 (0.62-1.56), 1.13 (0.72-1.79), and 1.82 (1.07-3.12).

CONCLUSION

The development of hypertension tended to be preceded by elevated levels of bNT-proBNP or a substantial positive ΔNT-proBNP.

Evaluation of the appropriateness of the preclinical phase (stage A and stage B) of heart failure Management in Outpatient clinics in Italy rationale and design of the 'VASTISSIMO' study

Early detection of heart failure, when still preclinical, is fundamental. Therefore, it is important to assess whether preclinical heart failure management by cardiologists is adequate. The VASTISSIMO study ('EValuation of the AppropriateneSs of The preclInical phase (Stage A and Stage B) of heart failure Management in Outpatient clinics in Italy') is a prospective nationwide study aimed to evaluate the appropriateness of diagnosis and management of preclinical heart failure (stages A and B) by cardiologists working in outpatient clinics in Italy. Secondary goals are to verify if an online educational course for cardiologists can improve management of preclinical heart failure, and evaluate how well cardiologists are aware of patients' adherence to medications. The study involves 80 outpatient cardiology clinics distributed throughout Italy, affiliated either to the Hospital Cardiologists Association or to the Regional Association of Outpatient Cardiologists, and is designed with two phases of consecutive outpatient enrolment each lasting 1 month. In phase 1, physicians' awareness of the risk of heart failure and their decision-making process are recorded. Subsequently, half of the cardiologists are randomized to undergo an online educational course aimed to improve preclinical heart failure management through implementation of guideline recommendations. At the end of the course, all cardiologists are evaluated (phase 2) to see whether changes in clinical management have occurred in those who underwent the educational program versus those who did not. Patients' adherence to prescribed medications will be assessed through the Morisky Self-report Questionnaire. This study should provide valuable information about cardiologists' awareness of preclinical heart failure and the appropriateness of clinical practice in outpatient cardiology clinics in Italy.

Bilateral leg edema in an older woman

Bilateral leg edema is a frequent symptom in older people and an important concern in geriatric medicine. Further evaluation is frequently not performed and simple therapy with diuretics is prescribed. Particularly in older patients, long-term use of diuretics can lead to severe electrolyte imbalances, volume depletion, and falls. In this case report we want to focus the physicians' attention on the necessity to determine the cause and show a correspondingly effective treatment for bilateral leg edema in older people. A thorough approach is required to recognize diseases and to avoid adverse drug events as geriatric patients often show an atypical presentation or minor symptoms. The cause of swollen legs is often multifactorial; therefore, the patient's individual history and an appropriate physical examination are important. Depending on the clinical symptoms, evaluation including basic laboratory tests, urinalysis, chest radiography, and echocardiogram may be indicated. The most probable cause of bilateral edema in older patients is chronic venous insufficiency. Heart failure is also a common cause. Other systemic causes such as renal disease or liver disease are much rarer. Antihypertensive and anti-inflammatory drugs can frequently cause leg edema, but the incidence of drug-induced leg swelling is unknown. With the help of this special case we tried to develop an approach to the diagnosis of symmetric leg edema in older patients, a problem frequently neglected in geriatric medicine.

The association between N-terminal pro B-type natriuretic peptide and lipoprotein particle concentration plateaus at higher N-terminal pro B-type natriuretic peptide values: Multi-Ethnic Study on Atherosclerosis

BACKGROUND

The association between N-terminal pro B-type natriuretic peptide (NT-proBNP) and blood levels of small and large LDL- and HDL- particle (P) concentration may not be linear throughout the whole range of NT-proBNP values.

METHODS

Linear spline regression analysis between NT-proBNP and lipoprotein particle concentrations was performed cross-sectionally in 5597 individuals from the Multi-Ethnic Study of Atherosclerosis adjusted for age, race, sex, body mass index, % of energy from saturated fats, intentional exercise, statin use, antihypertensive medication use, diabetes, IL-6 and estimated glomerular filtration rate. Spline knots were selected as the point at which the linear slope changed in these associations.

RESULTS

NT-proBNP was positively associated with large LDL-P and HDL-P, but inversely associated with small LDL-P and HDL-P, but only for NT-proBNP values below the knot (range: 100-200 pg/mL).

CONCLUSION

These results suggest the presence of two distinct biological mechanisms above and below the knot determining the association between NT-proBNP and lipoprotein particle concentrations.

Doxorubicin-induced cardiac dysfunction in unselected patients with a history of early-stage breast cancer

Cardiomyopathy is a known complication of anthracycline-based adjuvant chemotherapy and is more commonly reported in population-based studies of breast cancer survivors than in clinical trials. This study prospectively evaluated the prevalence of elevated cardiac biomarkers in unselected patients who had been treated with doxorubicin for early-stage breast cancer and the prevalence of reduced LVEF in patients with an elevated biomarker. All participants underwent an examination, symptom inventory, medical record review, and biomarker analysis for BNP, troponin, and plasma and urine NT-proBNP. Patients who had one or more elevated biomarkers were referred for echocardiogram; systolic dysfunction was defined as LVEF less than 55 %. Multivariable logistic regression was used to determine the associations between age, BMI, cumulative dose of doxorubicin, diabetes, hypertension, and left-sided radiation therapy and the risk of reduced LVEF. Among the 269 patients who underwent lab testing (mean age 56 years, mean time since completion of doxorubicin-based chemotherapy 6 years), 192 (72 %) had one or more elevated biomarker. Among the 166 patients who completed an echocardiogram, 11.5 % had a LVEF < 55 %. After adjusting for covariates known to affect cardiac function, multivariable logistic regression revealed plasma NT-proBNP to be the only measured cardiac biomarker associated with systolic dysfunction. There is a relationship between NT-proBNP and the frequency of reduced LVEF in women treated with doxorubicin for curative intent; further study of NT-proBNP as a potential biomarker for subclinical cardiac dysfunction after exposure to anthracyclines is warranted.

NT-proBNP and troponin T and risk of rapid kidney function decline and incident CKD in elderly adults

BACKGROUND AND OBJECTIVES

Elevations in N-terminal pro-B-type natriuretic peptide and high-sensitivity troponin T are associated with poor cardiovascular outcomes. Whether elevations in these cardiac biomarkers are associated with decline in kidney function was evaluated.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

N-terminal pro-B-type natriuretic peptide and troponin T were measured at baseline in 3752 participants free of heart failure in the Cardiovascular Health Study. eGFR was determined from the Chronic Kidney Disease Epidemiology Collaboration equation using serum cystatin C. Rapid decline in kidney function was defined as decline in serum cystatin C eGFR≥30%, and incident CKD was defined as the onset of serum cystatin C eGFR<60 among those without CKD at baseline (n=2786). Cox regression models were used to examine the associations of each biomarker with kidney function decline adjusting for demographics, baseline serum cystatin C eGFR, diabetes, and other CKD risk factors.

RESULTS

In total, 503 participants had rapid decline in serum cystatin C eGFR over a mean follow-up time of 6.41 (1.81) years, and 685 participants developed incident CKD over a mean follow-up time of 6.41 (1.74) years. Participants in the highest quartile of N-terminal pro-B-type natriuretic peptide (>237 pg/ml) had an 67% higher risk of rapid decline and 38% higher adjusted risk of incident CKD compared with participants in the lowest quartile (adjusted hazard ratio for serum cystatin C eGFR rapid decline, 1.67; 95% confidence interval, 1.25 to 2.23; hazard ratio for incident CKD, 1.38; 95% confidence interval, 1.08 to 1.76). Participants in the highest category of troponin T (>10.58 pg/ml) had 80% greater risk of rapid decline compared with participants in the lowest category (adjusted hazard ratio, 1.80; 95% confidence interval, 1.35 to 2.40). The association of troponin T with incident CKD was not statistically significant (hazard ratio, 1.17; 95% confidence interval, 0.92 to 1.50).

CONCLUSIONS

Elevated N-terminal pro-B-type natriuretic peptide and troponin T are associated with rapid decline of kidney function and incident CKD. Additional studies are needed to evaluate the mechanisms that may explain this association.

B-type natriuretic peptide-guided therapy for perioperative medicine?

The recent guideline from the European Society of Cardiology and European Society of Anesthesiology recommended the use of B-type natriuretic peptide (BNP) as preoperative testing for high-risk cardiac patients undergoing non-cardiac surgery. In this article, the potential benefits, risks and details for implementing BNP testing in perioperative medicine are discussed. Review of four related lines of research including the use of BNP test for preoperative prognosis, BNP test for screening asymptomatic heart failure, BNP as prognostic test in asymptomatic, non-heart failure patients and using BNP for detecting silent myocardial ischaemia showed converging cut-off levels of BNP for risk stratification. BNP has better OR and relative risk in comparison with Revised Cardiac Risk Index (RCRI) in predicting perioperative cardiac risk. BNP-guided therapy can be low risk based on current evidence on non-surgical patients, including treating asymptomatic patients without heart failure to prevent cardiovascular complications. At present, there is lack of direct evidence supporting perioperative BNP testing. Further research with randomised controlled trials is needed to confirm the benefit of BNP-guided management. Preoperative BNP testing may be considered in patients with RCRI above 0 undergoing intermediate or high-risk surgery. BNP-guided therapy is likely a beneficial addition to perioperative medicine. Its combination with β-blocker titration, RCRI and perioperative cardiovascular monitoring can be a major advance in reducing cardiac risk resulting in a dynamic, individualised optimisation process.

Incident heart failure in relation to vascular disease: insights from the Health, Aging, and Body Composition Study

AIMS

The contribution of heart failure (HF) unrelated to vascular disease to the overall HF burden in older adults is not well characterized. This was investigated in this study.

METHODS AND RESULTS

We assessed HF incidence and outcomes in 2895 participants of the Health ABC Study (age 74 ± 3 years, 48.4% men, 41.4% black) in relation to vascular disease (coronary, peripheral, or cerebrovascular disease) either present at baseline or developed prior to HF. During 11.4 years follow-up, 493 participants developed HF; 134 (27.2%) in participants without any prior vascular disease and 177 (36.8%) without coronary disease. Both baseline [hazard ratio (HR) 2.4, 95% confidence interval (CI) 1.9-2.8] and incident vascular disease (HR 4.3, 95% CI 3.6-5.2) were associated with HF. During a median follow-up of 2.1 years after HF onset, 67.5% participants died. Annual mortality after HF development was 21.3% in those with compared with 24.6% in those without vascular disease (HR 1.11, 95% CI 0.87-1.43; P = 0.399). There were 658 all-cause (436.3/1000 person-years) and 523 HF-related (346.4/1000 person-years) hospitalizations after HF development. There was no significant difference in hospitalizations between those with and without vascular disease [rate ratio (RR) 1.04, 95% CI 0.86-1.24 for all-cause, and RR 0.84 95% CI 0.69-1.02 for HF hospitalization]. HF with preserved EF was more common in participants without vascular disease (67.0% vs. 55.0%, P = 0.040).

CONCLUSION

A significant proportion of HF in older adults develops without prior vascular disease. Outcomes for these patients are poor compared with those with preceding vascular disease. These data suggest the need for more targeted HF prediction and prevention efforts.

Protective effect of rhBNP on intestinal injury in the canine models of sepsis

Sepsis is the leading cause of death in the intensive care units worldwide. Proinflammatory cytokines such as TNF (tumor necrosis factor)-α and IL (interleukin)-6 mediate the pathogenesis of septic shock characterized by hemodynamic instability and end-stage multi-organ functional failure. Brain natriuretic peptide (BNP) has been used as a diagnostic and prognostic biomarker in the cardiovascular disorders. Most recently, plasma level of BNP has also been used to predict outcomes of critical illnesses including sepsis. We have recently reported that human recombinant BNP (rhBNP) could protect lungs from acute proinflammatory injury in response to LPS-injection. In the current study, using LPS (lipopolysaccharide)-induced canine sepsis models, we further investigated the effect of rhBNP on intestinal injury and its potential mechanisms. We have found that rhBNP (5μg or 10μg/kg weight) could significantly reduce intestinal tissue damage in response to LPS-injection in the dog sepsis models through down-regulating proinflammatory cytokines TNF-α and IL-6 (5-10 fold decrease compared to LPS-injection only group) by a mechanism of suppressing IκB phosphorylation and NF-κB expression. These findings suggest that BNP protect intestinal tissues from endotoxin-induced hyper-inflammatory injury and thus, may be used as therapeutic agents for sepsis.

Treatment strategies for the prevention of heart failure

With the astounding morbidity and mortality associated with heart failure (HF), preventive approaches have been explored. Controlling hypertension to prevent HF is well-established, especially with sodium restriction and thiazide-based antihypertensive therapies showing potential advantages. Control of dyslipidemia with aggressive statin therapy is particularly beneficial in preventing HF in the setting of acute coronary syndrome. The HOPE study also established the benefit of ACE inhibitors in the prevention of HF in high-risk subjects. Meanwhile old data supporting tight glycemic control in preventing HF have not been confirmed, suggesting the complexity of diabetic cardiomyopathy. Avoiding tobacco use and other known cardiotoxins are likely helpful. While there has been substantial development in identifying biomarkers predicting future development of HF, therapeutic interdiction guided by biomarker levels have yet to be established, even though it offers hope in modulating the natural history of the development of HF in at-risk individuals.