Early diagnosis of acute coronary syndrome

Plasma levels of bactericidal/permeability-increasing protein correlate with systemic inflammation in acute coronary syndrome

Background

Neutrophils play important roles in atherosclerosis and atherothrombosis. Bactericidal/permeability-increasing protein (BPI) is mainly expressed in the granules of human neutrophils in response to inflammatory stress. This observational, cross-sectional study investigated the plasma level of BPI in patients with acute coronary syndrome (ACS) and its correlation with blood neutrophil counts and circulating inflammatory biomarkers.

Methods

A total of 367 patients who had acute chest pain and who were admitted to our hospital for coronary angiography (CAG) and/or percutaneous coronary intervention (PCI) from May 1, 2020 to August 31, 2020 were recruited. Among them, 256 had a cardiac troponin value above the 99th percentile upper reference limit and were diagnosed with ACS. The remaining patients (n = 111) were classified as non-ACS. The TIMI and GRACE scores were calculated at admission. The Gensini score based on CAG was used to determine atherosclerotic burden. Plasma levels of interleukin (IL)-1β, myeloperoxidase-DNA (MPO-DNA), high sensitivity C-reactive protein (hs-CRP), S100A8/A9, and BPI were measured using enzyme-linked immunosorbent assays. Correlations of plasma BPI levels with examination scores and levels of circulating inflammatory biomarkers were explored. Receiver operating characteristic (ROC) curve analysis was used to determine the diagnostic efficacy of BPI for ACS and myocardial infarction.

Results

Patients in the ACS group showed significantly higher plasma BPI levels compared to the non-ACS group (46.42 ± 16.61 vs. 16.23 ± 6.19 ng/mL, p < 0.05). Plasma levels of IL-1β, MPO-DNA, hs-CRP, and S100A8/A9 in the ACS group were also significantly higher than those in the non-ACS group (all p < 0.05). In addition, plasma BPI levels were positively correlated with the TIMI, GRACE, and Gensini scores (r = 0.176, p = 0.003; r = 0.320, p < 0.001; r = 0.263, p < 0.001, respectively) in patients with ACS. Plasma BPI levels were also positively correlated with blood neutrophil counts (r = 0.266, p < 0.001) and levels of circulating inflammatory biomarkers (IL-1β, r = 0.512; MPO-DNA, r = 0.452; hs-CRP, r = 0.554; S100A8/A9, r = 0.434; all p < 0.001) in patients with ACS. ROC curve analysis revealed that the diagnostic efficacy of BPI for ACS was not inferior to that of IL-1β, MPO-DNA, hs-CRP, S100A8/A9, or blood neutrophil counts. ROC analysis also showed that the diagnostic efficacy of BPI for myocardial infarction was not inferior to that of creatine kinase (CK)-MB or cardiac troponin I.

Conclusion

BPI is associated with systemic inflammation in ACS and may be involved in the process of atherosclerosis and atherothrombosis. The potential of BPI as a prognostic and diagnostic biomarker for ACS should be investigated in clinical settings.

Gut microbiome-based noninvasive diagnostic model to predict acute coronary syndromes

Background

Previous studies have shown that alterations in the gut microbiota are closely associated with Acute Coronary Syndrome (ACS) development. However, the value of gut microbiota for early diagnosis of ACS remains understudied.

Methods

We recruited 66 volunteers, including 29 patients with a first diagnosis of ACS and 37 healthy volunteers during the same period, collected their fecal samples, and sequenced the V4 region of the 16S rRNA gene. Functional prediction of the microbiota was performed using PICRUSt2. Subsequently, we constructed a nomogram and corresponding webpage based on microbial markers to assist in the diagnosis of ACS. The diagnostic performance and usefulness of the model were analyzed using boostrap internal validation, calibration curves, and decision curve analysis (DCA).

Results

Compared to that of healthy controls, the diversity and composition of microbial community of patients with ACS was markedly abnormal. Potentially pathogenic genera such as Streptococcus and Acinetobacter were significantly increased in the ACS group, whereas certain SCFA-producing genera such as Blautia and Agathobacter were depleted. In addition, in the correlation analysis with clinical indicators, the microbiota was observed to be associated with the level of inflammation and severity of coronary atherosclerosis. Finally, a diagnostic model for ACS based on gut microbiota and clinical variables was developed with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.963 (95% CI: 0.925-1) and an AUC value of 0.948 (95% CI: 0.549-0.641) for bootstrap internal validation. The calibration curves of the model show good consistency between the actual and predicted probabilities. The DCA showed that the model had a high net clinical benefit for clinical applications.

Conclusion

Our study is the first to characterize the composition and function of the gut microbiota in patients with ACS and healthy populations in Southwest China and demonstrates the potential effect of the microbiota as a non-invasive marker for the early diagnosis of ACS.

Aptamer-functionalized field-effect transistor biosensors for disease diagnosis and environmental monitoring

Nano-biosensors that are composed of recognition molecules and nanomaterials have been extensively utilized in disease diagnosis, health management, and environmental monitoring. As a type of nano-biosensors, molecular specificity field-effect transistor (FET) biosensors with signal amplification capability exhibit prominent advantages including fast response speed, ease of miniaturization, and integration, promising their high sensitivity for molecules detection and identification. With intrinsic characteristics of high stability and structural tunability, aptamer has become one of the most commonly applied biological recognition units in the FET sensing fields. This review summarizes the recent progress of FET biosensors based on aptamer functionalized nanomaterials in medical diagnosis and environmental monitoring. The structure, sensing principles, preparation methods, and functionalization strategies of aptamer modified FET biosensors were comprehensively summarized. The relationship between structure and sensing performance of FET biosensors was reviewed. Furthermore, the challenges and future perspectives of FET biosensors were also discussed, so as to provide support for the future development of efficient healthcare management and environmental monitoring devices.

Exploring the "gene-protein-metabolite" network of coronary heart disease with phlegm and blood stasis syndrome by integrated multi-omics strategy

Background: According to the theory of traditional Chinese medicine, phlegm and blood stasis (PBS) is the pathological basis for coronary heart disease (CHD). This study aimed to explore the biological basis of PBS syndrome in CHD. Methods: Using a strategy that integrated RNA-seq, DIA-based proteomics, and untargeted metabolomics on 90 clinic samples, we constructed a "gene-protein-metabolite" network for CHD-PBS syndrome. We expanded the sample size and validated the differential genes and metabolites in the network through enzyme-linked immunosorbent assay. Results: Our findings revealed that the "gene-protein-metabolite" network of CHD-PBS syndrome included 33 mRNAs, four proteins, and 25 metabolites. JNK1, FOS, CCL2, CXCL8, PTGS2, and CSF1 were all poorly expressed in the PBS group during the sequencing stage, whereas arachidonic acid (AA) was highly expressed. During the validation stage, JNK1, AP-1, CCL2, and CXCL8 were poorly expressed, whereas PTGS2, CSF1, and AA were highly expressed. The area under the receiver operating curve was as follows: CSF1 [0.9635, 95%CI (0.9295, 0.9976)] >JNK1 [0.9361, 95% CI (0.8749, 0.9972)] >CXCL8 [0.8953, 95% CI (0.8222, 0.9684)] > CCL2 [0.8458, 95% CI (0.7676, 0.9241)] >AP-1 [0.7884, 95%CI (0.6869, 0.8899)]. The logistic regression model composed of CSF1 and JNK1 showed the greatest diagnostic value and significance for PBS syndrome. Conclusion: PBS syndrome is characterized by low levels of FOS, AP-1, CCL2, CXCL8, and JNK1 and elevated levels of PTGS2 and CSF1, implying that the AA metabolism is abnormal and that the JNK/AP-1 pathway is inhibited. PBS syndromes, as a subtype of CHD, may have unique molecular changes. Background. Globally, coronary heart disease (CHD) is the leading cause of death, and this would likely continue until 2030 (Mirzaei et al., 2009, 95, 740-746). According to the disease course, CHD can be classified as chronic stable CHD (or chronic coronary syndrome) and acute coronary syndrome (ACS) (Katus et al., 2017; Knuuti, 2019). Although stable CHD is not as lethal as ACS, it has a varied incidence range and patients with CHD have prolonged angina. Some symptoms of stable angina are alleviated with pharmacological therapy, but it cannot eliminate recurrent angina (Rousan et al., 2017). The clinical outcomes were not significantly improved in patients who underwent revascularization compared with those who received optimal pharmacological therapy (Shaw et al., 2008; Antman and Braunwald, 2020). A bottleneck appears to exist in CHD treatment, and traditional Chinese medicine (TCM) can act as a favorable complement. Because of its individualized treatment approach, TCM is widely practiced in eastern civilizations (Teng et al., 2016). TCM has become a principal complement in western countries (Wieland et al., 2013). Like "disease" is used in western medicine, "syndrome" is used in TCM to comprehend anomalous human conditions on the basis of patients' symptoms, tongue, and pulse (Li et al., 2012). On the basis of disease-syndrome diagnose, a TCM doctor can subclassify CHD patients into various categories, such as phlegm and blood stasis (PBS) syndrome, cold congealing and Qi stagnation syndrome, and Qi stagnation and blood stasis syndrome. PBS syndrome has recently emerged as a hot research topic in the TCM field. Objective diagnosis, expert consultations, and efficacy evaluation scales have been developed for PBS syndrome (Ren et al., 2020; Liu et al., 2021; Zheng et al., 2022). The concept of "omics" originates from the genome. It refers to the vocabulary generated by biological molecules at different levels to describe high-sequence molecular biological data resources (Dai and Shen, 2022). RNA, protein, and metabolites decipher the essence of complex etiologies, and the integration of transcriptomics, proteomics, and metabolomics are becoming a promising research mode (Pan et al., 2022). Multi-omics studies have revealed the biological characteristics of APOE transgenic mice, bronchopulmonary dysplasia, and plant tolerant to heavy metals (Singh et al., 2016; Lal et al., 2018; Mohler et al., 2020). Over the past few years, many academic achievements related to CHD-PBS syndrome have been accrued in the single-omic area. For example, Zhou identified the differential metabolites between PBS syndrome and Qi and Yin deficiency syndrome by using the urine samples of 1072 volunteers. Some of the specific metabolites of PBS syndrome are pyroglutamic acid, glutaric acid, glucose, mannitol, and xanthine (Zhou et al., 2019). Li's metabolomic study suggested that valine, leucine, isoleucine, and glycerol phospholipid metabolism could represent PBS syndrome (Zheng et al., 2022). Although some progress has been made in the understanding of PBS syndrome in CHD through the studies conducted, some issues still exist, such as a single-omics level, a lack of in-depth research, an inability to verify each other's research results, and a lack of validation of research conclusions. Overall, a systematic description of the biological foundation of PBS syndrome is lacking. Thus, the present study utilizes system biology methodologies and constructs a multi-omics network by integrating differential genes, proteins, and metabolites to systematically and comprehensively reveal the biological basis of CHD-PBS syndrome. The current study explored 1) the characteristics of the transcriptome, proteome, and metabolome for CHD-PBS syndrome; 2) the "gene-protein-metabolite" network based on differential genes (DGs), differential proteins (DPs), and differential metabolites (DMs); 3) the key biological process and metabolic pathway most related to PBS syndrome; and 4) quantitative results and the diagnostic potential of biomarkers for PSB syndrome. Materials and methods. Multi-omics sequencing, bioinformatics analysis, and clinical validation research strategy. We collected the blood samples from healthy subjects as well as CHD patients with PBS and non-phlegm and blood stasis (NPBS) syndrome to compare the differences between them by subjecting the samples to the transcriptome, proteome, and metabolomics analyses. Bioinformatics analysis identified differential molecules as well as related biological processes and pathways. Next, the "gene-protein-metabolite" network was constructed using the MetaboAnalyst database, String database, and Cytoscape software. We selected molecules with strong centrality and biological association as potential PBS syndrome biomarkers and recruited more volunteers for further validation by enzyme-linked immunosorbent assay (ELISA). Finally, the ROC curve was utilized to assess the level and diagnostic efficacy of various molecules (Figure 1).

Treatment Seeking Behaviors and Associated Factors among Patients Experiencing Acute Coronary Syndrome Using Health Belief Model in Addis Ababa, Ethiopia

Background

Acute coronary syndrome (ACS) is a life-threatening condition. The mortality rate will be reduced if immediate treatment is provided. Patients' awareness of ACS is limited, so they do not seek help as quite often as they should. The level of treatment seeking behavior and associated factors among ACS patients admitted to three hospitals in Addis Ababa, Ethiopia, were assessed using a health belief model.

Methods

A cross-sectional study was conducted among 330 ACS patients from November 2019 to December 2020. Sociodemographic and clinical variables data were extracted using pre-tested checklist. The outcome and other variables data were collected using the checklist and structured questionnaire. The data were entered into Epi-data 3.1 and exported to STATA 17.1 for analysis. Descriptive statistics relevant to the variable was performed. A multivariable logistic regression was used to identify factors associated with treatment seeking behavior.

Results

This study revealed that the mean time from symptom onset to arrival at the emergency unit (EU) was 24 ± 19.5 hours, slightly < half of the participants (n=149, 45.1 %) had adequate treatment seeking behavior. Perceived threat (AOR=1.03,95% CI:1.01–1.06, p=0.002), perceived benefits (AOR=1.09, 95%CI: 1.02–1.0, p≤0.001), self-efficacy (AOR=1.16, 95% CI :1.01- 1.22, p≤0.001), education (AOR=2.2,95%CI:1.31–3.9, p≤0.01) self-autonomy (AOR=3.1,95%CI:1.82–5.4, p<.001) and no depression (AOR=1.9,95%CI:1.1–3.3, p≤0.05) were found to have significantly association with adequate treatment seeking behavior.

Conclusion

This study indicates, less than half of ACS patients had adequate treatment seeking behavior. Thus, context-specific behavioral interventions, along with public awareness campaigns about ACS, should be implemented.

Imaging in experimental models of diabetes

Translational medicine, experimental medicine and experimental animal models, in particular mice and rats, represent a multidisciplinary field that has made it possible to achieve, in the last decades, important scientific progress. In this review, we have summarized the most frequently used imaging animal models, such as ultrasound (US), micro-CT, MRI and the optical imaging methods, and their main implications in diagnostic and therapeutic fields, with a particular focus on diabetes mellitus, a multifactorial disease extremely widespread among the general population.

Identification of a Novel Theranostic Signature of Metabolic and Immune-Inflammatory Dysregulation in Myocardial Infarction, and the Potential Therapeutic Properties of Ovatodiolide, a Diterpenoid Derivative

Myocardial infarction (MI) is a multifactorial global disease, recognized as one of the leading causes of cardiovascular morbidity and mortality. Timely and correct diagnoses and effective treatments could significantly reduce incidence of complications and improve patient prognoses. In this study, seven unconventional differentially expressed genes (DEGs) (MAN2A2, TNFRSF12A, SPP1, CSNK1D, PLAUR, PFKFB3, and CXCL16, collectively termed the MTSCPPC signature) were identified through integrating DEGs from six MI microarray datasets. The pathological and theranostic roles of the MTSCPPC signature in MI were subsequently analyzed. We evaluated interactions of the MTSCPPC signature with ovatodiolide, a bioactive compound isolated from Anisomeles indica (L.) Kuntze, using in silico molecular docking tools and compared it to specific inhibitors of the members of the MTSCPPC signature. Single-cell transcriptomic analysis of the public databases revealed high expression levels of the MTSCPPC signature in immune cells of adult human hearts during an MI event. The MTSCPPC signature was significantly associated with the cytokine–cytokine receptor interactions, chemokine signaling, immune and inflammatory responses, and metabolic dysregulation in MI. Analysis of a micro (mi)RNA regulatory network of the MTSCPPC signature suggested post-transcriptional activation and the roles of miRNAs in the pathology of MI. Our molecular docking analysis suggested a higher potential for ovatodiolide to target MAN2A2, CSNK1D, and TNFRSF12A. Collectively, the results derived from the present study further advance our understanding of the complex regulatory mechanisms of MI and provide a potential MI theranostic signature with ovatodiolide as a therapeutic candidate.

Association between epicardial adipose tissue density and characteristics of coronary plaques assessed by coronary computed tomographic angiography

To investigate the relationship between the epicardial adipose tissue density (EATD) and the coronary plaque components as assessed by coronary computed tomographic angiography (CCTA). The study cohort included 240 patients with chest pain or precardiac discomfort (mean age 62.01 ± 7.45 years, 55.83% male). Patients were assigned to the high-risk plaque (HRP) group (n = 133) or non-HRP group (n = 107). All patients underwent CCTA to assess plaque composition, and quantitative analysis of EATD and epicardial adipose tissue volume (EATV). Age, gender, EATV, EATD, diabetes history and family history were all correlated with HRP. There was no linear correlation between EATD and EATV among the subjects (R² = 0.008, p = 0.177), but there was a curvilinear correlation (R² = 0.102, p < 0.001). After adjusting other traditional factors, and we observed robust associations of EAT volume and density with HRP (all p < 0.05). For per 1 standard deviation increase in EATD, the risk of HRP was 3.120 times the risk than that of non-HRP. For per 1 standard deviation increase in EATV, the risk of HRP was 1.499 times the risk than that of non-HRP. The receiver operating characteristic curve showed that EATD was more predictive of HRP than EATV (AUC = 0.761, 95% CI 0.701-0.822). Our study found that EATD and EATV are both independent factors affecting the presence of HRPs, and EATD had a high predictive value for the presence of HRP.

ABHD4-Regulating RNA Panel: Novel Biomarkers in Acute Coronary Syndrome Diagnosis

Background: Acute coronary syndrome (ACS) is a major cause of death all over the world. STEMI represents a type of myocardial infarction with acute ST elevation. We aimed to assess the predictive power of potential RNA panel expression in acute coronary syndrome. Method: We used in silico data analysis to retrieve RNAs related to glycerophospholipid metabolism dysregulation and specific to ACS that results in the selection of Alpha/Beta hydrolase fold domain4 (ABHD4) mRNA and its epigenetic regulators (Foxf1 adjacent noncoding developmental regulatory RNA (FENDRR) lncRNA, miRNA-221, and miRNA-197). We assessed the expression of the serum RNA panel in 68 patients with ACS, 21 patients with chest pain due to non-cardiac causes, and 21 healthy volunteers by quantitative real-time polymerase chain reaction. Results: The study data showed significant down regulation in the expression of the serum levels of FENDRR lncRNA and miRNA-221-3p by 120-fold and 22-fold in Unstable angina (UA) in comparison with healthy volunteers, and by 8.6-fold and 2-fold in ST segment elevation myocardial infarction (STEMI) patients versus UA; concomitant upregulation in the expression of ABHD4 mRNA and miRNA-197-5p by 444-fold and 10-fold in UA compared with healthy volunteers, and by 1.54-fold and 4.5-fold in STEMI versus unstable angina. Performance characteristics analysis showed that the ABHD4-regulating RNA panel were potential biomarkers for prediction of ACS. Moreover, there was a significant association between the 2 miRNAs and ABHD4 mRNA and the regulating FENDRR lncRNA. Conclusion: Collectively, ABHD4 mRNA regulating RNA panel based on putative interactions seems to be novel non-invasive biomarkers that could detect ACS early and stratify severity of the condition that could improve health outcome.

Therapeutic Efficacy and Safety of Safflower Injection in the Treatment of Acute Coronary Syndrome

Background

Safflower injection (SFI), a popular Chinese patent drug, is commonly used to treat acute coronary syndromes (ACSs) in China. The research seeks to scientifically estimate the clinical efficacy of SFI for ACS patients.

Methods

Eight electronic databases were retrieved for eligible research from the founding date to September 8, 2020. Odds ratio (OR) was adopted to assess the total effective rate, ECG improvement, and adverse reaction, and mean difference (MD) was used for assessing the hemorheology indexes as well as the LVEF.

Results

Sixteen randomized controlled trials involving 1620 sufferers with ACS were incorporated. The outcomes showed that, in comparison to conventional medication alone, SFI combined with conventional treatment remarkably enhanced the total effective rate (OR = 3.66, 95% CI [2.73, 4.90], P < 0.00001), ECG improvement (OR = 2.85, 95% CI [2.04, 3.99], P < 0.00001), and LVEF (MD = 5.13, 95% CI [3.73, 6.53], P < 0.00001). Moreover, SFI combined with conventional treatment significantly decreased hemorheology indexes including BV (MD = −0.95, 95% CI [−1.76, −0.13], P=0.02), HCT (MD = −2.37, 95% CI [−3.25, −1.50], P < 0.00001), FIB (MD = −0.44, 95% CI [−0.60, −0.29], P < 0.00001), and PAR (OR = −7.65, 95% CI [−10.16, −5.14], P < 0.00001). However, no notable contrast was observed to link the experimental and the control team for PV (MD = −0.42, 95% CI [−0.83, 0.00], P=0.05) and adverse reactions (OR = 0.59, 95% CI [0.13, 2.74], P=0.50).

Conclusion

Despite the limitations that existed in this meta-analysis, the outcomes demonstrated that SFI and conventional combined medication is an effective and relatively safe therapy for ACS sufferers.

Serum Metabonomic Study of Patients With Acute Coronary Syndrome Using Ultra-Performance Liquid Chromatography Orbitrap Mass Spectrometer

Acute coronary syndrome (ACS) can cause arrhythmia, heart failure, and even sudden death. Our aim in this study was to identify potential metabolic biomarkers in patients with ACS. The serum metabonomics approach based on ultra-performance liquid chromatography (UPLC)/Orbitrap mass spectrometer (MS) was used to analyze the serum samples from 45 patients with ACS and 29 healthy controls. Multivariate statistical analysis was used to screen for ACS biomarkers. In total, 69 biomarkers were identified to be enriched in 19 metabolic pathways; 43 biomarkers were significantly up-regulated, while 26 biomarkers were significantly down-regulated in the ACS group. The main classes were lyso-sphingolipid (SM), cinnamic acids, cholines, and primary amides. Receiver operating characteristic (ROC) curve analysis showed that lysoPC(20:4(8Z,11Z,14Z,17Z)/0:0) (ROC area under the curve, AUC = 0.936), SM(d18:0/16:0) (ROC AUC = 0.932), and SM(d18:1/14:0) (ROC AUC = 0.923) had a high ACS diagnostic ability. The AUC value of the diagnostic model constructed using these combined biomarkers was 0.96. Therefore, these biomarkers may improve the diagnostic efficacy of ACS. The findings of this study also implied that glycerophospholipid metabolism; the biosynthesis of unsaturated fatty acids; linoleic acid metabolism; and valine, leucine, and isoleucine biosynthesis played important roles in ACS. Network analysis by ingenuity pathway analysis (IPA) showed these biomarkers were correlated to the cardiac hypertrophy signaling pathway, ERK/MAPK signaling pathway, NF-kappa B signaling pathway, nitric oxide (NO) signaling pathway in cardiovascular system, and TLR-signaling pathway. These findings will help to improve the ability of accurate diagnosis and intervention of ACS.

Diagnostic value and prognostic significance of CTRP9 combined with pentraxin-3 in acute coronary syndrome

The present study aimed to explore the diagnostic value and prognostic significance of C1q/tumor necrosis factor-related protein 9 (CTRP9) combined with pentraxin-3 (PTX-3) in acute coronary syndrome (ACS). A total of 137 patients with coronary heart disease and chest pain were included. Among them, seventy-nine patients with ACS were allocated into a study group and fifty-eight patients with non-cardiac chest pain (NCCP) were allocated into a control group. The serum CTRP9, PTX-3 levels were quantified by ELISA, and their correlation with other ACS-related indexes, diagnostic value for ACS and predictive significance for poor prognosis were analyzed. In addition, the risk factors of the poor prognosis of ACS patients were studied. CTRP9 was lowly expressed and PTX-3 was highly expressed in the serum of ACS patients. CTRP9 was negatively correlated with cardiac troponin I (cTnI), creatine kinase-MB (CK-MB) and high-sensitivity C-reactive protein (hs-CRP) (P<0.05), while PTX-3 was positively correlated with them (P<0.05). Combined detection of CTRP9 and PTX-3 was of high value in the diagnosis and prognosis of ACS patients. In addition, CTRP9 and PTX-3 were independent risk factors for the poor prognosis of ACS. Patients with ACS had lower CTRP9 expression and higher PTX-3 expression than those without ACS. Moreover, the combined detection of CTRP9 and PTX-3 can better evaluate the diagnosis and prognosis of ACS patients.

Prognostic role of plasma galectin-3 levels in acute coronary syndrome

Aim:

Cystatin C, neutrophil gelatinase-associated lipocalin and galectin-3 have emerged as biomarker candidates to predict cardiovascular outcomes and mortality in the general population as well as in patients with coronary artery or renal disease. However, their predictive role and clinical utility in patients with acute coronary syndromes alone or in combination beyond currently used risk scores remains to be determined.

Methods and results:

Cystatin C, neutrophil gelatinase-associated lipocalin, and galectin-3 were measured in plasmas of 1832 patients at the time of presentation with acute coronary syndromes requiring percutaneous coronary intervention or coronary artery bypass grafting. The primary outcomes were major adverse cardiac and cerebrovascular events (defined as the composite of all-cause mortality, cerebrovascular events, any repeat revascularization or myocardial infarction) and all-cause mortality after 1 year and occurred in 192 (10.5%) and 78 (4.3%) of patients, respectively. All three biomarkers were increased in those with major adverse cardiac and cerebrovascular events compared with those without (p&lt;0.001). However, only galectin-3 (all-cause mortality: hazard ratio=1.027 (95% confidence interval (1.011–1.043); p=0.001), major adverse cardiac and cerebrovascular events: hazard ratio=1.025 (95% confidence interval (1.012–1.037); p&lt;0.001)) but not cystatin C nor neutrophil gelatinase-associated lipocalin emerged as independent predictors of both major adverse cardiac and cerebrovascular events and death. The risks were particularly high in the highest quartile of galectin-3. The integration of galectin-3 into the global registry of acute coronary events (GRACE) score improved the prediction of major adverse cardiac and cerebrovascular events and all-cause mortality significantly. The areas under the receiver operator characteristics curves increased from 0.6701 to 0.6932 for major adverse cardiac and cerebrovascular events (p=0.0474) and from 0.804 to 0.8199 for all-cause mortality (p=0.0197). Finally, we applied net reclassification improvement index using different cut-offs for major adverse cardiac and cerebrovascular events which showed negative results (for the cut-offs of 5% and 15%, net reclassification improvement index 0.028, p=0.586, for the cut-offs of 10% and 20%, net reclassification improvement index 0.072, p=0.1132 and for the cut-offs of 10% and 30% the net reclassification improvement index is 0.0843, p=0.077).

Conclusion:

In acute coronary syndromes patients, galectin-3 has moderate prognostic accuracy, provides statistically significant incremental value in some, but not all models, and that the magnitude of any improvement would seem of questionable clinical value.

Feature selection and risk prediction for patients with coronary artery disease using data mining

Coronary artery disease (CAD) is an important cause of mortality across the globe. Early risk prediction of CAD would be able to reduce the death rate by allowing early and targeted treatments. In healthcare, some studies applied data mining techniques and machine learning algorithms on the risk prediction of CAD using patient data collected by hospitals and medical centers. However, most of these studies used all the attributes in the datasets which might reduce the performance of prediction models due to data redundancy. The objective of this research is to identify significant features to build models for predicting the risk level of patients with CAD. In this research, significant features were selected using three methods (i.e., Chi-squared test, recursive feature elimination, and Embedded Decision Tree). Synthetic Minority Over-sampling Technique (SMOTE) oversampling technique was implemented to address the imbalanced dataset issue. The prediction models were built based on the identified significant features and eight machine learning algorithms, utilizing Acute Coronary Syndrome (ACS) datasets provided by National Cardiovascular Disease Database (NCVD) Malaysia. The prediction models were evaluated and compared using six performance evaluation metrics, and the top-performing models have achieved AUC more than 90%. Graphical abstract.

Clinical risk scores identify more patients at risk for cardiovascular events within 30 days as compared to standard ACS risk criteria: the WESTCOR study

AIMS

Troponin-based algorithms are made to identify myocardial infarctions (MIs) but adding either standard acute coronary syndrome (ACS) risk criteria or a clinical risk score may identify more patients eligible for early discharge and patients in need of urgent revascularization.

METHODS AND RESULTS

Post-hoc analysis of the WESTCOR study including 932 patients (mean 63 years, 61% male) with suspected NSTE-ACS. Serum samples were collected at 0, 3, and 8-12 h and high-sensitivity cTnT (Roche Diagnostics) and cTnI (Abbott Diagnostics) were analysed. The primary endpoint was MI, all-cause mortality, and unplanned revascularizations within 30 days. Secondary endpoint was non-ST-elevation myocardial infarction (NSTEMI) during index hospitalization. Two combinations were compared: troponin-based algorithms (ESC 0/3 h and the High-STEACS algorithm) and either ACS risk criteria recommended in the ESC guidelines, or one of eleven clinical risk scores, HEART, mHEART, CARE, GRACE, T-MACS, sT-MACS, TIMI, EDACS, sEDACS, Goldman, and Geleijnse-Sanchis. The prevalence of primary events was 21%. Patients ruled out for NSTEMI and regarded low risk of ACS according to ESC guidelines had 3.8-4.9% risk of an event, primarily unplanned revascularizations. Using HEART score instead of ACS risk criteria reduced the number of events to 2.2-2.7%, with maintained efficacy. The secondary endpoint was met by 13%. The troponin-based algorithms without evaluation of ACS risk missed three-index NSTEMIs with a negative predictive value (NPV) of 99.5% and 99.6%.

CONCLUSION

Combining ESC 0/3 h or the High-STEACS algorithm with standardized clinical risk scores instead of ACS risk criteria halved the prevalence of rule-out patients in need of revascularization, with maintained efficacy.

Absolute Change in High-Sensitivity Cardiac Troponin I at Three Hours After Presentation is Useful for Diagnosing Acute Myocardial Infarction in the Emergency Department

Background

A rise and/or fall in cardiac troponin value with at least one value above the 99th percentile upper reference limit is essential for acute myocardial infarction (AMI) diagnosis. We evaluated the clinical usefulness of serial high-sensitivity cardiac troponin I (hs-cTnI) measurements in AMI diagnosis, in terms of the predictability of absolute and relative changes.

Methods

For this retrospective, forward observational study, we enrolled 281 patients older than 18 years who presented with chest pain at the emergency department (ED) between August 2015 and December 2016. The patients were grouped as AMI and non-AMI, and 73 (26%) were diagnosed as having AMI. Hs-cTnI (Abbott Diagnostics, Abbott Park, IL, USA) was measured at presentation and 3 hours later. We assessed the diagnostic performance of the absolute and relative changes in hs-cTnI.

Results

The cut-off values to predict AMI were 16.2 ng/L and 42.1% for the absolute and relative hs-cTnI changes, respectively. The area under the curve of hs-cTnI for AMI diagnosis was larger for absolute changes than for relative changes [0.96 (95% confidence interval [CI], 0.92–0.98) vs 0.89 (95% CI, 0.85–0.93)] (P=0.014).

Conclusions

The absolute hs-cTnI change at 3 hours after presentation was superior to the relative change, and a rise and/or fall in hs-cTnI of >16.2 ng/L at 3 hours after presentation was useful to identify AMI in patients presenting at the ED.

Myoglobin for Detection of High-Risk Patients with Acute Myocarditis

There is an unmet need for accurate and practical screening to detect myocarditis. We sought to test the hypothesis that the extent of acute myocarditis, measured by late gadolinium enhancement (LGE) on cardiac magnetic resonance imaging (CMR), can be estimated based on routine blood markers. A total of 44 patients were diagnosed with acute myocarditis and included in this study. There was strong correlation between myoglobin and LGE (r_s = 0.73 [95% CI 0.51; 0.87], p < 0.001), while correlation was weak between LGE and TnT-hs (r_s = 0.37 [95% CI 0.09; 0.61], p = 0.01). Receiver operating curve (ROC) analysis determined myoglobin ≥ 87 μg/L as cutoff to identify myocarditis (92% sensitivity, 80% specificity). The data were reproduced in an established model of coxsackievirus B3 myocarditis in mice (n = 26). These data suggest that myoglobin is an accurate marker of acute myocarditis. Graphical Abstract Receiver operating curve analysis determined myoglobin ≥ 87 μg/L as cutoff to identify myocarditis and these data were reproduced in an established model of coxsackievirus B3 myocarditis in mice: CMRI, cardiac magnetic resonance imaging; Mb, myoglobin; LGE, late gadolinium enhancement; ROC, receiver operating curve analysis.

Platelet Carcinoembryonic Antigen Cell Adhesion Molecule 5 (CEACAM5) as a Possible Novel Diagnostic Tool for Evaluation of Acute Coronary Syndrome

Background

Acute coronary syndrome (ACS) occurs approximately every 40 seconds, and was an underlying cause of death in 1 out of every 7 deaths. More accurate indicators are needed to distinguish patients with ACS from patients manifesting negative changes in electrocardiogram (ECG) and myocardial enzymes. This study aimed to investigate whether the expression of platelet carcinoembryonic antigen cell adhesion molecule-5 (CEACAM5/CEA/CD66e) could help predict ACS.

Material/Methods

We enrolled 82 participants (mean age 60 years, 33 females and 49 males). The expression of CEA on washed human platelets was assessed using two-color flow cytometry. The CEA levels on platelets and in serum of these 82 consecutive patients were detected using two-color whole-blood flow cytometry analysis and a custom-made Luminex multiplex assay, respectively.

Results

CEA was expressed on the surface of human platelets. The expression of platelet CEA (P<0.01), but not serum CEA (P=0.30), was significantly higher in patients with ACS compared to patients with normal coronary artery. Increased platelet CEA levels could serve as a new independent indicator for ACS (P=0.0003). Platelet CEA testing (P=0.000002), as well as cardiac troponin I (cTnI) (P=0.0005), can diagnose ACS with high sensitivity and specificity, and, combined with cTnI (P<0.0001), can improve the diagnostic value.

Conclusions

Platelet CEA expression was higher in individuals presenting with ACS. Hence, platelet CEA might be a novel and reliable biomarker for ACS. Large-scale studies are needed to confirm this hypothesis.

A Clinically Evaluated Interferometric Continuous-Wave Radar System for the Contactless Measurement of Human Vital Parameters

Vital parameters are key indicators for the assessment of health. Conventional methods rely on direct contact with the patients’ skin and can hence cause discomfort and reduce autonomy. This article presents a bistatic 24 GHz radar system based on an interferometric six-port architecture and features a precision of 1 µm in distance measurements. Placed at a distance of 40 cm in front of the human chest, it detects vibrations containing respiratory movements, pulse waves and heart sounds. For the extraction of the respiration rate, time-domain approaches like autocorrelation, peaksearch and zero crossing rate are compared to the Fourier transform, while template matching and a hidden semi-Markov model are utilized for the detection of the heart rate from sphygmograms and heart sounds. A medical study with 30 healthy volunteers was conducted to collect 5.5 h of data, where impedance cardiogram and electrocardiogram were used as gold standard for synchronously recording respiration and heart rate, respectively. A low root mean square error for the breathing rate (0.828 BrPM) and a high overall F1 score for heartbeat detection (93.14%) could be achieved using the proposed radar system and signal processing.

Artificial Intelligence in Cardiovascular Medicine

PURPOSE OF REVIEW

The ripples of artificial intelligence are being felt in various sectors of human life. Machine learning, a subset of artificial intelligence, extracts information from large databases of information and is gaining traction in various fields of cardiology. In this review, we highlight noteworthy examples of machine learning utilization in echocardiography, nuclear cardiology, computed tomography, and magnetic resonance imaging over the past year.

RECENT FINDINGS

In the past year, machine learning (ML) has expanded its boundaries in cardiology with several positive results. Some studies have integrated clinical and imaging information to further augment the accuracy of these ML algorithms. All the studies mentioned in this review have clearly demonstrated superior results of ML in relation to conventional approaches for identifying obstructions or predicting major adverse events in reference to conventional approaches. As the influx of data arriving from gradually evolving technologies in health care and wearable devices continues to be more complex, ML may serve as the bridge to transcend the gap between health care and patients in the future. In order to facilitate a seamless transition between both, a few issues must be resolved for a successful implementation of ML in health care.

Association between neutrophil-lymphocyte ratio and arterial stiffness in patients with acute coronary syndrome

The aim of the present study was to assess the association between neutrophil–lymphocyte ratio (NLR) and arterial stiffness and provide a predictive index for diagnosing atherosclerosis in patients with acute coronary syndrome (ACS). We enrolled patients with ACST who were confirmed by coronary angiography. Data were collected by questionnaire and blood indexes. Brachial-ankle pulse wave velocity (baPWV) was measured using BP-203RPE III network arteriosclerosis detection equipment. Correlation analysis of traditional cardiovascular risk factors and baPWV was performed, and multivariate line regression analysis was conducted to explore the relevant factors for baPWV. A total of 210 patients were included in the final analyses according to the inclusion criteria. Patients with a high baPWV had a lower lymphocyte count than those with a low baPWV (1.2 ± 0.4 vs. 1.4 ± 0.4, P = 0.004). The NLRs of the low and high bvPWV groups were 3.1 ± 1.5 and 4.0 ± 2.1, respectively; no significant difference was observed. The results suggest that there is a positive relationship between baPWV and NLR (r = 0.403, P = 0.005) and neutrophils (r = 0.319, P = 0.016). Multivariate line regression suggested that NLR was positively associated with baPWV (B = 0.372, P = 0.000). The present results indicate that NLR is independently associated with arterial stiffness in patients with ACS. NLR, an inexpensive, easily measurable, widely available biomarker, could be an additional tool for assessing cardiovascular risk in clinical practice.

Artificial Intelligence in Cardiovascular Imaging: JACC State-of-the-Art Review

Data science is likely to lead to major changes in cardiovascular imaging. Problems with timing, efficiency, and missed diagnoses occur at all stages of the imaging chain. The application of artificial intelligence (AI) is dependent on robust data; the application of appropriate computational approaches and tools; and validation of its clinical application to image segmentation, automated measurements, and eventually, automated diagnosis. AI may reduce cost and improve value at the stages of image acquisition, interpretation, and decision-making. Moreover, the precision now possible with cardiovascular imaging, combined with "big data" from the electronic health record and pathology, is likely to better characterize disease and personalize therapy. This review summarizes recent promising applications of AI in cardiology and cardiac imaging, which potentially add value to patient care.

Role of High-sensitivity Cardiac Troponin in Acute Coronary Syndrome

Chest pain is one of the most common reasons for an emergency room (ER) visit in the US, with almost 6 million ER visits annually. High-sensitivity cardiac troponin (hscTn) assays have the ability to rapidly rule in or rule out acute coronary syndrome with improved sensitivity, and they are increasingly being used. Though hscTn assays have been approved for use in European, Australian, and Canadian guidelines since 2010, the FDA only approved their use in 2017. There is no consensus on how to compare the results from various hscTn assays. A literature review was performed to analyze the advantages and limitations of using hscTn as a standard biomarker to evaluate patients with suspected ACS in the emergency setting.

Characteristics and Outcomes of Patients Hospitalized With Suspected Acute Coronary Syndrome in Whom the Diagnosis is not Confirmed

Patients admitted with suspected acute coronary syndrome (ACS) in whom the diagnosis is not confirmed are poorly characterized. In a contemporary registry of consecutive patients hospitalized with suspected ACS as the primary diagnosis, we assessed characteristics on admission and in-hospital and 6-month mortality of patients discharged with other diagnoses and compared this subgroup with true ACS patients. Of 2557 patients included, 9.0% were discharged with a non-ACS diagnosis such as nonspecific chest pain, myopericarditis, stress cardiomyopathy, hemodynamic disturbances, heart failure, myocardial, pulmonary or valvular disease, or others. Compared with true ACS patients, those with other diagnoses were younger, more often female, and had less cardiovascular risk factors. Both groups had comparable rates of nonchest pain presentation and similar hemodynamic characteristics on admission. Non-ACS patients presented less often with Q waves or with ST-segment or T-wave changes and had a lower Global Registry of Acute Coronary Events score than true ACS patients. In-hospital (4.3 vs 4.0%, respectively, p = 0.834) and 6-month (5.4 vs 8.0%, respectively, p = 0.163) mortality rates were comparable in both groups. However, if patients in the non-ACS group were divided into subgroups with nonspecific chest pain (6.2% of total) or other diagnoses (2.8% of total), major differences in in-hospital (0.0 vs 13.9%, respectively, p < 0.001) and 6-month (0.7 vs 15.7%, respectively, p < 0.001) mortality rates would become apparent and remain after multivariable adjustment. In conclusion, in a non-negligible proportion of patients hospitalized with suspected ACS, this diagnosis is not confirmed. Prognosis of these patients follows a bimodal pattern, being excellent in those with nonspecific chest pain but worse than that of true ACS patients in the rest. Efforts are necessary to ensure prompt identification and early risk stratification of these patients allowing appropriate management decisions.

Comparison between creatine kinase MB, heart-type fatty acid-binding protein, and cardiac troponin T for detecting myocardial ischemic injury after cardiac surgery

BACKGROUND

Heart-type fatty acid-binding protein (H-FABP) is a cytoplasmic protein and is released form necrotic cardiac myocytes, as well as ischemic cardiac myocytes. In this study, we compared creatine kinase MB (CK-MB), H-FABP, and cardiac troponin T (cTnT) after coronary artery bypass grafting (CABG), heart valve surgery, or septal defect surgery to evaluate the difference in detecting myocardial injury between three markers.

METHODS

A total of 69 patients (CABG, 32; valve surgery, 27; and septal defect surgery, 10) were prospectively enrolled. Blood samples were taken at specific intervals.

RESULTS

Mean amount (AUC_0-72h) of CK-MB and cTnT released for 72 h in the patients with valve surgery were 2446 h·ng/ml and 93.2 h·ng/ml, which were significantly larger than those in the patients with CABG or septal defect surgery (p < .05). Mean amount (AUC_0-72h) of H-FABP released for 72 h in the patients with CABG was 1939 h·ng/ml, which was significantly larger than that in the patients with septal defect surgery (700.1 h·ng/ml) (p < .05).

CONCLUSION

H-FABP would be a more useful marker for detecting myocardial ischemic injury than CK-MB and cTnT. CK-MB and cTnT would be more sensitive to myocardial injury with surgical trauma than with ischemic injury in the patients with cardiac surgery.

High-Sensitivity Cardiac Troponin I and Clinical Risk Scores in Patients With Suspected Acute Coronary Syndrome

BACKGROUND

High-sensitivity cardiac troponin assays can help to identify patients who are at low risk of myocardial infarction in the emergency department. We aimed to determine whether the addition of clinical risk scores would improve the safety of early rule-out pathways for myocardial infarction.

METHODS

In 1935 patients with suspected acute coronary syndrome, we evaluated the safety and efficacy of 2 rule-out pathways alone or in conjunction with low-risk TIMI (Thrombolysis In Myocardial Infarction) (0 or 1), GRACE (Global Registry of Acute Coronary Events) (≤108), EDACS (Emergency Department Assessment of Chest Pain Score) (<16), or HEART (History, ECG, Age, Risk factors, Troponin) (≤3) scores. The European Society of Cardiology 3-hour pathway uses a single diagnostic threshold (99th percentile), whereas the High-STEACS (High-Sensitivity Troponin in the Evaluation of Patients With Acute Coronary Syndrome) pathway applies different thresholds to rule out (<5 ng/L) and rule in (>99th percentile) myocardial infarction.

RESULTS

Myocardial infarction or cardiac death during the index presentation or at 30 days occurred in 14.3% of patients (276/1935). The European Society of Cardiology pathway ruled out 70%, with 27 missed events giving a negative predictive value of 97.9% (95% CI, 97.1-98.6). The addition of a HEART score ≤3 reduced the proportion ruled out by the European Society of Cardiology pathway to 25% but improved the negative predictive value to 99.7% (95% CI, 99.0-100; P<0.001). The High-STEACS pathway ruled out 65%, with 3 missed events for a negative predictive value of 99.7% (95% CI, 99.4-99.9). No risk score improved the negative predictive value of the High-STEACS pathways, but all reduced the proportion ruled out (24% to 47%; P<0.001 for all).

CONCLUSIONS

Clinical risk scores significantly improved the safety of the European Society of Cardiology 3-hour pathway, which relies on a single cardiac troponin threshold at the 99th percentile to rule in and rule out myocardial infarction. Where lower thresholds are used to rule out myocardial infarction, as applied in the High-STEACS pathway, risk scores halve the proportion of patients ruled out without improving safety.

CLINICAL TRIAL REGISTRATION

URL: https://www.clinicaltrials.gov . Unique identifier: NCT01852123.

German contribution to development and innovations in the management of acute myocardial infarction and cardiogenic shock

Treatment of acute coronary syndromes has evolved over time leading to a significantly reduced mortality. Multiple major trials have been performed in Germany leading to new treatment strategies in acute coronary syndromes including cardiogenic shock. This review article will summarize major trials and their impact on guideline recommendations in acute myocardial infarction highlighting reperfusion strategies, antiplatelet regimens, prognosis assessment and also mechanical circulatory support in stable infarction patients and in cardiogenic shock.

Contemporary Emergency Department Management of Patients with Chest Pain: A Concise Review and Guide for the High-Sensitivity Troponin Era

This article synthesizes current best evidence for the evaluation of patients with suspected acute coronary syndrome (ACS) using high-sensitivity troponin assays, enabling physicians to effectively incorporate them into practice. Unlike conventional assays, high-sensitivity assays can precisely measure blood cardiac troponin concentrations in the vast majority of healthy individuals, facilitating the creation of rapid diagnostic algorithms. Very low troponin concentrations on presentation accurately rule out acute myocardial infarction (AMI) and enable the discharge of approximately 20% of patients after a single test, whereas an additional 30%-40% of patients can be safely discharged after short-interval serial sampling in as little as 1 or 2 hours. In contrast, highly abnormal troponin concentrations on presentation (more than 5 times the upper reference limit) or rapidly rising levels on serial testing can rapidly rule in AMI with high specificity. However, approximately one-third of patients remain in a biomarker-indeterminate "observation zone" even after serial sampling. These patients pose a disposition challenge to clinicians because although the differential diagnosis of elevated troponin concentrations is broad, these patients have an increased risk for short-term major adverse cardiac events. Use of repeated serial troponin sampling and structured clinical prediction tools may assist disposition for these patients, because no validated pathways currently exist to guide clinicians. Ongoing research to tailor diagnostic thresholds to individual patient characteristics may enable improved diagnostic accuracy and usher in a new era of personalized medicine in the evaluation of suspected ACS.