Marker For Acute Myocardial Infarction Research Articles

Multi-Shell Nanourchin-Integrated Dual Mode Lateral Flow Immunoassay for Sensitive and Rapid Detection of Clinical Cardiac Myosin-Binding Protein C.

Cardiac myosin-binding protein C (cMyBP-C) is a novel cardiac marker of acute myocardial infarction (AMI) and acute cardiac injuries (ACI). Construction of point-of-care testing techniques capable of sensing cMyBP-C with high sensitivity and precision is urgently needed. Herein, we synthesized an Au@NGQDs@Au/Ag multi-shell nanoUrchins (MSNUs), and then applied it in a colorimetric/SERS dual-mode immunoassay for detection of cMyBP-C. The MSNUs displayed superior stability, colorimetric brightness, and SERS enhancement ability with an enhanced factor of 5.4 × 109, which were beneficial to improve the detection capability of test strips. The developed MSNU-based test strips can achieve an ultrasensitive immunochromatographic assay of cMyBP-C in both colorimetric and SERS modes with the limits of detection as low as 19.3 and 0.77 pg/mL, respectively. Strikingly, this strip was successfully applied to analyze actual plasma samples with significantly better sensitivity, negative predictive value, and accuracy than commercially available gold test strips. Notably, this method possessed a wide range of application scenarios via combining with a color recognizer application named Color Grab on the smartphone, which can meet various needs of different users. Overall, our MSNU-based test strip as a mobile health monitoring tool shows excellent sensitivity, reproducibility, and rapid detection of the cMyBP-C, which holds great potential for the early clinic diagnosis of AMI and ACI.

Thrombomodulin as a potential diagnostic marker of acute myocardial infarction and correlation with immune infiltration: Comprehensive analysis based on multiple machine learning

BackgroundAcute myocardial infarction (AMI) is a global health problem with high mortality. Early diagnosis can prevent the development of AMI and provide valuable information for subsequent treatment. Angiogenesis has been shown to be a critical factor in the development of infarction and targeting this process may be a potential protective strategy for preventing myocardial injury and improving the prognosis of AMI patients. This study aimed to screen and verify diagnostic markers related to angiogenesis in AMI and to investigate the molecular mechanisms of action associated with AMI in terms of immune cell infiltration. MethodsThe GSE66360 and the GSE60993 datasets were both downloaded from the GEO database and were used as the training cohort and the external validation cohort, respectively. Angiogenesis-related genes (ARGs) were downloaded from the MSigDB database. The hub ARGs were identified via LASSO, RF, and SVM-RFE algorithms. ROC curves were used to assess the accuracy of the hub ARGs. The potential mechanisms of the hub ARGs were analyzed by GSEA. The ssGSEA algorithm was used to determine differences in immune cell infiltration and immune function. The CIBERSORT algorithm was used for immune cell infiltration analysis. In addition, we constructed a ceRNA network map of differentially expressed ARGs. ResultsWe identified the thrombomodulin (THBD) gene from ARGs as a potential diagnostic marker for AMI based on the LASSO, SVM-RFE, and RF algorithms. THBD was differentially expressed and had a potential diagnostic value (area under the curve [AUC] = 0.931 and 0.765 in the training and testing datasets, respectively). GSEA showed that the MAPK signaling pathway was more enriched in the high-expression group of THBD (P < 0.05). Immune cell infiltration analysis demonstrated that THBD was mainly positively correlated with monocytes (R = 0.48, P = 0.00055) and neutrophils (R = 0.36, P = 0.013). Finally, in the ceRNA regulatory network, THBD was closely associated with 9 miRNAs and 42 lncRNAs involved in AMI. ConclusionTHBD can be used as a potential diagnostic marker for AMI. This study provides new insights for future AMI diagnosis and molecular mechanism research. Moreover, immune cell infiltration plays an essential role in the occurrence and development of AMI.

Prognostic Value of ST-segment Deviation in Lead aVR in Electrocardiogram in Acute Myocardial Infarction

Background: Acute myocardial infarction (AMI) remains a significant cause of morbidity and mortality worldwide, necessitating effective risk stratification tools for improved management. ST-segment deviation in lead augmented vector right (aVR) has emerged as a potential prognostic marker in AMI, but its clinical relevance in the Indian context requires further investigation. Materials and Methods: We conducted a single-center prospective observational study among patients admitted with AMI to assess the prognostic value of ST-segment deviation in lead aVR. Patients were categorized based on the presence or absence of ST-segment deviation in lead aVR, and demographic, clinical, and angiographic characteristics were compared between groups. Follow-up evaluations were performed to assess left ventricular ejection fraction (LVEF) and the incidence of ventricular tachycardia (VT). Results: The study enrolled 110 patients, categorizing them by ST-segment deviation in lead aVR. Patients with ST elevation in lead aVR showed higher moderate LVEF dysfunction (31%–40%) than those with isoelectric ST segments (P = 0.0058). Conversely, patients with ST depression in lead aVR had increased preserved ejection fraction compared to those with an isoelectric ST segment (P = 0.0414). &lt;50% ST-segment resolution postpercutaneous coronary intervention (PCI) was more common among non-ST-segment elevation myocardial infarction (NSTEMI) patients. The incidence of VT was higher in ST elevation in lead aVR (P = 0.0045). Significant differences in ST-segment resolution after PCI (P = 0.0117) between STEMI and NSTEMI patients were noted. Conclusion: ST-segment deviation in lead aVR serves as a valuable prognostic marker in AMI, correlating with adverse outcomes such as moderate LVEF dysfunction and increased risk of VT. Furthermore, its association with ST-segment resolution post-PCI highlights its role in assessing reperfusion success and guiding management strategies. These findings underscore the importance of ST-segment deviation in lead aVR for risk stratification and personalized management in AMI patients.

Multimetal-Based Metal-Organic Framework System for the Sensitive Detection of Heart-Type Fatty Acid Binding Protein in Electrochemiluminescence Immunoassay.

In this work, an electrochemiluminescence (ECL) quenching system using multimetal-organic frameworks (MMOFs) was proposed for the sensitive and specific detection of heart-type fatty acid-binding protein (H-FABP), a marker of acute myocardial infarction (AMI). Bimetallic MOFs containing Ru and Mn as metal centers were synthesized via a one-step hydrothermal method, yielding RuMn MOFs as the ECL emitter. The RuMn MOFs not only possessed the strong ECL performance of Ru(bpy)32+ but also maintained high porosity and original metal active sites characteristic of MOFs. Moreover, under the synergistic effect of MOFs and Ru(bpy)32+, RuMn MOFs have more efficient and stable ECL emission. The trimetal-based MOF (FePtRh MOF) was used as the ECL quencher because of the electron transfer between FePtRh MOFs and RuMn MOFs. In addition, active intramolecular electron transfer from Pt to Fe or Rh atoms also occurred in FePtRh MOFs, which could promote intermolecular electron transfer and improve electron transfer efficiency to enhance the quenching efficiency. The proposed ECL immunosensor demonstrated a wide dynamic range and a low detection limit of 0.01-100 ng mL-1 and 6.8 pg mL-1, respectively, under optimal conditions. The ECL quenching system also presented good specificity, stability, and reproducibility. Therefore, an alternative method for H-FABP detection in clinical diagnosis was provided by this study, highlighting the potential of MMOFs in advancing ECL technology.

A MoS2 nanosheet-based CRISPR/Cas12a biosensor for efficient miRNA quantification for acute myocardial infarction

Acute myocardial infarction (AMI) represents the leading cause of cardiovascular death worldwide, and it is thus pivotal to develop effective approaches for the timely detection of AMI markers, especially possessing the characteristics of antibody-free, signal amplification, and manipulation convenience. We herein construct a MoS2 nanosheet-powered CRISPR/Cas12a sensing strategy for sensitive determination of miR-499, a superior AMI biomarker to protein markers. The presence of miR-499 at a trace level is able to induce a significantly enhanced fluorescence signal in a DNA-based molecular engineering platform, which consists of CRISPR/Cas12a enzymatic reactions and MoS2 nanosheet-controllable signal reporting components. The MoS2 nanosheets were characterized by using atomic force microscopy (AFM) and transmission electron microscope (TEM). The detection feasibility was verified by using polyacrylamide gel electrophoresis (PAGE) analysis and fluorescence measurements. The detection limit is determined as 381.78 pM with the linear range from 0.1 ⅹ 10−9 to 13.33 ⅹ 10−9 M in a fast manner (about 30 min). Furthermore, miRNA detection in real human serum is also conducted with desirable recovery rates (89.5 %–97.6 %), which may find potential application for the clinic diagnosis. We describe herein the first example of MoS2 nanosheet-based signal amplified fluorescence sensor for effective detection of AMI-related miRNA.

Effect of Yoga-Based Cardiac Rehabilitation Program on Endothelial Function, Oxidative Stress, and Inflammatory Markers in Acute Myocardial Infarction: A Randomized Controlled Trial.

The aim of this study was to evaluate the effects of yoga-based cardiac rehabilitation (Yoga-CaRe) on the endothelial system, oxidative stress, and inflammatory markers in patients with acute myocardial infarction (MI). A sub-study was conducted in two clinical sites of the Yoga-CaRe trial (a multicenter randomized controlled trial). Participants with acute MI were randomized and allocated to either the Yoga-CaRe program (13 sessions with encouragement to home practice) or enhanced standard care (three educational sessions). Endothelial function, oxidative stress, and inflammatory biomarkers were assessed using biomarkers such as asymmetric dimethylarginine (ADMA), endothelial nitric oxide synthase (eNOS), endothelin-1 (ET-1), E-selectin, P-selectin, vascular cell adhesion molecule (VCAM), intercellular cell-adhesion molecule-1, total nitric oxide concentration (NOx), oxidized low-density lipoprotein (Oxd-LDL), superoxide dismutase, total antioxidant capacity (TAOC), tumor necrosis factor-alpha (TNFα), and C-reactive protein (CRP) at baseline and 12 weeks. Laboratory and statistical analysis were done by staff blinded to group allocation. Eighty-two patients (of the 110 patients recruited) completed the study. The mean age was 53.1 ± 10.6 and 51.9 ± 10.7 years in enhanced standard care and Yoga-CaRe group, respectively. At 12 weeks, Yoga-CaRe significantly reduced ADMA, ET-1, and ICMA-1 than the enhanced standard care group. Although E-selectin and VCAM at 12 weeks were reduced in both groups, enhanced standard care had a significantly higher reduction than the Yoga-CaRe group. Among markers of oxidative stress, TAOC increased in the Yoga-CaRe group. We found no difference in eNOS, NOx, P-selectin, TNFα, CRP, and Oxd-LDL between the two groups. Yoga-CaRe improved the endothelial function (through a reduction in ET-1 and modulating adhesion molecules) and enhanced antioxidant capacity.

Identification of key genes associated with acute myocardial infarction using WGCNA and two-sample mendelian randomization study.

Acute myocardial infarction (AMI) is a severe condition with high morbidity and mortality rates. This study aimed to identify hub genes potentially associated with AMI and assess their clinical utility in predicting AMI occurrence. Gene microarray data were obtained from the Gene Expression Omnibus (GEO) database. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were conducted on samples from patients with AMI and control samples to identify modules significantly associated with AMI. GO and KEGG analyses were applied to investigate the potential functions of these hub genes. Lastly, the mendelian randomization (MR) method was applied to analyze the causal relationship between the hub gene TNF and AMI. 285 differentially expressed genes (DEGs) were identified through WCGNA and were clustered into 6 modules. The yellow module appeared most relevant to AMI. Further exploration through GO and KEGG pathway enrichment showed that key hub genes in the yellow module were linked to positive regulation of cytokine production, cytokine receptor binding, NF-kappa B signaling pathway, IL-17 signaling pathway, and TNF signaling pathway. The top 10 genes identified through Cytoscape software analysis were IL1B, TNF, TLR4, TLR2, FCGR3B, MMP9, CXCL8, TLR8, ICAM1, and JUK. Utilizing inverse variance weighting (IVW) analysis, we discovered a significant association between TNF and AMI risk, with an OR of 0.946 (95% CI = 0.911-0.984, p = 0.005). The result of this study indicated that TNF, TLR2, TLR4, IL1B and FCGR3B may be potential biodiagnostic markers for AMI. TNF can inhibit inflammatory and oxidative stress responses in AMI, exerting a protective role in the heart.

Prognostic importance of lung ultrasound sonography in patients with st-elevation myocardial infarction

Abstract Background Lung ultrasonography (LUS) is a relatively new method for assessing subclinical lung congestion. It has been approved to predict prognosis in heart failure; however, the importance of LUS as a prognostic marker in acute myocardial infarction is not well studied. Purpose Our goal was to assess the predictive value of LUS in patients with ST-segment elevation myocardial infarction(STEMI). Methods The study involved 140 patients in total. The primary percutaneous coronary intervention was performed on all patients. We used the 8-zone approach to perform LUS in patients with STEMI within 6 hours of admission. LUS detected lung congestion as B-lines, and the sum of the B-line from 8 chest zones was determined. The patients were divided into two groups depending on the amounts of B lines. Patients with a number of B-lines &amp;lt; 15 were included in Group 1 (70 patients) and patients with a B-lines ≥ 15 were included in Group 2 (70 patients). The NT-proBNP analysis was performed both upon admission and six months later. The groups' other characteristics were similar. The primary outcome was a 6-month death rate after admission for STEMI. The secondary endpoint was NT-proBNP level over six months and cardiac cause of rehospitalization. Results NT-proBNP levels were, on average, 1471.6±272.8pg/ml in group 1 and 1512.3 ±285.8pg/ml in group 2 at the beginning of the study (p=0.39). It was 653.5±241.6 pg/ml and 857.4±217.8pg/ml, respectively, at the end of six months (p &amp;lt; 0.0001). Cardiovascular mortality during follow-up was 2.86 % in group 1 and 12.86 % in group 2 (p =0.029), and hospitalization for a cardiac cause was 7.14% and 18.57%, respectively (p =0.044). Conclusions LUS may be used as part of the initial risk stratification in STEMI patients because it provides important prognostic information. B-lines detected by lung ultrasound can be an independent predictor of poor prognosis in STEMI patients.

Correlation between admission red cell distribution width and GRACE risk score as an early mortality marker in patients with acute myocardial infarction

Background: Red blood cell distribution width (RDW) is a measurement of the size variation of red blood cells in circulation. The Global Registry of Acute Coronary Events (GRACE) score is the most commonly used risk-stratification scoring system to predict mortality in acute coronary syndrome for both ST- elevated myocardial infarction (STEMI), non-ST elevated myocardial infarction (NSTEMI). The aim of this study was to assess the easily determinable red blood cell distribution width (RDW) as an early mortality marker of acute myocardial infarction (MI) mortality and the correlation of RDW-CV on admission with GRACE risk score in patients with acute myocardial infarction. Methods: This hospital-based, prospective observational study included 211 patients (mean age 58.15 +/- 12.45 years, male 176) admitted with acute MI (STEMI/NSTEMI) from January 2022 to June 2022. The study population was divided into two groups basing on the 50th percentile of the admission RDW-CV value -13.7. The GRACE score was calculated on admission to predict the GRACE in hospital mortality score within 24 hours of admission. Results: The study found that the higher RDW-CV values were associated with adverse prognostic factors in acute myocardial infarction like increased age, lower systolic blood pressure, heart failure, cardiac arrest, higher cardiac biomarker levels and higher in-hospital mortality (p = 0.049, level of significance p&lt; 0.05) and this correlated with a higher GRACE score (Pearson’s correlation coefficient R= 0.47, P&lt;0.05). Conclusion: Thus, RDW can be used as a useful parameter for predicting in-hospital mortality in acute MI patients.

Screening of Potential Circulating Diagnostic Biomarkers and Molecular Mechanisms of Systemic Lupus Erythematosus-Related Myocardial Infarction by Integrative Analysis.

The risk of acute myocardial infarction (AMI) is elevated in patients with systemic lupus erythematosus (SLE), and it is of great clinical value to identify potential molecular mechanisms and diagnostic markers of AMI associated with SLE by analyzing public database data and transcriptome sequencing data. AMI and SLE-related sequencing datasets GSE62646, GSE60993, GSE50772 and GSE81622 were downloaded from the Gene Expression Omnibus (GEO) database and divided into prediction and validation cohorts. To identify the key genes associated with AMI related to SLE, WGCNA and DEGs analysis were performed for the prediction and validation cohorts, respectively. The related signaling pathways were identified by GO/KEGG enrichment analysis. Peripheral blood mononuclear cells (PBMCs) from patients with AMI were collected for transcriptome sequencing to validate the expression of key genes in patients with AMI. Least absolute shrinkage and selection operator (LASSO) regression analysis was applied to screen diagnostic biomarkers. The diagnostic efficacy of biomarkers was validated by ROC analysis, and the CIBERSORTx platform was used to analyze the composition of immune cells in AMI and SLE. A total of 108 genes closely related to AMI and SLE were identified in the prediction cohort, and GO/KEGG analysis showed significantly enriched signaling pathways. The results of differential analysis in validation cohort were consistent with them. By transcriptional sequencing of PBMCs from peripheral blood of AMI patients, combined with the results of prediction and validation cohort analysis, seven genes were finally screened out. LASSO analysis finally identifies DYSF, LRG1 and CSF3R as diagnostic biomarkers of SLE-related-AMI. CIBERSORTx analysis revealed that the biomarkers were highly correlated with neutrophils. Neutrophil degranulation and NETs formation play important roles in SLE-related AMI, and DYSF, LRG1 and CSF3R were identified as important diagnostic markers for the development and progression of SLE-related AMI.

PO-04-174 AN ELECTROGRAPHIC DEEP LEARNING MODEL FOR LONG-TERM MORTALITY OF THE PATIENTS SURVIVING AFTER ACUTE MYOCARDIAL INFARCTION

The diagnosis of acute myocardial infarction (AMI) initially depends on a patient’s history and the 12-lead ECG. Significant changes of the ST segment on ECG are one of the diagnostic markers of AMI and are associated with higher short-term or long-term mortality of patients. However, scoring systems or predictors for long-term risk stratification are still lacking for patients with AMI. Recently deep learning (DL) model built based on 12-lead ECG showed its great potential for early diagnosis of heart failure and atrial fibrillation. We aimed to develop a prognosis model for the long-term mortality of AMI patients based on 12-lead ECG using DL. Twelve-lead ECGs of patients during AMI were retrieved retrospectively between 2011 to 2017, and a convolutional neural network (CNN) using 12-lead ECG and patient’s age has been built to predict all-cause death within one year. The patients’ ECG recordings were split into training, validation, and testing set at a ratio of 5:2:3 and the patients were not overlapped among different datasets. Survival analysis was conducted using the Kaplan-Meier method with available follow-up data in a testing set stratified by the built model. Furthermore, Cox proportional hazard model was performed to get crude hazard ratio (HR) and covariate-adjusted HR for TIMI and GRACE score. 16827 ECGs from 2238 patients (77% male, age 64.8±13.8 years) with AMI were included. The AUC of the DL model is 0.80, with a sensitivity of 82%, and specificity of 66% using an optimal threshold on the testing set. In addition, we also found that the patients labeled as dead by DL model have a higher probability of death over a 6-year follow-up with the HR of 6.00 (95% confidence interval (CI) 3.92-9.20) while the HR of TIMI score is 1.38 (95% CI 0.97-1.97) and HR of GRACE score is 2.72 (95% CI 1.92-3.86). By applying multivariate adjustment, the DL model can be an independent predictor with the HR of 5.68 (95% CI 3.69-8.74) for the sex-adjusted model, 6.11 (95% CI 3.95-9.45) for the TIMI-socre-adjusted model and 5.22 (95% CI 3.38-8.06) for GRACE-score-adjusted model. (Figure 1) Our result showed that the DL model built based on 12-lead ECG can predict long-term mortality after AMI for up to 6 years. The DL model can provide an instant prognostic indicator using the 12-lead ECG complemented with TIMI or GRACE scores.

ACSL1, CH25H, GPCPD1, and PLA2G12A as the potential lipid-related diagnostic biomarkers of acute myocardial infarction.

Lipid metabolism plays an essential role in the genesis and progress of acute myocardial infarction (AMI). Herein, we identified and verified latent lipid-related genes involved in AMI by bioinformatic analysis. Lipid-related differentially expressed genes (DEGs) involved in AMI were identified using the GSE66360 dataset from the Gene Expression Omnibus (GEO) database and R software packages. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to analyze lipid-related DEGs. Lipid-related genes were identified by two machine learning techniques: least absolute shrinkage and selection operator (LASSO) regression and support vector machine recursive feature elimination (SVM-RFE). The receiver operating characteristic (ROC) curves were used to descript diagnostic accuracy. Furthermore, blood samples were collected from AMI patients and healthy individuals, and real-time quantitative polymerase chain reaction (RT-qPCR) was used to determine the RNA levels of four lipid-related DEGs. Fifty lipid-related DEGs were identified, 28 upregulated and 22 downregulated. Several enrichment terms related to lipid metabolism were found by GO and KEGG enrichment analyses. After LASSO and SVM-RFE screening, four genes (ACSL1, CH25H, GPCPD1, and PLA2G12A) were identified as potential diagnostic biomarkers for AMI. Moreover, the RT-qPCR analysis indicated that the expression levels of four DEGs in AMI patients and healthy individuals were consistent with bioinformatics analysis results. The validation of clinical samples suggested that 4 lipid-related DEGs are expected to be diagnostic markers for AMI and provide new targets for lipid therapy of AMI.

Isolated T wave Inversion in Lead aVL as an early sign of Inferior Wall Myocardial Infarction

Electrocardiogram (ECG) is instrumental in identifying acute myocardial infarction (AMI). ST-segment elevation in a region of specific coronary vessels in an acute coronary syndrome (ACS) setting is the hallmark of AMI. Reciprocal ST depression and T wave inversion (TWI) are well-recognized changes that could accompany ST segment elevations. Reciprocal changes may represent the only early manifestation of AMI and may be present in specific leads such as lead aVL as early and sensitive markers of AMI. Abnormalities in the ST segment and T wave can result from non-ACS causes, but early recognition and appropriate intervention are paramount for patients with ACS. We report a case of a 55-year-old male with acute IWMI with early reciprocal and dynamic ECG changes with a literature review.

Association between P2Y1 and P2Y12 polymorphisms and acute myocardial infarction and ADP-induced platelet aggregation

BackgroundThe objective of this study was to investigate the relationship between P2Y1 and P2Y12 genotypes and the risk of acute myocardial infarction (AMI) in the Quanzhou population and to determine associations between P2Y1 and P2Y12 genotypes and ADP-induced platelet aggregation in this population.MethodsAll subjects were screened for P2Y1 (c.1622A > G) and P2Y12 (H1/H2, c.34C > T) polymorphisms by direct DNA sequencing. The maximal platelet aggregation rate (MAR) in AMI patients (n = 61) and healthy control subjects (n = 50) was measured by a PL-12 platelet function analyzer, and adenosine diphosphate (ADP) (5 μmol/L) was used as an agonist.ResultsThe haploid H2 allele in the P2Y12 gene was more frequent in patients with AMI than in control subjects (OR 1.887, P = 0.005). The P2Y12 H2 haplotype was significantly associated with AMI in the codominant (P = 0.008), dominant (OR 2.103, P = 0.003), and overdominant models (OR 2.133, P = 0.003). After adjusting for potential confounders, H2 haplotype carriers had a 2.132-fold increased risk for AMI (OR 2.132, P = 0.012) compared with noncarriers. Moreover, we observed that the ADP-induced MAR in the carriers of the H2 haplotype from the control group was somewhat higher than that in noncarriers of this group (P = 0.020). However, we failed to demonstrate that the P2Y1 H1/H2 polymorphism affected ADP-induced MAR in AMI patients. Additionally, P2Y1 c.1622A > and P2Y12 c.34C > T polymorphisms were not associated with the risk of AMI or ADP-induced MAR in either group.ConclusionsTherefore, our results suggest that the P2Y12 H2 haplotype was associated with a higher risk of AMI, while its effect on increased ADP-induced platelet aggregation remains to be investigated. Thus, the P2Y12 H2 haplotype may be a potential marker for AMI.

MicroRNA-499-5p and chemokine (C-C motif) ligand18 as new diagnostic markers of Acute Myocardial Infarction

MicroRNA-499-5p and chemokine (C-C motif) ligand18 as new diagnostic markers of Acute Myocardial Infarction

Association between Frontal QRS-T Angle and Major Adverse Cardiovascular Events among Patients with Acute Myocardial Infarction: A Cross-sectional Study

Introduction: Acute myocardial infarction has reached epidemic proportions in the Indian population. The premature onset of acute myocardial infarction has shifted the focus of research. An abnormal frontal QRS-T angle can be used as a marker of acute myocardial infarction and can also predict Major Adverse Cardiac Events (MACE) such as heart failure, complex ventricular arrhythmias (sustained ventricular tachycardia or ventricular fibrillation), early post-infarction angina, mechanical complications, and cardiac death resulting from acute myocardial infarction. Predicting the likelihood of serious adverse cardiovascular events and mortality in patients who have experienced an acute myocardial infarction aids in developing immediate and short-term treatment plans. Aim: To assess the association between the Frontal QRS-T angle and MACE among patients with Acute Myocardial Infarction (MI). Materials and Methods: A cross-sectional study was conducted on adult patients admitted with a diagnosis of acute MI at the Department of Medicine, BLDE (Deemed to be University) Shri B.M. Patil Medical College Hospital and Research Centre, Vijayapura, Karnataka, India from January 2021 to June 2022. A total of 95 patients were enrolled in the study and classified into two groups: Group A (n=68) with a frontal QRS-T angle of &lt;100 degrees, and Group B (n=27) with a frontal QRS-T angle of &gt;100 degrees. The patients were monitored for the emergence of serious MACE such as heart failure, pulmonary oedema, cardiogenic shock, arrhythmias, and death while they were in the hospital. Statistical analysis was performed using the Chisquare test, Independent t-test, and Mann-Whitney U test as applicable. A p-value of &lt;0.05 was considered statistically significant. Results: The most common age group in Group A was 60-70 years, while in Group B it was 50-60 years. A total of 95 patients with acute MI were enrolled and divided into two groups. Out of 95 patients, 68 patients with a frontal QRS-T angle &lt;100 degrees were in Group A, and 27 patients with a frontal QRS-T angle &gt;100 degrees were in Group B. There was a significant difference between the two groups with respect to MACE, including heart failure (Group A=8.8%, Group B=77.8%, p=0.00), pulmonary oedema (Group A=10.3%, Group B=77.8%, p=0.00), and cardiogenic shock (Group A=7.4%, Group B=40.7%, p=0.00). Conclusion: A frontal QRS-T angle of &gt;100 degrees was a reliable factor for assessing in-hospital major adverse cardiac outcomes such as heart failure, pulmonary oedema, and cardiogenic shock. Hence, a frontal QRS-T angle of &gt;100 degrees on a 12-lead ECG is a cost-effective, reliable, and noninvasive parameter of MACE in patients with acute MI.

CircSMARCC1 and CircLRBA are potential biomarkers in forensic postmortem diagnosis of acute myocardial infarction

Postmortem diagnosis of acute myocardial infarction (AMI), especially early AMI, is a challenge for forensic scientists. Circular RNAs (circRNA) are a unique type of RNA with a closed loop structure and more stability, compared with linear RNA. We aimed at evaluating whether circRNAs are ideal postmortem diagnostic markers for AMI. We employed bioinformatics methods to screen for target circRNAs. Divergent and convergent primers were used to confirm the loop structure. Ribonuclease R (RNaseR) digestion and artificial simulated room temperature test were performed to evaluate the stability of circRNAs. Furthermore, RT-PCR analysis was performed to assess the expressions of target circRNAs in a mouse model of AMI and in autopsy cases, while the diagnostic significance of circRNAs was evaluated by the receiver-operator characteristic (ROC) curve. The bioinformatics analysis screened out circSMARCC1 and circLRBA as target circRNAs. Agarose gel electrophoresis revealed the loop structure of target circRNAs. RNaseR digestion and the artificial simulated room temperature test showed that the stability of circRNAs was good. In mouse AMI model, circSMARCC1 levels were elevated while circLRBA levels were suppressed. Finally, in forensic autopsy cases, circSMARCC1 levels were significantly elevated, while circLRBA levels were significantly suppressed in the MI and early-MI group, relative to the normal control group. The ROC curve analysis showed that both circSMARCC1 and circLRBA can distinguish between AMI and normal control cases. Futher, a combination of the two circRNAs can increase the diagnostic efficacy of AMI. Thus, circSMARCC1 and circLRBA are potential biomarkers for postmortem diagnosis of AMI.

Traditional and novel diagnostic biomarkers for acute myocardial infarction

Abstract Background Acute myocardial infarction (AMI) is a leading cause of death worldwide. The first hours of acute myocardial infarction are correlated with the highest risk of death. Therefore, early diagnosis of the infarction seriously affects the efficacy of the treatment administered to the patient. Misdiagnosing patients with chest pain often leads to inappropriate admission of them as acute myocardial infarction patients. The physical examination of the patient, the electrocardiogram, and the assessment of cardiac biomarkers all play an important role in the early diagnosis of acute ischemia, along with the patient's medical history. Main body The present review highlights a number of different biomarkers that are released and elevated in blood during an acute myocardial infarction. Conclusions Analysis of cardiac biomarkers has become the first-line diagnostic tool used in the diagnosis of acute myocardial infarction. Novel markers of acute myocardial infarction, when added to routinely used markers, can provide added value not only in the earlier detection of acute myocardial infarction but also in monitoring the clinical progress of the disease, predicting its consequences, evaluating its prognosis, detecting recurrence, and managing its treatment. This leads to a lower mortality rate associated with acute myocardial infarction. cMyC, IMA, S100, and MicroRNAs can serve as markers of early diagnosis of acute myocardial infarction, whereas myeloperoxidase, sCD40L, PAPPA, and TNF-α can be used to monitor the clinical progress of the disease. In addition, H-FABP, GDF-15, F2 isoprostanes, and ST2 can serve as predictors of AMI complications and mortality. Copeptin, ST2, and SIRT can be useful as prognostic markers of acute myocardial infarction.

Plasma desmosine for prediction of outcomes after acute myocardial infarction.

Elastin degradation is implicated in the pathology of vulnerable plaque. Recent studies show promising results for plasma desmosine (pDES), an elastin-specific degradation product, as a marker of cardiovascular disease (CVD) outcomes. The aim of this study was to investigate the potential role of pDES as a marker of clinical outcome in patients with acute myocardial infarction (AMI). In this case-control study, we studied 236 AMI patients: 79 patients who had death and/or myocardial infarction (MI) at 2 years, and 157 patients who did not have an event at 2 years. pDES was measured using a validated liquid chromatography-tandem mass spectrometry method. Association of pDES with adverse outcomes, and the incremental value of pDES to global registry of acute coronary events (GRACE) score for risk stratification was assessed. pDES levels were elevated in patients with the composite outcome of death/MI at 2 years (p = 0.002). Logistic regression analyses showed pDES to be associated with death/MI at 2 years [Odds ratio (OR) 5.99 (95% CI 1.81-19.86) p = 0.003]. pDES remained a significant predictor of death/MI at 2 years even after adjustment for age, sex, history of CVD, revascularisation, blood pressure, medications on discharge, Troponin I, and NT-proBNP levels.[OR 5.60 (95% CI 1.04-30.04) p = 0.044]. In another multivariable model including adjustment for eGFR, pDES was significantly associated with the composite outcome at 6 months, but not at 2 years follow up. DES was also able to reclassify risk stratification for death/MI at 6 months, when added to the GRACE risk model [Net Reclassification Index (NRI) 41.2 (95% CI 12.0-70.4) p = 0.006]. pDES concentrations predict clinical outcomes in patients with AMI, demonstrating its potential role as a prognostic marker in AMI.

Robust prognostic prediction model developed with integrated biological markers for acute myocardial infarction

Commonly used prediction methods for acute myocardial infarction (AMI) were created before contemporary percutaneous coronary intervention was recognized as the primary therapy. Although several studies have used machine learning techniques for prognostic prediction of patients with AMI, its clinical application has not been achieved. Here, we developed an online application tool using a machine learning model to predict in-hospital mortality in patients with AMI. A total of 2,553 cases of ST-elevation AMI were assigned to 80% training subset for cross validation and 20% test subset for model performance evaluation. We implemented random forest classifier for the binary classification of in-hospital mortality. The selected best feature set consisted of ten clinical and biological markers including max creatine phosphokinase, hemoglobin, heart rate, creatinine, systolic blood pressure, blood sugar, age, Killip class, white blood cells, and c-reactive protein. Our model achieved high performance: the area under the curve of the receiver operating characteristic curve for the test subset, 0.95: sensitivity, 0.89: specificity, 0.91: precision, 0.43: accuracy, 0.91 respectively, which outperformed common scoring methods. The freely available application tool for prognostic prediction can contribute to risk triage and decision-making in patient-centered modern clinical practice for AMI.