Acute Myocardial Infarction Screening Research Articles

Gut-microbiome-based predictive model for ST-elevation myocardial infarction in young male patients.

ST-segment elevation myocardial infarction (STEMI) in young male patients accounts for a significant proportion of total heart attack events. Therefore, clinical awareness and screening for acute myocardial infarction (AMI) in asymptomatic patients at a young age is required. The gut microbiome is potentially involved in the pathogenesis of STEMI. The aim of the current study is to develop an early risk prediction model based on the gut microbiome and clinical parameters for this population. A total of 81 young males (age < 44 years) were enrolled in this study. Forty-one young males with STEMI were included in the case group, and the control group included 40 young non-coronary artery disease (CAD) males. To identify the differences in gut microbiome markers between these two groups, 16S rRNA-based gut microbiome sequencing was performed using the Illumina MiSeq platform. Further, a nomogram and corresponding web page were constructed. The diagnostic efficacy and practicability of the model were analyzed using K-fold cross-validation, calibration curves, and decision curve analysis (DCA). Compared to the control group, a significant decrease in tendency regarding α and β diversity was observed in patients in the case group and identified as a significantly altered gut microbiome represented by Streptococcus and Prevotella. Regarding clinical parameters, compared to the control group, the patients in the case group had a higher body mass index (BMI), systolic blood pressure (SBP), triglyceride (TG), alanine aminotransferase (ALT), and aspartate aminotransferase (AST) and low blood urea nitrogen (BUN). Additionally, BMI and SBP were significantly (p<0.05) positively correlated with Streptococcus and [Ruminococcus]. Further, BMI and SBP were significantly (p<0.05) negatively correlated with Prevotella and Megasphaera. A significant negative correlation was only observed between Prevotella and AST (p < 0.05). Finally, an early predictive nomogram and corresponding web page were constructed based on the gut microbiome and clinical parameters with an area under the receiver-operating characteristic (ROC) curve (AUC) of 0.877 and a C-index of 0.911. For the internal validation, the stratified K-fold cross-validation (K = 3) was as follows: AUC value of 0.934. The calibration curves of the model showed good consistency between the actual and predicted probabilities. The DCA results showed that the model had a high net clinical benefit for use in the clinical setting. In this study, we combined the gut microbiome and common clinical parameters to construct a prediction model. Our analysis shows that the constructed model is a non-invasive tool with potential clinical application in predicting STEMI in the young males.

Role of Biochemical Markers in Detection of Myocardial Infarction

Introduction: Acute myocardial infarction causes significant mortality and morbidity. Timely conclusion permits clinicians to risk stratify their patients and select suitable treatment. Biomarkers have been utilized to help with timely decision, whereas an expanding number of novel markers have been recognized to predict result taking after an acute myocardial infarction or acute coronary disorder. This may encourage tailoring of appropriate treatment to high-risk patients. This survey focuses on an assortment of promising biomarkers which give symptomatic and prognostic data. Objective: To compare the early demonstrative efficiency of the cardiac troponin I (cTn-I) level with that of the cardiac troponin T (cTn-T) level, as well as the creatine kinase (CK), CK-MB, and myoglobin levels, for acute myocardial infarction (AMI) in patients without an initially diagnostic ECG presenting to the Emergency department within 24 hours of the onset of their symptoms. Material and Methods Study design: Prospective Observational Cohort Settings: Punjab Institute of Cardiology Duration: Six months i.e. 1st January 2020 to 30th June 2020 Data Collection procedure: A planned, observational, cohort study was performed including chest pain patients admitted to territory care hospital. Members were sequential consenting through Emergency department with chest pain and age more than 30 years. Exclusion included having symptoms &gt;24 hours, failure to total information collection, receipt of CPR, and ST-segment elevation on the starting ECG. Estimations included levels of Trop-I, Trop- T, CK, CK-MB, and myoglobin at the time of introduction and 1, 2, 6, and 12-24 hours after presentation as well as showing ECG and clinical follow-up. The collected data was analyzed by using SPSS version 23. Results: 140 included for study out of the 200 patients, 21 (14%) were analyzed as having acute myocardial infarction after diagnostic ECG testing. The sensitivities of all 5 biochemical markers for acute myocardial infarction were poor at the time of emergency department induction. The sensitivity of Trop-T was essentially superior to that of Trop-I over the starting 2 hours (3.2-33.1), but both markers' sensitivities were low (&lt;60%) during this time outline. The Trop-I was significantly more particular for acute myocardial infarction than was the Trop-T, but not essentially better than CK-MB or myoglobin. Likelihood proportion analysis appeared that the biochemical markers with the most elevated positive ratios for acute myocardial infarction amid the primary 2 hours taking after emergency department admission were myoglobin and CK-MB. From 6 through 24 hours, the positive probability proportions for Trop I, CK-MB, and myoglobin were predominant to those of CK and Trop-T. Conclusion: Trop-I, CK-MB, and myoglobin are essentially more particular for acute myocardial infarction than are CK and Trop-T. Myoglobin is the biochemical marker having the most elevated combination of sensitivity, specificity, and negative predictive value for acute myocardial infarction inside 2 hours of emergency department induction. Not one or the other Trop-I nor Trop-T offers significant advantages over myoglobin and CK-MB within the early less than 2 hours starting screening for acute myocardial infarction. The cardiac troponins are of advantage in recognizing acute myocardial infarction greater than 6 hours after presentation. Key words: Myocardial Infarction, CKMB, Trop t, Trop I, Myoglobin

Troponin Limit of Detection Plus Cardiac Risk Stratification Scores to Rule Out Acute Myocardial Infarction and 30-Day Major Adverse Cardiac Events in ED Patients.

When screening for acute myocardial infarction (AMI), troponin levels below the 99th percentile, including those below the limit of detection (LOD), are considered normal. We hypothesized that a low-risk HEART score (0-3) or ACS Pretest Probability Assessment <2% plus a single troponin below the LOD would rule out both AMI and 30-day major adverse cardiac events (MACE). We studied all patients who presented to a single academic emergency department and received a troponin I (Siemens Ultra Troponin I) from September 1, 2013, to November 13, 2013 (n=888). Demographic and clinical data were abstracted from the electronic medical record. Primary outcome was a final encounter diagnosis of myocardial infarction. Secondary outcome was 30-day MACE, defined as composite of myocardial infarction, revascularization, or death from a cardiac or uncertain etiology. Sensitivities of low-risk HEART score and ACS Pretest Probability <2% alone were 98% (95% confidence interval [CI], 89%-100%) and 96% (95% CI, 86%-100%) for AMI and 94% (95% CI, 86%-98%) and 95% (95% CI, 88%-99%), respectively, for 30-day MACE. When combined with troponin below the LOD, sensitivity for AMI was 100% (95% CI, 93%-100%; difference 2%; 95% CI, -2% to 6%) for low-risk HEART Score and 100% (95% CI, 93%-100%; difference 4%; 95% CI, -1.5% to 10%) for ACS Pretest Probability <2%. When combined with troponin below the LOD, sensitivity for 30-day MACE was 100% (95% CI, 95%-100%; difference 6%; 95% CI, 1%-12%) for low-risk HEART Score and 100% (95% CI, 95%-100%; difference 5%; 95% CI, 0.2%-10%) for ACS Pretest Probability <2%. Addition of a single troponin below the LOD to these scores improves sensitivity for 30-day MACE.

Plasma miR-1, miR-208, miR-499 as potential predictive biomarkers for acute myocardial infarction: An independent study of Han population

BackgroundIt has been demonstrated that circulating muscle-enriched miR-1 and the cardiac-specific miR-208 and miR-499 might leak out of the necrotic myocardium and release into the circulation during the early stages of acute myocardial infarction (AMI). This study aims to investigate potential predictive value of the three miRNAs in AMI. MethodsPlasma samples were taken from 70 AMI patients and 72 healthy controls. The expression levels of target miRNAs were measured by qRT-PCR. Student's t test and χ2 test were applied to test the significance of the differences between AMI patients and controls. Additionally, a meta-analysis about the prediction accuracy of the three miRNAs in AMI was performed to summarize all the results from available studies. ResultsThe expression of plasma miR-1, miR-208 and miR-499 were all significantly elevated in AMI patients compared with controls. By receiver operating characteristic (ROC) curve analysis, plasma miR-1, miR-208 and miR-499 were demonstrated to be potential biomarkers for the prediction of AMI with AUC values of 0.81, 0.72, and 0.88, respectively. The meta-analysis consisted of nine studies for miR-1, eight studies for miR-208 and eight studies for miR-499. The summary estimates of miR-1, miR-208 and miR-499 were 0.73, 0.80 and 0.83 for sensitivity, 0.82, 0.95 and 0.90 for specificity, 0.84, 0.89 and 0.91 for AUC, respectively. ConclusionIn summary, we confirmed the predictive values of plasma miR-1, miR-208 and miR-499 in AMI. In contrast to miR-1, the cardiac-specific miR-208 and miR-499 were supposed to be more reliable as biomarkers in AMI screening and prediction.

Creatine kinase-MB does not add additional benefit to a negative troponin in the evaluation of chest pain

Objective The aim of this study was to determine whether current troponin assay alone can be used for initial screening for acute myocardial infarction (AMI) and whether creatine kinase-MB (CK-MB) can safely be eliminated from this evaluation in the emergency department (ED). Methods A retrospective cohort study of patients who had cardiac troponin T (Roche, Basel, Switzerland) and CK-MB ordered at an urban academic level 1 trauma center with more than 55,000 annual visits. Patients with troponin testing in the ED were identified over a period of 12 months, and corresponding CK-MB indexes were examined identifying patients with negative troponins (<0.01) and positive CK-MB indexes (>6.0). In these patients, further cardiac markers, hospital course, and 30-day mortality were then evaluated. A 99% confidence interval around point estimate was used in data analysis. Results During the study period, there were 11,092 separate ED patient encounters where a patient had at least one troponin resulted. Most (97.9%) of the samples had an associated CK-MB ordered. There were 7545 initial negative troponins representing 68% of all initial samples. Seven of these had an associated positive MB index. When subsequent troponins were evaluated, an additional 4910 negative troponins were identified, with 4 patients having a positive MB. None of these 11 patients were judged to have ruled in for AMI by the treating physicians. The rate of true-positive CK-MB index with negative troponin was 0% (99% confidence interval, 0-0.04%). Conclusion Our results suggest that CK-MB is not necessary in the initial screening for AMI and may safely be omitted in patients with negative troponins.

Using neural networks and just nine patient-reportable factors of screen for AMI

The study investigated the effect of different input selections on the performance of artificial neural networks in screening for acute myocardial infarction (AMI) in Malaysian patients complaining of chest pain. We used hospital data to create neural networks with four input selections and used these to diagnose AMI. A 10-fold cross-validation and committee approach was used. All the neural networks using various input selections outperformed a multiple logistic regression model, although the difference was not statistically significant. The neural networks achieved an area under the ROC curve of 0.792 using nine inputs, whereas multiple logistic regression achieved 0.739 using 64 inputs. Sensitivity levels of over 90 per cent were achieved using low output threshold levels. Specificity levels of over 90 per cent were achieved using threshold levels of 0.4-0.5. Thus neural networks can perform as well as multiple logistic regression models even when using far fewer inputs.

A simple test for myocardial infarction

Background: The purpose of this study was to determine the feasibility of using a first pass phase map of the ventricular blood pool to detect and localize acute myocardial infarction (AMI). Methods: Subjects: 50 sequential patients had first time acute MI localized by well defined focal pyrophosphate (pyp) uptake with Ecg, enzyme and clinical confirmation. During this same period of time 16 patients were admitted to rule out MI and showed no pyp uptake, or other findings of AMI. Technique: 20 mCi of 99mTc pyp was bolus injected into all subjects admitted to RO MI. Using a small mobile camera 30 deg RAO planar first pass data was acquired in list mode with millisecond time markers. Representative cycles were constructed from the two highest count RV and the three highest LV beats. Each of these chosen heart beats were individually divided into time segments that were 1/16 of the beat length to 1 ms precision. The corresponding segments were then added. The valve planes (which are nearly perpendicular to the RAO imaging plane) are defined by functional techniques. A first harmonic phase map was then reapplied to the ventricular blood strictly limited by the valve planes and diastolic pool edges. The location of a phase defect was shown on the RAO (long axis) color coded ventricular map and the size of the defect was quantitated in a corresponding histogram of all of the pixels in the map. The computer generated map was available immediately after the 20 second angiogram and was interpreted without knowledge of subsequent findings. Regional wall motion (RWM) by sequential isocount contours during the cardiac cycle. RVEF and LVEF as well as LVEDV and pulmonary transit time were also calculated After 4 to 6 hours repeat angiography was performed with 99mTc DTPA in the optimum view to superimpose the static pyp image. Results: 48 of the 50 MIs were correctly localized in the RAO ventricular phase maps. Two posterolateral wall infarcts were not detected. 38 of the infarcts had corresponding RWM defects. In general the phase maps were much easier to interpret and quantitate than the RWM displays. None of the 16 non MI subjects had phase defects. Conclusion: The rapidity and simplicity of this test suggests a roll in screening for AMI especially in subjects without prior history of AMI.