Identification Of Acute Myocardial Infarction Research Articles

Functionalized Triangular Carbon Quantum Dot Stabilized Gold Nanoparticles Decorated Boron Nitride Nanosheets Interfaced for Electrochemical Detection of Cardiac Troponin T.

The fast, and highly sensitive estimation of cardiac troponin T (cTnT) is crucial for the early identification of acute myocardial infarction (AMI). The electrochemical immunoassay-based (EIB) sensors are highly promising for this purpose, as they offer precise measurements and can be directly assessed in intricate matrices, including blood. To increase sensitivity, EIB sensors use nanomaterials or amplification processes, which can be laborious to develop. With this, we develop an electrochemical immunosensor for the sensitive detection of cardiac troponin T (cTnT). The sensing platform is composed of functionalized triangular carbon quantum dots stabilized gold nanoparticles which are integrated with boron nitride nanosheets (caf-TCQDs@AuNPs on HO-BNNS). Ferrocene carboxylic acid (Fc-COOH) serves as the signal label. The composite was developed and examined using several techniques such as X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM), cyclic voltammetry, and chronocoulometry. The caf-TCQDs@AuNPs supported on HO-BNNS, have a large surface area and excellent electrical conductivity, and serve as an effective platform for the immobilization of anti-cTnT monoclonal antibodies via carbodiimide coupling. The Fc-COOH, functioning as a signal label through the oxidation process, was integrated with caf-TCQDs@AuNPs on the HO-BNNS platform to establish an electrochemical immunosensor for the detection of cTnT. The electrochemical immunosensor demonstrated excellent performance for the determination of cTnT under optimal conditions, exhibiting a linearity range spanning from 0.0001 to 100 ng mL-1, accompanied by a low detection limit of 0.0013 ng mL-1. Notably, the immunosensor revealed high specificity, as well as excellent levels of reproducibility and reliability for the examination of human serum samples.

Identification of Acute Myocardial Infarction from Left Ventricular Wall Rupture Using ResNet 18-Deep Active Learning Algorithms

Identification of Acute Myocardial Infarction from Left Ventricular Wall Rupture Using ResNet 18-Deep Active Learning Algorithms

Rationale and design of the artificial intelligence scalable solution for acute myocardial infarction (ASSIST) study

BackgroundAcute coronary syndrome (ACS), specifically ST-segment elevation myocardial infarction is a major cause of morbidity and mortality throughout Europe. Diagnosis in the acute setting is mainly based on clinical symptoms and physician's interpretation of an electrocardiogram (ECG), which may be subject to errors. ST-segment elevation is the leading criteria to activate urgent reperfusion therapy, but a clear ST-elevation pattern might not be present in patients with coronary occlusion and ST-segment elevation might be seen in patients with normal coronary arteries. MethodsThe ASSIST project is a retrospective observational study aiming to improve the ECG-assisted assessment of ACS patients in the acute setting by incorporating an artificial intelligence platform, Willem™ to analyze 12‑lead ECGs. Our aim is to improve diagnostic accuracy and reduce treatment delays. ECG and clinical data collected during this study will enable the optimization and validation of Willem™. A retrospective multicenter study will collect ECG, clinical, and coronary angiography data from 10,309 patients. The primary outcome is the performance of this tool in the correct identification of acute myocardial infarction with coronary artery occlusion. Model performance will be evaluated internally with patients recruited in this retrospective study while external validation will be performed in a second stage. ConclusionASSIST will provide key data to optimize Willem™ platform to detect myocardial infarction based on ECG-assessment alone. Our hypothesis is that such a diagnostic approach may reduce time delays, enhance diagnostic accuracy, and improve clinical outcomes.

Urine Metabolites Changes in Acute Myocardial Infarction Rats via Metabolomic Analysis.

To screen biomarkers for forensic identification of acute myocardial infarction (AMI) by non-targeted metabolomic studies on changes of urine metabolites in rats with AMI. The rat models of the sham surgery group, AMI group and hyperlipidemia + acute myocardial infarction (HAMI) group were established. Ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS) was used to analyze the changes of urine metabolic spectrometry in AMI rats. Principal component analysis, partial least squares-discriminant analysis, and orthogonal partial least squares-discriminant analysis were used to screen differential metabolites. The MetaboAnalyst database was used to analyze the metabolic pathway enrichment and access the predictive ability of differential metabolites. A total of 40 and 61 differential metabolites associated with AMI and HAMI were screened, respectively. Among them, 22 metabolites were common in both rat models. These small metabolites were mainly concentrated in the niacin and nicotinamide metabolic pathways. Within the 95% confidence interval, the area under the curve (AUC) values of receiver operator characteristic curve for N8-acetylspermidine, 3-methylhistamine, and thymine were greater than 0.95. N8-acetylspermidine, 3-methylhistamine, and thymine can be used as potential biomarkers for AMI diagnosis, and abnormal metabolism in niacin and nicotinamide may be the main causes of AMI. This study can provide reference for the mechanism and causes of AMI identification.

Australian paramedic ECG interpretation in acute coronary syndrome

Background: The paramedic use of electrocardiogram (ECG) is the gold standard for prehospital identification of acute myocardial infarction. Following an extension to their scope of practice, all paramedics have the capability to identify an ST-elevation myocardial infarction (STEMI). However, there have been no investigations into paramedic ECG interpretation. Aims: This study aimed to investigate paramedic accuracy regarding ECG interpretation and compare findings with international literature. Methods: Anonymous participants were voluntarily recruited to interpret 12 ECGs. A literature review was undertaken to compare results with previous studies. Findings: Paramedics correctly identified the ECGs with a mean score of 63%. Accuracy in ECG interpretation increased with a higher educational background and specialist training. Postgraduate mean accuracy was 83.33%, with specialist accuracy at 83.53%. Conclusions: Further education and research into interpreting difficult ECGs is necessary. Australian services may consider the implementation of modified cardiac protocols to include suspected non-STEMI.

Identification of acute myocardial infarction and stroke events using the National Health Insurance Service database in Korea.

The escalating burden of cardiovascular disease (CVD) is a critical public health issue worldwide. CVD, especially acute myocardial infarction (AMI) and stroke, is the leading contributor to morbidity and mortality in Korea. We aimed to develop algorithms for identifying AMI and stroke events from the National Health Insurance Service (NHIS) database and validate these algorithms through medical record review. We first established a concept and definition of "hospitalization episode," taking into account the unique features of health claims-based NHIS database. We then developed first and recurrent event identification algorithms, separately for AMI and stroke, to determine whether each hospitalization episode represents a true incident case of AMI or stroke. Finally, we assessed our algorithms' accuracy by calculating their positive predictive values (PPVs) based on medical records of algorithm- identified events. We developed identification algorithms for both AMI and stroke. To validate them, we conducted retrospective review of medical records for 3,140 algorithm-identified events (1,399 AMI and 1,741 stroke events) across 24 hospitals throughout Korea. The overall PPVs for the first and recurrent AMI events were around 92% and 78%, respectively, while those for the first and recurrent stroke events were around 88% and 81%, respectively. We successfully developed algorithms for identifying AMI and stroke events. The algorithms demonstrated high accuracy, with PPVs of approximately 90% for first events and 80% for recurrent events. These findings indicate that our algorithms hold promise as an instrumental tool for the consistent and reliable production of national CVD statistics in Korea.

Paramedic electrocardiogram interpretation in acute coronary syndrome

Background: The paramedic use of electrocardiogram (ECG) is the gold standard for prehospital identification of acute myocardial infarction. Following an extension to their scope of practice, all paramedics have the capability to identify an ST-elevation myocardial infarction (STEMI). However, there have been no investigations into paramedic ECG interpretation. Aims: This study aimed to investigate paramedic accuracy regarding ECG interpretation and compare findings with international literature. Methods: Anonymous participants were voluntarily recruited to interpret 12 ECGs. A literature review was undertaken to compare results with previous studies. Findings: Paramedics correctly identified the ECGs with a mean score of 63%. Accuracy in ECG interpretation increased with a higher educational background and specialist training. Postgraduate mean accuracy was 83.33%, with specialist accuracy at 83.53%. Conclusions: Further education and research into interpreting difficult ECGs is necessary. Australian services may consider the implementation of modified cardiac protocols to include suspected non-STEMI.

Machine learning for early prediction of acute myocardial infarction or death in acute chest pain patients using electrocardiogram and blood tests at presentation

AimsIn the present study, we aimed to evaluate the performance of machine learning (ML) models for identification of acute myocardial infarction (AMI) or death within 30 days among emergency department (ED) chest pain patients.Methods and resultsUsing data from 9519 consecutive ED chest pain patients, we created ML models based on logistic regression or artificial neural networks. Model inputs included sex, age, ECG and the first blood tests at patient presentation: High sensitivity TnT (hs-cTnT), glucose, creatinine, and hemoglobin. For a safe rule-out, the models were adapted to achieve a sensitivity > 99% and a negative predictive value (NPV) > 99.5% for 30-day AMI/death. For rule-in, we set the models to achieve a specificity > 90% and a positive predictive value (PPV) of > 70%. The models were also compared with the 0 h arm of the European Society of Cardiology algorithm (ESC 0 h); An initial hs-cTnT < 5 ng/L for rule-out and ≥ 52 ng/L for rule-in. A convolutional neural network was the best model and identified 55% of the patients for rule-out and 5.3% for rule-in, while maintaining the required sensitivity, specificity, NPV and PPV levels. ESC 0 h failed to reach these performance levels.DiscussionAn ML model based on age, sex, ECG and blood tests at ED arrival can identify six out of ten chest pain patients for safe early rule-out or rule-in with no need for serial blood tests. Future studies should attempt to improve these ML models further, e.g. by including additional input data.

Electromicrofluidic device with integrated PDMS microchannel and laser-induced graphene electrodes for electrochemical detection of cardiac biomarker in a point-of-care platform

By providing a facile and scalable alternative to otherwise complex and resource-intensive synthesis of graphene, laser-induced graphene (LIG) is spearheading the translation of graphene-based propositions to deployable technologies for societal benefit. LIG is a versatile and economical synthesis approach which is being used on a variety of substrates and in a multitude of applications—including miniaturized sensing systems. One aspect that has not been addressed thoroughly in LIG-based miniaturized sensing systems is its successful integration with microfluidics and its possible use in point-of-care settings. To further diversify the applications of LIG with integrated microfluidics, this work reports on the development of an integrated flexible microfluidics-LIG based electrochemical biosensor. The work describes the methodology to develop a polydimethylsiloxane-LIG scribed polyamide microfluidic device in a leakage-free flexible application. In view of the excellent electrical and electrochemical properties of LIG, such device has been employed for electrochemical biosensing. The biosensing capabilities of the microfluidic device were validated via sensing of cardiac troponin I—a gold standard cardiac biomarker for early identification of acute myocardial infarction (AMI). The developed biosensor demonstrated a detection and quantification limit of 45.33 pg ml−1 and 151.10 pg ml−1 respectively, which are in clinically significant ranges for diagnosis of AMI. The µ-fluidic biosensor was also analyzed for stability and interference with other cardiac biomarkers. The developed integrated µ-fluidic electrochemical biosensor was evaluated for possible point-of-source applications in conjunction with a custom 3D printed peristaltic pump and smartphone-enabled miniaturized potentiostat.

Utility of echocardiography in patients with suspected acute myocardial infarction in the presence of left bundle-branch block

Abstract Background Rapid identification of acute myocardial infarction (AMI) as life-threatening disorder by clinical assessment, cardiac troponin and the electrocardiogram (ECG) is important for the early initiation of highly effective, evidence-based therapy. Patients presenting with suspected AMI and left bundle branch block (LBBB) to the emergency department (ED) represent a unique diagnostic and therapeutic challenge, as altered ventricular depolarization masks changes in ventricular repolarization associated with myocardial ischemia. Current guidelines suggest, based on expert opinion, early echocardiography as a helpful tool in patients with suspected AMI and LBBB to identify new wall motion abnormalities, which guides further diagnostics strategies in these patients. Purpose To evaluate the diagnostic accuracy of echocardiography among patients with suspected AMI and LBBB in the recorded ECG at ED presentation. Methods We prospectively evaluated the diagnostic accuracy of echocardiography in patients with LBBB presenting with chest discomfort to 26 ED's in three international, prospective, diagnostic studies. Two independent cardiologists centrally adjudicated the final diagnosis in each study according to the universal definition of myocardial infarction. All patients underwent a clinical assessment that included standardized and detailed medical history including assessment of chest pain characteristics, vital signs, physical examination, 12-lead ECG, continuous ECG rhythm monitoring, pulse oximetry, standard blood test, and chest radiography and echocardiography if indicated. We compared echocardiographic findings in patients with LBBB who were diagnosed with an AMI to those without an AMI. Results Among 283 patients presenting with chest pain and LBBB to the ED, AMI was the final diagnosis in 36% (102 of 283 patients) of patients. An echocardiography had been performed in 100/283 patients (35%) in the emergency department. AMI was the final diagnosis in 41/100 (41%) of patients. A wall motion abnormality in any region was seen in 77 (77%) of patients with no difference between patients diagnosed with AMI (33 patients, 81%) versus without AMI (44 patients, 75%, p=0.49). Additionally, we found no differences for each wall region (Table 1). Most patients with LBBB had moderately reduced left ventricular ejection fraction (LVEF, median 40%), a dilated left atrium (67%) or left ventricular hypertrophy (55%) without any differences between the two groups (Table 1). Conclusions Early echocardiography in patients with suspected AMI and LBBB provided only limited utility to identify patients, which may benefit from immediate coronary angiography. Our findings scrutinize current guidelines and downgrades the utility of echocardiography in this setting. Funding Acknowledgement Type of funding source: Other. Main funding source(s): Swiss National Science Foundation, the Swiss Heart Foundation, the European Union, the Cardiovascular Research Foundation Basel, the University Hospital Basel, Queensland Emergency Medicine Research Foundation, Christchurch Heart Institute and Health Research Council and Heart Foundation of New Zealand, Christchurch Emergency Care Foundation

Identification of acute myocardial infarction in elderly patients using optimized highly sensitive troponin I thresholds

Purpose: Established diagnostic thresholds for high-sensitivity cardiac troponins (hs-cTn) might not apply for elderly patients as they are elevated irrespective of the presence of an acute myocardial infarction (AMI). Aim of the present study was to investigate hs-cTnI in elderly patients with suspected AMI and to calculate optimized diagnostic cutoffs.Material and methods: Data from a prospective multi-centre study and from a second independent prospective single-centre cohort study were analysed. A number of 2903 patients were eligible for further analysis. Patients > 70 years were classified as elderly. hs-cTnI was measured upon admission.Results: Around 34.7% of 2903 patients were classified as elderly. Around 22.5% of elderly patients were finally diagnosed with AMI. Elderly patients had higher hs-cTnI levels at admission irrespective of the final diagnosis (p < 0.001). According to the AUROC, hs-cTnI was a strong marker for detection of AMI in elderly patients. Application of the 99th percentile cutoffs showed a substantially lower specificity in elderly. By using optimized thresholds, specificity was improved to levels as in younger patients in both cohorts but accompanied with a decrease in sensitivity.Conclusions: hs-cTnI levels have a lower specificity for detecting AMI in elderly patients. This lower specificity can be improved by using hs-cTnI thresholds optimized for elderly patients.

Abstract 186: Improving Identification and Assessment of Readmission Risk for Acute Myocardial Infarction and Heart Failure Patients Following Implementation of a National Quality Improvement Program

Background: Optimal transition care represents an important step in mitigating the risk of early hospital readmission. For many hospitals, however, resources are not available to support transition care processes, and hospitals may not be able to identify patients in greatest need. It remains unknown whether a coordinated quality improvement campaign could help to increase a) identification of at-risk patients and b) use of a readmission risk score to identify patients needing extra services/resources. Methods: The American College of Cardiology Patient Navigator Program was designed as a 2-year (2015-2017) quality improvement campaign to assess the impact of transition-care interventions on transition care performance metrics for patients with acute myocardial infarction (AMI) and heart failure (HF) at 35 acute care hospitals. All sites were active participants in the NCDR ACTION Registry. Facilities were free to choose their transition care priorities, with at least 3 goals established at baseline. Pre-discharge identification of AMI and HF patients and assessment of their respective readmission risk were 4 of the 36 metrics tracked quarterly. Performance reports were provided regularly to the individual institutions. Sharing of best practices was actively encouraged through webinars, a listserv, and an online dashboard with display of blinded performance for all 35 hospitals. Results: At baseline, 31% (11/35) and 23% (8/35) of facilities did not have a process for prospectively identifying AMI and HF patients, respectively. At 2 years, the rate of not having processes decreased to 8% (3/35) and 3% (1/35), respectively. Among hospitals able to identify AMI and HF patients, there was high patient-level identification performance from the outset (91% for AMI and 86% for HF at baseline), with added improvement over 2 years (+2.2% for AMI and +9.3% for HF). At baseline, processes to assess readmission risk for AMI and HF patients were only completed by 26% (9/35) and 31% (11/35) of facilities, respectively. At 2 years, AMI and HF readmission risk assessment rose to 80% (28/35) and 86% (30/35), respectively. Similar improvements were noted at the patient-level, with 34% (52% --&gt; 86%) and 16% (75% --&gt; 91%) absolute 2-year increases in the percentage of AMI and HF patients undergoing assessment of readmission risk, respectively. Conclusions: Implementation of a quality improvement campaign focused on care transition can substantially improve prospective identification of AMI and HF patients and assessment of their readmission risk. It remains to be determined whether process improvement lead to reduction in 30-day readmission and/or improvement in other clinically important outcome measures.

Evaluation of High-Sensitivity Cardiac Troponin I Levels in Patients With Suspected Acute Coronary Syndrome.

Low concentrations of high-sensitivity cardiac troponin I determined on presentation to the emergency department (ED) have been shown to have an excellent negative predictive value (NPV) for the identification of acute myocardial infarction. The sensitivity, and therefore clinical applicability, of such testing strategies is unknown. To determine the diagnostic performance of low concentrations of high-sensitivity cardiac troponin I in patients with suspected cardiac chest pain and an electrocardiogram showing no ischemia as an indicator of acute myocardial infarction. A pooled analysis of 5 international (Australia, New Zealand, and England) prospective, observational cohort studies with blinded outcome assessment and 30-day follow-up was conducted. A total of 3155 patients presenting with symptoms suggestive of cardiac ischemia were included in the analysis. Eligible patients had a nonischemic electrocardiogram determined and high-sensitivity troponin I measured at presentation. The lower limit of detection (1.2 ng/L) as well as cutoff concentrations rounded to the nearest integer for a high-sensitivity troponin I assay were used in the analysis. Recruitment was undertaken from November 1, 2007, to August 10, 2013. The primary outcome was fatal or nonfatal acute myocardial infarction occurring within 30 days of ED presentation, adjudicated with serial troponin testing. The secondary outcome was the proportion of patients potentially suitable for early discharge at each cutoff concentration. Of the 3155 eligible patients, 1771 were male (56.1%), and mean (SD) age was 57.4 (13.3) years. Acute myocardial infarction developed in 291 individuals (9.2%). The 1.2-ng/L limit of detection gave a sensitivity of 99.0% (95% CI, 96.8%-99.7%) and an NPV of 99.5% (95% CI, 98.4%-99.9%). This cutoff level would allow for early discharge of 594 patients (18.8%). All higher rounded cutoff values had sensitivities less than 98.0%. Diagnostic performance of the limit of detection was maintained when patients were stratified by age, sex, risk factors, presence of coronary artery disease, and early presentation. High-sensitivity troponin I concentrations determined at presentation to the ED that were below the limit of detection identified 18.8% of patients potentially suitable for discharge, with a high sensitivity for acute myocardial infarction. Rounded cutoff values above the limit of detection may not have the required sensitivity for clinical implementation.

Left bundle branch block, chest pain and catheterization laboratory activation: an unavoidable cascade reaction?

Identification of acute myocardial infarction (AMI) in the presence of left bundle branch block (LBBB) remains challenging.European guidelines recommend prompt reperfusion therapy in patients with suspected ongoing myocardial ischemia and new or presumably new LBBB, whereas AHA/ACC guidelines state that LBBB should not be considered diagnostic of AMI in isolation.Sgarbossa criteria and their recent modified version with the introduction of ST/S ratio can be helpful in this setting. A clinical–instrumental algorithm to manage suspected AMI in the presence of LBBB has been recently proposed. We present five paradigmatic clinical cases.

Analysis of Multi-Lead ECG Signals using Decision Tree Algorithms

Electrocardiogram (ECG) is a signal with unique, valuable information about the functional aspects of the heart with respect to time. The automatic analysis of ECG signals is an important application since the early detection of heart diseases/abnormalities can prolong life and enhance the quality of living through appropriate treatment. The ECG is collected using a number of electrodes placed in different positions on the body. Multi-lead ECGs acquired simultaneously helps in better diagnosis of heart diseases. This paper focuses on classification of healthy and Myocardial infarction signals. The identification of acute myocardial infarction with symptoms of Ischemia is critical to delivering appropriate medical care. In this paper decision tree based classifiers are implemented for the classification of ECG signals. The signals were analyzed for 34 normal and 33 myocardial infarction patients in the database PTB from the domain Physionet.org. The classifiers, J48 and Classification and Regression Trees (CART) are compared with respect to accuracy measures. The J48 classifier performs better with the correct classification rate of 98% and 0.9 Kappa statistics. General Terms Signal Processing, Classification, Data Mining.

Features of pathogenesis, clinical course and diagnosis of acute cholecystitis of patients with decompensated cardiovascular diseases

The work presents the features of pathogenesis, clinical course and diagnosis of acute cholecystitis of patients with decompensated cardiovascular diseases have been submitted in this report. The main diseases of cardiovascular system that affects the prognosis of acute cholecystitis have been set off. The sufficient detailed is written about the criteria for patients at risk. Listed severe somatic diseases, which are frequent in older patients being treated in surgical hospitals. The pathogenetic link between inflammatory disease of the gallbladder and cardiovascular system has been explained. The problem of mutual deterioration between acute cholecystitis and different manifestations of coronary artery disease has been reviewed. The noting widespread introduction of new non-invasive methods (ultrasonography, computer tomography and magnetic resonance tomography) and invasive (endovideosurgery) diagnostics. Detailed characteristics of such instrumental techniques as ultrasonography, magnetic resonance cholangiopancreatography, magnetic tomography, endoscopic retrograde cholangiopancreatography, diagnostic laparoscopy has been given. The role of specific biochemical markers of necrosis has been showed: creatinephosphokinase, its heart fraction, troponin test. Possible changes on the electrocardiogram of patients with acute cholecystitis and reasons for their appearance have been described. Detailed recommendations for the identification of acute myocardial infarction of patients with acute cholecystitis using markers of myocardial damage have been given.

Identification of acute myocardial infarction in patients with atrial fibrillation and chest pain with a contemporary sensitive troponin I assay.

BackgroundThe introduction of modern troponin assays has facilitated diagnosis of acute myocardial infarction due to improved sensitivity with corresponding loss of specificity. Atrial fibrillation (AF) is associated with elevated levels of troponin. The aim of the present study was to evaluate the diagnostic performance of troponin I in patients with suspected acute coronary syndrome and chronic AF.MethodsContemporary sensitive troponin I was assayed in a derivation cohort of 90 patients with suspected acute coronary syndrome and chronic AF to establish diagnostic cut-offs. These thresholds were validated in an independent cohort of 314 patients with suspected myocardial infarction and AF upon presentation. Additionally, changes in troponin I concentration within 3 hours were used.ResultsIn the derivation cohort, optimized thresholds with respect to a rule-out strategy with high sensitivity and a rule-in strategy with high specificity were established. In the validation cohort, application of the rule-out cut-off led to a negative predictive value of 97 %. The rule-in cut-off was associated with a positive predictive value of 88 % compared with 71 % if using the 99th percentile cut-off. In patients with troponin I levels above the specificity-optimized threshold, additional use of the 3-hour change in absolute/relative concentration resulted in a further improved positive predictive value of 96 %/100 %.ConclusionsTroponin I concentration and the 3-hour change in its concentration provide valid diagnostic information in patients with suspected myocardial infarction and chronic AF. With regard to AF-associated elevation of troponin levels, application of diagnostic cut-offs other than the 99th percentile might be beneficial.Electronic supplementary materialThe online version of this article (doi:10.1186/s12916-015-0410-8) contains supplementary material, which is available to authorized users.

ACUTE MYOCARDIAL INFARCTION;

A delay in confirming a diagnosis of AMI may increase the risk of complication and a delay in ruling out the diagnosiscontributes to overcrowding in the emergency department. A crucial step in confirming or ruling out the diagnosis of AMI is themeasurement of myocardial enzymes in the serum. Early administration of thrombolytic therapy results in improved survival after AMI. Sothis study was planned to find out the serum marker with a better predictive value for the identification of acute myocardial infarction at thetime of admission. Design: Cross-sectional study. Setting: Emergency department of Punjab Institute of Cardiology, Lahore. Period:15th May, 2008 to 15th July, 2008. Methods: The study population consisted of 70 patients. Patients from both sexes, with clinicalhistory of typical chest pain for more than 30 minutes in duration with evidence of acute changes of myocardial infarction on ECG wereincluded in the study. This study was conducted to compare the positive predictive value and negative predictive value of creatine kinase-MB (CK-MB), cardiac troponin T (CTnT) and cardiac troponin I (CTnI) for detection of AMI. Data analysis was performed with StatisticalPackage for Social Sciences 11.5 (SPSS 11.5). Results: 88.6% cases had CTnI concentration more than the limit value while 11.4%cases had CTnI less than the limit value. The concentration of CTnT was more than the limit value in 70% cases and below the limit value in30% cases. The concentration of CK-MB was more than the limit value in 35.7% cases and 64.3% cases had CK-MB value less than thelimit value. The positive predictive value (PPV) of CtnI is 100% and negative predictive value (NPV) of CTnT is 100% in this study.Conclusions: It is concluded that CTnl is the better marker for the identification of acute myocardial infarction and CTnT is the bettermarker to exclude AMI as compared to CK-MB.

Identification of acute myocardial infarction from electronic healthcare records using different disease coding systems: a validation study in three European countries

ObjectiveTo evaluate positive predictive value (PPV) of different disease codes and free text in identifying acute myocardial infarction (AMI) from electronic healthcare records (EHRs).DesignValidation study of cases of AMI identified...

Necrosis Avidity: A Newly Discovered Feature of Hypericin and its Preclinical Applications in Necrosis Imaging

Hypericin has been widely studied as a potent photosensitizer for photodynamic therapy in both preclinical and clinical settings. Recently, hypericin has also been discovered to have a specific avidity for necrotic tissue. This affinity is also observed in a series of radiolabeled derivatives of hypericin, including [123I]iodohypericin, [124I]iodohypericin, and [131I]iodohypericin. Hypericin, along with other necrosis-avid contrast agents, has been investigated for use in noninvasively targeting necrotic tissues in numerous disorders. Potential clinical applications of hypericin include the identification of acute myocardial infarction, evaluation of tissue viability, assessment of therapeutic responses to treatments, and interventional procedures for solid tumors. The mechanisms of necrosis avidity in hypericin remain to be fully elucidated, although several hypotheses have been suggested. In particular, it has been proposed that the necrosis avidity of hypericin is compound specific; for instance, cholesterol, phosphatidylserine, or phosphatidylethanolamine components in the phospholipid bilayer of cellular membranes may be the major targets for its observed selectivity. Further investigations are needed to identify the specific binding moiety that is responsible for the necrosis avidity of hypericin.