Cardiac biomarkers by point-of-care testing - back to the future?

The measurement of the cardiac troponins (cTn), cardiac troponin T (cTnT) and cardiac troponin I (cTnI) are integral to the management of patients with suspected acute coronary syndromes (ACS). Patients without clear electrocardiographic evidence of myocardial infarction require measurement of cTnT or cTnI. It therefore follows that a rapid turnaround time (TAT) combined with the immediacy of results return which is achieved by point-of-care testing (POCT) offers a substantial clinical benefit. Rapid results return plus immediate decision-making should translate into improved patient flow and improved therapeutic decision-making. The development of high sensitivity troponin assays offer significant clinical advantages. Diagnostic algorithms have been devised utilising very low cut-offs at first presentation and rapid sequential measurements based on admission and 3 h sampling, most recently with admission and 1 h sampling. Such troponin algorithms would be even more ideally suited to point-of-care testing as the TAT achieved by the diagnostic laboratory of typically 60 min corresponds to the sampling interval required by the clinician using the algorithm. However, the limits of detection and analytical imprecision required to utilise these algorithms is not yet met by any easy-to-use POCT systems

Computer Aided ECG Analysis - State of the Art and Upcoming Challenges

In this paper we present current achievements in computer aided ECG analysis and their applicability in real world medical diagnosis process. Most of the current work is covering problems of removing noise, detecting heartbeats and rhythm-based analysis. There are some advancements in particular ECG segments detection and beat classifications but with limited evaluations and without clinical approvals. This paper presents state of the art advancements in those areas till present day. Besides this short computer science and signal processing literature review, paper covers future challenges regarding the ECG signal morphology analysis deriving from the medical literature review. Paper is concluded with identified gaps in current advancements and testing, upcoming challenges for future research and a bullseye test is suggested for morphology analysis evaluation.Comment: 7 pages, 3 figures, IEEE EUROCON 2013 International conference on computer as a tool, 1-4 July 2013, Zagreb, Croati

ESC core curriculum for the general cardiologist (2013)

[No abstract available

An artificial neural network to safely reduce the number of ambulance ECGs transmitted for physician assessment in a system with prehospital detection of ST elevation myocardial infarction

<p>Abstract</p> <p>Background</p> <p>Pre-hospital electrocardiogram (ECG) transmission to an expert for interpretation and triage reduces time to acute percutaneous coronary intervention (PCI) in patients with ST elevation Myocardial Infarction (STEMI). In order to detect all STEMI patients, the ECG should be transmitted in all cases of suspected acute cardiac ischemia. The aim of this study was to examine the ability of an artificial neural network (ANN) to safely reduce the number of ECGs transmitted by identifying patients without STEMI and patients not needing acute PCI.</p> <p>Methods</p> <p>Five hundred and sixty ambulance ECGs transmitted to the coronary care unit (CCU) in routine care were prospectively collected. The ECG interpretation by the ANN was compared with the diagnosis (STEMI or not) and the need for an acute PCI (or not) as determined from the Swedish coronary angiography and angioplasty register. The CCU physician's real time ECG interpretation (STEMI or not) and triage decision (acute PCI or not) were registered for comparison.</p> <p>Results</p> <p>The ANN sensitivity, specificity, positive and negative predictive values for STEMI was 95%, 68%, 18% and 99%, respectively, and for a need of acute PCI it was 97%, 68%, 17% and 100%. The area under the ANN's receiver operating characteristics curve for STEMI detection was 0.93 (95% CI 0.89-0.96) and for predicting the need of acute PCI 0.94 (95% CI 0.90-0.97). If ECGs where the ANN did not identify a STEMI or a need of acute PCI were theoretically to be withheld from transmission, the number of ECGs sent to the CCU could have been reduced by 64% without missing any case with STEMI or a need of immediate PCI.</p> <p>Conclusions</p> <p>Our ANN had an excellent ability to predict STEMI and the need of acute PCI in ambulance ECGs, and has a potential to safely reduce the number of ECG transmitted to the CCU by almost two thirds.</p

Probabilistic classification of acute myocardial infarction from multiple cardiac markers

Logistic regression and Gaussian mixture model (GMM) classifiers have been trained to estimate the probability of acute myocardial infarction (AMI) in patients based upon the concentrations of a panel of cardiac markers. The panel consists of two new markers, fatty acid binding protein (FABP) and glycogen phosphorylase BB (GPBB), in addition to the traditional cardiac troponin I (cTnI), creatine kinase MB (CKMB) and myoglobin. The effect of using principal component analysis (PCA) and Fisher discriminant analysis (FDA) to preprocess the marker concentrations was also investigated. The need for classifiers to give an accurate estimate of the probability of AMI is argued and three categories of performance measure are described, namely discriminatory ability, sharpness, and reliability. Numerical performance measures for each category are given and applied. The optimum classifier, based solely upon the samples take on admission, was the logistic regression classifier using FDA preprocessing. This gave an accuracy of 0.85 (95% confidence interval: 0.78–0.91) and a normalised Brier score of 0.89. When samples at both admission and a further time, 1–6 h later, were included, the performance increased significantly, showing that logistic regression classifiers can indeed use the information from the five cardiac markers to accurately and reliably estimate the probability AMI

Prolonged PR interval, first-degree heart block and adverse cardiovascular outcomes: a systematic review and meta-analysis

Objective: First-degree atrioventricular block is frequently encountered in clinical practice and is generally considered a benign process. However, there is emerging evidence that prolonged PR interval may be associated with adverse outcomes. This study aims to determine if prolonged PR interval is associated with adverse cardiovascular outcomes and mortality. Methods: We searched MEDLINE and EMBASE for studies that evaluated clinical outcomes associated with prolonged and normal PR intervals. Relevant studies were pooled using random effects meta-analysis for risk of mortality, cardiovascular mortality, heart failure, coronary heart disease, atrial fibrillation and stroke or transient ischaemic attack (TIA). Sensitivity analyses were performed considering the population type and the use of adjustments. Results: Our search yielded 14 studies that were undertaken between 1972 and 2011 with 400 750 participants. Among the studies that adjusted for potential confounders, the pooled results suggest an increased risk of mortality with prolonged PR interval risk ratio (RR) 1.24 95% CI 1.02 to 1.51, five studies. Prolonged PR interval was associated with significant risk of heart failure or left ventricular dysfunction (RR 1.39 95% CI 1.18 to 1.65, three studies) and atrial fibrillation (RR 1.45 95% CI 1.23 to 1.71, eight studies) but not cardiovascular mortality, coronary heart disease or myocardial infarction or stroke or TIA. Similar observations were recorded when limited to studies of first-degree heart block. Conclusions: Data from observational studies suggests a possible association between prolonged PR interval and significant increases in atrial fibrillation, heart failure and mortality. Future prospective studies are needed to confirm the relationships reported, consider possible mechanisms and define the optimal monitoring strategy for such patients

Identifying critically important cardiovascular outcomes for trials in hemodialysis: an international survey with patients, caregivers and health professionals

BACKGROUND: Cardiovascular disease (CVD) is a major contributor to morbidity and mortality in people on hemodialysis (HD). Cardiovascular outcomes are reported infrequently and inconsistently across trials in HD. This study aimed to identify the priorities of patients/caregivers and health professionals (HPs) for CVD outcomes to be incorporated into a core outcome set reported in all HD trials. METHODS: In an international online survey, participants rated the absolute importance of 10 cardiovascular outcomes (derived from a systematic review) on a 9-point Likert scale, with 7-9 being critically important. The relative importance was determined using a best-worst scale. Likert means, medians and proportions and best-worst preference scores were calculated for each outcome. Comments were thematically analyzed. RESULTS: Participants included 127 (19%) patients/caregivers and 549 (81%) HPs from 53 countries, of whom 530 (78%) completed the survey in English and 146 (22%) in Chinese. All but one cardiovascular outcome ('valve replacement') was rated as critically important (Likert 7-9) by all participants; 'sudden cardiac death', 'heart attack', 'stroke' and 'heart failure' were all rated at the top by patients/caregivers (median Likert score 9). Patients/caregivers ranked the same four outcomes as the most important outcomes with mean preference scores of 6.2 (95% confidence interval 4.8-7.5), 5.9 (4.6-7.2), 5.3 (4.0-6.6) and 4.9 (3.6-6.3), respectively. The same four outcomes were ranked most highly by HPs. We identified five themes underpinning the prioritization of outcomes: 'clinical equipoise and potential for intervention', 'specific or attributable to HD', 'severity or impact on the quality of life', 'strengthen knowledge and education', and 'inextricably linked burden and risk'. CONCLUSIONS: Patients and HPs believe that all cardiovascular outcomes are of critical importance but consistently identify sudden cardiac death, myocardial infarction, stroke and heart failure as the most important outcomes to be measured in all HD trials