Feasibility and performance of a device for automatic self-detection of symptomatic acute coronary artery occlusion in outpatients with coronary artery disease : a multicentre observational study

Background Time delay between onset of symptoms and seeking medical attention is a major determinant of mortality and morbidity in patients with acute coronary artery occlusion. Response time might be reduced by reliable self-detection. We aimed to formally assess the proof-of-concept and accuracy of self-detection of acute coronary artery occlusion by patients during daily life situations and during the very early stages of acute coronary artery occlusion. Methods In this multicentre, observational study, we tested the operational feasibility, specificity, and sensitivity of our RELF method, a three-lead detection system with an automatic algorithm built into a mobile handheld device, for detection of acute coronary artery occlusion. Patients were recruited continuously by physician referrals from three Belgian hospitals until the desired sample size was achieved, had been discharged with planned elective percutaneous coronary intervention, and were able to use a smartphone; they were asked to perform random ambulatory selfrecordings for at least 1 week. A similar self-recording was made before percutaneous coronary intervention and at 60 s of balloon occlusion. Patients were clinically followed up until 1 month after discharge. We quantitatively assessed the operational feasibility with an automated dichotomous quality check of self-recordings. Performance was assessed by analysing the receiver operator characteristics of the ST difference vector magnitude. This trial is registered with ClinicalTrials.gov, number NCT02983396. Findings From Nov 18, 2016, to April 25, 2018, we enrolled 64 patients into the study, of whom 59 (92%) were eligible for self-applications. 58 (91%) of 64 (95% CI 81.0-95.6) patients were able to perform ambulatory self-recordings. Of all 5011 self-recordings, 4567 (91%) were automatically classified as successful within 1 min. In 65 balloon occlusions, 63 index tests at 60 s of occlusion in 55 patients were available. The mean specificity of daily life recordings was 0.96 (0.95-0.97). The mean false positive rate during daily life conditions was 4.19% (95% CI 3.29-5.10). The sensitivity for the target conditions was 0.87 (55 of 63; 95% CI 0.77-0.93) for acute coronary artery occlusion, 0.95 (54 of 57; 0.86-0.98) for acute coronary artery occlusion with electrocardiogram (ECG) changes, and 1.00 (35 of 35) for acute coronary artery occlusion with ECG changes and ST-segment elevation myocardial infarction criteria (STEMI). The index test was more sensitive to detect a 60 s balloon occlusion than the STEMI criteria on 12-lead ECG (87% vs 56%; p<0.0001). The proportion of total variation in study estimates due to heterogeneity between patients (I-2) was low (12.6%). The area under the receiver operator characteristics curve was 0.973 (95% CI 0.956-0.990) for acute coronary artery occlusion at different cutoff values of the magnitude of the ST difference vector. No patients died during the study. Interpretation Self-recording with our RELF device is feasible for most patients with coronary artery disease. The sensitivity and specificity for automatic detection of the earliest phase of acute coronary artery occlusion support the concept of our RELF device for patient empowerment to reduce delay and increase Survival without overloading emergency services. Copyright (C) 2019 The Author(s). Published by Elsevier Ltd

A Review of Atrial Fibrillation Detection Methods as a Service

Atrial Fibrillation (AF) is a common heart arrhythmia that often goes undetected, and even if it is detected, managing the condition may be challenging. In this paper, we review how the RR interval and Electrocardiogram (ECG) signals, incorporated into a monitoring system, can be useful to track AF events. Were such an automated system to be implemented, it could be used to help manage AF and thereby reduce patient morbidity and mortality. The main impetus behind the idea of developing a service is that a greater data volume analyzed can lead to better patient outcomes. Based on the literature review, which we present herein, we introduce the methods that can be used to detect AF efficiently and automatically via the RR interval and ECG signals. A cardiovascular disease monitoring service that incorporates one or multiple of these detection methods could extend event observation to all times, and could therefore become useful to establish any AF occurrence. The development of an automated and efficient method that monitors AF in real time would likely become a key component for meeting public health goals regarding the reduction of fatalities caused by the disease. Yet, at present, significant technological and regulatory obstacles remain, which prevent the development of any proposed system. Establishment of the scientific foundation for monitoring is important to provide effective service to patients and healthcare professionals

A descriptive study of the use of troponin I testing at a Cape Town district hospital

Introduction: Troponin I tests have been shown to be accurate and are relied upon to assist in making critical decisions regarding patient care in patients presenting with chest pain. The tests are expensive, however, and so their rational use becomes extremely important in a budget-constrained public health sector. The aim of this study was to describe how Troponin I tests are used throughout Victoria Hospital, by a range of requesting clinicians, working in different specialties. Methods A cross-sectional, prospective design was employed, using multiple data sources. We collected a consecutive sample over a three-month period from Victoria hospital’s Emergency Centre using a dedicated data collection tool connected to use of the point-of-care troponin I test. We supplemented this prospective sample with outcome data, using the hospital’s electronic admission record. Results Three hundred and sixteen patient entries were included in the final results. The majority of Troponin tests were negative (70%). Discharge directly from Emergency Centre was 10% in Troponin I positive patients, 37,5% in Equivocal Troponin patients, and 65% in Troponin negative patients. Furthermore, patients were twice as likely to be transferred to a tertiary facility if their Troponin was positive (24%), compared to equivocal (10.4%) or negative (12%). Discussion Chest pain was the most common presenting complaint, with Acute Coronary Syndrome being the most common working diagnosis. The clinical management of patients varied considerably when comparing their Troponin I result. Troponin I appears to be used as an effective rule-out tool in the decision-making pathway

The Recognition of STEMI by Paramedics and the Effect of Computer inTerpretation (RESPECT): a randomised crossover feasibility study

Background : The appropriate management of patients with ST-segment elevation myocardial infarction (STEMI) depends on accurate interpretation of the 12-lead ECG by paramedics. Computer interpretation messages on ECGs are often provided, but the effect they exert on paramedics’ decision-making is not known. The objective of this study was to assess the feasibility of using an online assessment tool, and collect pilot data, for a definitive trial to determine the effect of computer interpretation messages on paramedics’ diagnosis of STEMI. Methods : The Recognition of STEMI by Paramedics and the Effect of Computer inTerpretation (RESPECT) feasibility study was a randomised crossover trial using a bespoke, web-based assessment tool. Participants were randomly allocated 12 of 48 ECGs, with an equal mix of correct and incorrect computer interpretation messages, and STEMI and STEMI-mimics. The nature of the responses required a cross-classified multi-level model. Results : 254 paramedics consented into the study, 205 completing the first phase and 150 completing phase two. The adjusted OR for a correct paramedic interpretation, when the computer interpretation was correct (true positive for STEMI or true negative for STEMI-mimic), was 1.80 (95% CI 0.84 to 4.91) and 0.58 (95% CI 0.41 to 0.81) when the computer interpretation was incorrect (false positive for STEMI or false negative for STEMI-mimic). The intraclass correlation coefficient for correct computer interpretations was 0.33 for participants and 0.17 for ECGs, and for incorrect computer interpretations, 0.06 for participants and 0.01 for ECGs. Conclusions : Determining the effect of computer interpretation messages using a web-based assessment tool is feasible, but the design needs to take clustered data into account. Pilot data suggest that computer messages influence paramedic interpretation, improving accuracy when correct and worsening accuracy when incorrect