The burden and natural history of cardiac pathology at TB diagnosis in a high-HIV prevalence district in Zambia: protocol for the TB-Heart study.

BACKGROUND: Tuberculosis (TB) continues to be a major cause of death across sub-Saharan Africa (SSA). In parallel, non-communicable disease and especially cardiovascular disease (CVD) burden has increased substantially in the region. Cardiac manifestations of TB are well-recognised but the extent to which they co-exist with pulmonary TB (PTB) has not been systematically evaluated. The aim of this study is to improve understanding of the burden of cardiac pathology in PTB in those living with and without HIV in a high-burden setting. METHODS: This is a cross-sectional and natural history study to evaluate the burden and natural history of cardiac pathology in participants with PTB in Lusaka, Zambia, a high burden setting for TB and HIV. Participants with PTB, with and without HIV will be consecutively recruited alongside age- and sex-matched TB-uninfected comparators on a 2:1 basis. Participants will undergo baseline assessments to collect clinical, socio-demographic, functional, laboratory and TB disease impact data followed by point-of-care and standard echocardiography. Participants with PTB will undergo further repeat clinical and functional examination at two- and six months follow-up. Those with cardiac pathology at baseline will undergo repeat echocardiography at six months. DISCUSSION: The outcomes of the study are to a) determine the burden of cardiac pathology at TB diagnosis, b) describe its association with patient-defining risk factors and biochemical markers of cardiac injury and stretch and c) describe the natural history of cardiac pathology during the course of TB treatment.

Point-of-care screening for heart failure with reduced ejection fraction using artificial intelligence during ECG-enabled stethoscope examination in London, UK: a prospective, observational, multicentre study.

BACKGROUND: Most patients who have heart failure with a reduced ejection fraction, when left ventricular ejection fraction (LVEF) is 40% or lower, are diagnosed in hospital. This is despite previous presentations to primary care with symptoms. We aimed to test an artificial intelligence (AI) algorithm applied to a single-lead ECG, recorded during ECG-enabled stethoscope examination, to validate a potential point-of-care screening tool for LVEF of 40% or lower. METHODS: We conducted an observational, prospective, multicentre study of a convolutional neural network (known as AI-ECG) that was previously validated for the detection of reduced LVEF using 12-lead ECG as input. We used AI-ECG retrained to interpret single-lead ECG input alone. Patients (aged ≥18 years) attending for transthoracic echocardiogram in London (UK) were recruited. All participants had 15 s of supine, single-lead ECG recorded at the four standard anatomical positions for cardiac auscultation, plus one handheld position, using an ECG-enabled stethoscope. Transthoracic echocardiogram-derived percentage LVEF was used as ground truth. The primary outcome was performance of AI-ECG at classifying reduced LVEF (LVEF ≤40%), measured using metrics including the area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity, with two-sided 95% CIs. The primary outcome was reported for each position individually and with an optimal combination of AI-ECG outputs (interval range 0-1) from two positions using a rule-based approach and several classification models. This study is registered with ClinicalTrials.gov, NCT04601415. FINDINGS: Between Feb 6 and May 27, 2021, we recruited 1050 patients (mean age 62 years [SD 17·4], 535 [51%] male, 432 [41%] non-White). 945 (90%) had an ejection fraction of at least 40%, and 105 (10%) had an ejection fraction of 40% or lower. Across all positions, ECGs were most frequently of adequate quality for AI-ECG interpretation at the pulmonary position (979 [93·3%] of 1050). Quality was lowest for the aortic position (846 [80·6%]). AI-ECG performed best at the pulmonary valve position (p=0·02), with an AUROC of 0·85 (95% CI 0·81-0·89), sensitivity of 84·8% (76·2-91·3), and specificity of 69·5% (66·4-72·6). Diagnostic odds ratios did not differ by age, sex, or non-White ethnicity. Taking the optimal combination of two positions (pulmonary and handheld positions), the rule-based approach resulted in an AUROC of 0·85 (0·81-0·89), sensitivity of 82·7% (72·7-90·2), and specificity of 79·9% (77·0-82·6). Using AI-ECG outputs from these two positions, a weighted logistic regression with l2 regularisation resulted in an AUROC of 0·91 (0·88-0·95), sensitivity of 91·9% (78·1-98·3), and specificity of 80·2% (75·5-84·3). INTERPRETATION: A deep learning system applied to single-lead ECGs acquired during a routine examination with an ECG-enabled stethoscope can detect LVEF of 40% or lower. These findings highlight the potential for inexpensive, non-invasive, workflow-adapted, point-of-care screening, for earlier diagnosis and prognostically beneficial treatment. FUNDING: NHS Accelerated Access Collaborative, NHSX, and the National Institute for Health Research.

Adapting the role of handheld echocardiography during the COVID-19 pandemic: A practical guide.

The COVID-19 pandemic has altered our approach to inpatient echocardiography delivery. There is now a greater focus to address key clinical questions likely to make an immediate impact in management, particularly during the period of widespread infection. Handheld echocardiography (HHE) can be used as a first-line assessment tool, limiting scanning time and exposure to high viral load. This article describes a potential role for HHE during a pandemic. We propose a protocol with a reporting template for a focused core dataset necessary in delivering an acute echocardiography service in the setting of a highly contagious disease, minimising risk to the operator. We cover the scenarios typically encountered in the acute cardiology setting and how an expert trained echocardiography team can identify such pathologies using a limited imaging format and include cardiac presentations encountered in those patients acutely unwell with COVID-19.

British Society of Echocardiography Departmental Accreditation Standards 2019 with input from the Intensive Care Society.

This article sets out a summary of standards for departmental accreditation set by the British Society of Echocardiography (BSE) Departmental Accreditation Committee. Full accreditation standards are available at www.bsecho.org. The BSE were the first national organisation to establish a quality standards framework for departments that support the practice of individual echocardiographers. This is an updated version which recognises that, not only should all echocardiographers be individually accredited as competent to practice, but that departments also need to be well organised and have the facilities, equipment and processes to ensure the services they deliver are of an appropriate clinical standard. In combination with individual accreditation, departmental accreditation lays down standards to help ensure safe and effective patient care. These standards supersede the 2012 BSE Departmental Accreditation Standards. Standards are set to cover all potential areas of practice, including transthoracic (level 2) echocardiography, transoesophageal echocardiography, stress echocardiography, training, and emergency (level 1) echocardiography. The emergency echocardiography standard is a new addition to departmental accreditation and has been developed with input from the Intensive Care Society.

Dobutamine Stress Echocardiography Ischemia as a Predictor of the Placebo-Controlled Efficacy of Percutaneous Coronary Intervention in Stable Coronary Artery Disease: The Stress Echocardiography-Stratified Analysis of ORBITA.

BACKGROUND: Dobutamine stress echocardiography is widely used to test for ischemia in patients with stable coronary artery disease. In this analysis, we studied the ability of the prerandomization stress echocardiography score to predict the placebo-controlled efficacy of percutaneous coronary intervention (PCI) within the ORBITA trial (Objective Randomised Blinded Investigation With Optimal Medical Therapy of Angioplasty in Stable Angina). METHODS: One hundred eighty-three patients underwent dobutamine stress echocardiography before randomization. The stress echocardiography score is broadly the number of segments abnormal at peak stress, with akinetic segments counting double and dyskinetic segments counting triple. The ability of prerandomization stress echocardiography to predict the placebo-controlled effect of PCI on response variables was tested by using regression modeling. RESULTS: At prerandomization, the stress echocardiography score was 1.56±1.77 in the PCI arm (n=98) and 1.61±1.73 in the placebo arm (n=85). There was a detectable interaction between prerandomization stress echocardiography score and the effect of PCI on angina frequency score with a larger placebo-controlled effect in patients with the highest stress echocardiography score (Pinteraction=0.031). With our sample size, we were unable to detect an interaction between stress echocardiography score and any other patient-reported response variables: freedom from angina (Pinteraction=0.116), physical limitation (Pinteraction=0.461), quality of life (Pinteraction=0.689), EuroQOL 5 quality-of-life score (Pinteraction=0.789), or between stress echocardiography score and physician-assessed Canadian Cardiovascular Society angina class (Pinteraction=0.693), and treadmill exercise time (Pinteraction=0.426). CONCLUSIONS: The degree of ischemia assessed by dobutamine stress echocardiography predicts the placebo-controlled efficacy of PCI on patient-reported angina frequency. The greater the downstream stress echocardiography abnormality caused by a stenosis, the greater the reduction in symptoms from PCI. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov. Unique identifier: NCT02062593.

A patient-centred model to quality assure outputs from an echocardiography department: consensus guidance from the British Society of Echocardiography.

Background Quality assurance (QA) of echocardiographic studies is vital to ensure that clinicians can act on findings of high quality to deliver excellent patient care. To date, there is a paucity of published guidance on how to perform this QA. The British Society of Echocardiography (BSE) has previously produced an Echocardiography Quality Framework (EQF) to assist departments with their QA processes. This article expands on the EQF with a structured yet versatile approach on how to analyse echocardiographic departments to ensure high-quality standards are met. In addition, a process is detailed for departments that are seeking to demonstrate to external bodies adherence to a robust QA process. Methods The EQF consists of four domains. These include assessment of Echo Quality (including study acquisition and report generation); Reproducibility & Consistency (including analysis of individual variability when compared to the group and focused clinical audit), Education & Training (for all providers and service users) and Customer & Staff Satisfaction (of both service users and patients/their carers). Examples of what could be done in each of these areas are presented. Furthermore, evidence of participation in each domain is categorised against a red, amber or green rating: with an amber or green rating signifying that a quantifiable level of engagement in that aspect of QA has been achieved. Conclusion The proposed EQF is a powerful tool that focuses the limited time available for departmental QA on areas of practice where a change in patient experience or outcome is most likely to occur.