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October 2018 Br J Cardiol 2018;25:150–1 doi: 10.5837/bjc.2018.027 Online First

Utility of MPS in AAA repair and prognostication of cardiovascular events and mortality

Mark G MacGregor, Neil Donald, Ayesha Rahim, Zara Kwan, Simon Wong, Hannah Sharp, Hannah Burkey, Mark Fellows, David Fluck, Pankaj Sharma, Vineet Prakash, Thang S Han

Abstract

Myocardial perfusion scintigraphy (MPS) is a non-invasive method that can be used to assess reversible left ventricular myocardial perfusion defect (<20% indicates limited and ≥20% indicates extensive ischaemia), and left ventricular ejection fraction (LVEF) at rest and at stress. Data on the utility of MPS used to stratify cardiac risk prior to abdominal aortic aneurysm (AAA) repairs are limited. We evaluated MPS as a stratification tool for patients scheduled for endovascular aneurysm repair (EVAR) or open repair, between 2013 and 2016 at Ashford and St Peter’s NHS Foundation Trust, and 4.9 years (median 2.8 years, interquartile range [IQR] 2.1–3.8) cardiovascular events (n=15, 17.9%) all-cause mortality (n=17, 22.6%). Of the 84 patients recruited (median age 75.7 years, IQR 69.4–79.6), 57 (67.9%) had limited and 27 (32.1%) extensive ischaemia, 62 (73.8%) underwent EVAR and 22 (26.2%) open repair. Compared with open repair patients, EVAR patients were older (median age 70.6 years vs. 76.4 years, p=0.015), had higher rates of extensive ischaemia (13.6% vs. 38.7%, p=0.025), and abnormal LVEF reserve (LVEF at stress minus LVEF at rest ≤0: 40.0% vs. 76.6%, p=0.011), while having lower rates of 30-day postoperative major adverse cardiac events (13.6% vs. 3.3%, p=0.040) but no difference for cardiovascular events (p=0.179) or 4.9 year all-cause mortality (22.7% vs. 22.6%, adjusted hazard ratio 0.80, 95% confidence interval [CI] 0.22 to 3.20, p=0.799). Our findings indicate that MPS provides valuable information for AAA repair procedure.

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October 2018 Br J Cardiol 2018;25:143–6 doi: 10.5837/bjc.2018.028 Online First

New-onset giant T-wave inversion with prolonged QT interval: shared by multiple pathologies

Debjit Chatterjee, Priya Philip, Kay Teck Ling

Abstract

This is a case series of 10 patients who presented with the same electrocardiogram (ECG) manifestation of new-onset giant T-wave inversion and QT prolongation over a period of 24 months in a district general hospital. This unique ECG manifestation has been described with several cardiac and non-cardiac conditions.

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October 2018 Br J Cardiol 2018;25:157–8 doi: 10.5837/bjc.2018.029 Online First

A case report of transient acute left ventricular dysfunction

Allam Harfoush

Abstract

Stunned myocardium is a rare, but serious, medical condition, and requires emergency intervention. Short periods of hypoperfusion may lead to a prolonged cardiac hypokinesia (hours to days), even though the perfusion is retained eventually. In other words, although the coronary circulation is retained, the hypokinesia remains. It might be considered as a case of prolonged post-ischaemic dysfunction.

In this case, a 60-year-old woman, visiting her siblings, presented with severe dyspnoea and cyanosis to the emergency department. Pulmonary oedema was diagnosed, and transthoracic echocardiography (TTE) showed general hypokinesia and reduced ejection fraction (15%), nevertheless, sequential TTE monitoring after the required medical intervention revealed a continuous improvement, with a 45% ejection fraction three days later and a specific anterior wall hypokinesia, solely.

In conclusion, rapid diagnosis and treatment are essential for stunned myocardium, as these could change the progress of the clinical condition.

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August 2018 Br J Cardiol 2018;25:102–6 doi: 10.5837/bjc.2018.023

CardioTweeters: an analysis of Twitter use by UK cardiologists

Sarah Hudson, Antony French

Abstract

Twitter is a web-based micro-blogging service in which messages called ‘Tweets’, which may include visual media, are shared with followers of the account. Benefits include continuing education, networking and personal branding. This article examines the current use of Twitter among UK-based cardiologists, and General Medical Council guidance on social media interaction.

UK cardiologists using Twitter were identified by reviewing the Twitter accounts followed by the British Cardiovascular Society using an analysis programme (Twitonomy). An iterative process of tracing accounts followed by UK cardiologists was then undertaken. The last 20 Tweets of the 10 UK cardiologists most followed by other cardiologists were then reviewed for content.

There were 301 UK cardiologists identified. The most common location was London, the sub-specialty intervention, and the majority were consultants. Most had tweeted within the past month, and over 100 times. Content analysis of Tweets revealed 64% were cardiology-related, and 80% related to cardiology/medicine/science.

In conclusion, Twitter has been adopted by a relatively small group of UK cardiologists, but evidence suggests that those who have find it useful. While professionalism and patient confidentiality remain valid concerns, Twitter should be promoted as a location-independent, time-efficient way to network, and keep pace with current research and practice.

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August 2018 Br J Cardiol 2018;25:86–7 doi: 10.5837/bjc.2018.024

Artificial intelligence in cardiology: applications, benefits and challenges

Panos Constantinides, David A Fitzmaurice

Abstract

The introduction of such digital technologies as robotic implants, home monitoring devices, wearable sensors and mobile apps in healthcare have produced significant amounts of data, which need to be interpreted and operationalised by physicians and healthcare systems across disparate fields.1 Most often, such technologies are implemented at the patient level, with patients becoming their own producers and consumers of personal data, something which leads to them demanding more personalised care.2

This digital transformation has led to a move away from a ‘top-down’ data management strategy, “which entailed either manual entry of data with its inherent limitations of accuracy and completeness, followed by data analysis with relatively basic statistical tools… and often without definitive answers to the clinical questions posited”.3 We are now in an era of a ‘bottom-up’ data management strategy that involves real-time data extraction from various sources (including apps, wearables, hospital systems, etc.), transformation of that data into a uniform format, and loading of the data into an analytical system for final analysis.3

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