Atrial fibrillation is the most common heart-rhythm disorder, affecting about 1.5% to 2% of the population with an increased risk of mortality and morbidity due to stroke, thromboembolism, and heart failure. If the conversion back to sinus rhythm does not happen spontaneously, pharmacological or electrical cardioversion (ECV) is the next available treatment options for some patients. However, the long-term success following ECV is variable. This review describes the factors that are associated with maintenance of sinus rhythm following ECV and proposes a clinical strategy based on the available evidence.Atrial fibrillation (AF) is a supraventricular arrhythmia characterized by extremely rapid and uncoordinated electrical activity in the atria with variable conduction through the atrioventricular node, resulting in irregular, and often rapid, ventricular contraction. AF is the most common sustained heart-rhythm disorder in the developed world, found in 1% to 2% of the general population, with a higher prevalence in females and older patients.1 Because of an aging population, it is likely that AF patient numbers will continue to rise, along with associated increases in healthcare costs. 2 Palpitations, breathlessness, fatigue, and reduced exercise tolerance are AF-associated symptoms, and there is an increased risk of stroke with AF, with the need for anticoagulation. 2In some patients, AF will be permanent and therapy is aimed at controlling the ventricular rate (rate-control strategy). In other patients, normal rhythm initially can be restored with pharmacological or electrical cardioversion (ECV) but often requires additional strategies to maintain sinus rhythm (SR; rhythm-control strategy).There is no convincing mortality benefit to achieving rhythm control over rate control; therefore, treatment decisions are usually based on the presence of symptoms and the perceived likelihood of successful cardioversion. Cardioversion can be achieved by pharmacological methods or ECV; however, maintenance of SR may only be temporary. [3][4][5][6][7] The use of ECV may be indicated where pharmacological rhythm-control strategies have failed and the patient remains symptomatic. Patient selection is important, as the maintenance of longterm SR can be difficult. The advantages of ECV are that it is associated with a high initial success rate (68%-98%) 8 ; however, it requires sedation or general anesthesia, and although initially successful, longterm maintenance of SR is not reliably achieved. 9 AF relapse following ECV is also associated with increased mortality, 10 thus highlighting the importance of identifying the correct patient group for cardioversion and, where possible, addressing reversible factors associated with poorer outcomes. Furthermore, it is crucial at the time of ECV that patients are appropriately prepared with adequate hydration and correction of any electrolyte abnormalities. ECV should also be avoided in stable patients with concurrent infection or significant inflammation.Many factors have been reported ...

BackgroundComputerised electrocardiogram (ECG) interpretation diagnostic algorithms have been developed to guide clinical decisions like with ST segment elevation myocardial infarction (STEMI) where time in decision making is critical. These computer-generated diagnoses have been proven to strongly influence the final ECG diagnosis by the clinician; often called automation bias. However, the computerised diagnosis may be inaccurate and could result in a wrong or delayed treatment harm to the patient. We hypothesise that an algorithmic certainty index alongside a computer-generated diagnosis might mitigate automation bias.The impact of reporting a certainty index on the final diagnosis is not known. PurposeTo ascertain whether knowledge of the computer-generated ECG algorithmic certainty index influences operator diagnostic accuracy. MethodologyClinicians who regularly analyse ECGs such as cardiology or acute care doctors, cardiac nurses and ambulance staff were invited to complete an online anonymous survey between March and April 2019. The survey had 36 ECGs with a clinical vignette of a typical chest pain and which were either a STEMI, normal, or borderline (but do not fit the STEMI criteria) along with an artificially created certainty index that was either high, medium, low

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