ECG predictors of AF: A systematic review (predicting AF in ischaemic stroke-PrAFIS).

In 25% of patients presenting with embolic stroke, a cause is not determined. Atrial fibrillation (AF) is a commonly identified mechanism of stroke in this population, particularly in older patients. Conventional investigations are used to detect AF, but can we predict AF in this population and generally? We performed a systematic review to identify potential predictors of AF on 12-lead electrocardiogram (ECG). METHOD: We conducted a search of EMBASE and Medline databases for prospective and retrospective cohorts, meta-analyses or case-control studies of ECG abnormalities in sinus rhythm predicting subsequent atrial fibrillation. We assessed quality of studies based on the Newcastle-Ottawa scale and data were extracted according to PRISMA guidelines. RESULTS: We identified 44 studies based on our criteria. ECG patterns that predicted the risk of developing AF included interatrial block, P-wave terminal force lead V1, P-wave dispersion, abnormal P-wave-axis, abnormal P-wave amplitude, prolonged PR interval, left ventricular hypertrophy, QT prolongation, ST-T segment abnormalities and atrial premature beats. Furthermore, we identified that factors such as increased age, high CHADS-VASC, chronic renal disease further increase the positive-predictive value of some of these parameters. Several of these have been successfully incorporated into clinical scoring systems to predict AF. CONCLUSION: There are several ECG abnormalities that can predict AF both independently, and with improved predictive value when combined with clinical risk factors, and if incorporated into clinical risk scores. Improved and validated predictive models could streamline selection of patients for cardiac monitoring and initiation of oral anticoagulants.

Comparing McDonald's food marketing practices on official Instagram accounts across 15 countries.

BACKGROUND: Social media advertising by fast food companies continues to increase globally, and exposure to food advertising contributes to poor diet and negative health outcomes (eg, cardiovascular disease). McDonald's-the largest fast food company in the world-operates in 101 countries, but little is known about their marketing techniques in various regions. The objective of this study was to compare the social media advertising practices of McDonald's-the largest fast food company in the world-in 15 high-income, upper-middle-income and lower-middle-income countries. METHODS: We randomly selected official McDonald's Instagram accounts for 15 high-income, upper-middle-income and lower-middle-income countries. We captured all the screenshots that McDonald's posted on those Instagram accounts from September to December 2019. We quantified the number of followers, 'likes', 'comments' and video views associated with each account in April 2020. We used content analysis to examine differences in the marketing techniques. RESULTS: The 15 accounts collectively maintained 10 million followers and generated 3.9 million 'likes', 164 816 comments and 38.2 million video views. We identified 849 posts. The three lower-middle-income countries had more posts (n=324; M, SD=108.0, 38.2 posts) than the five upper-middle-income countries (n=227; M, SD=45.4, 37.5 posts) and seven high-income countries (n=298; M, SD=42.6, 28.2 posts). Approximately 12% of the posts in high-income countries included child-targeted themes compared with 22% in lower-middle-income countries. Fourteen per cent of the posts in high-income countries included price promotions and free giveaways compared with 40% in lower-middle-income countries. CONCLUSIONS: Social media advertising has enabled McDonald's to reach millions of consumers in lower-middle-income and upper-middle-income countries with disproportionately greater child-targeted ads and price promotions in lower-middle-income countries. Such reach is concerning because of the increased risk of diet-related illnesses, including cardiovascular disease, in these regions.