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      Consumer wearable devices for evaluation of heart rate control using digoxin versus beta-blockers: the RATE-AF randomized trial

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          Abstract

          Consumer-grade wearable technology has the potential to support clinical research and patient management. Here, we report results from the RATE-AF trial wearables study, which was designed to compare heart rate in older, multimorbid patients with permanent atrial fibrillation and heart failure who were randomized to treatment with either digoxin or beta-blockers. Heart rate ( n = 143,379,796) and physical activity ( n = 23,704,307) intervals were obtained from 53 participants (mean age 75.6 years (s.d. 8.4), 40% women) using a wrist-worn wearable linked to a smartphone for 20 weeks. Heart rates in participants treated with digoxin versus beta-blockers were not significantly different (regression coefficient 1.22 (95% confidence interval (CI) −2.82 to 5.27; P = 0.55); adjusted 0.66 (95% CI −3.45 to 4.77; P = 0.75)). No difference in heart rate was observed between the two groups of patients after accounting for physical activity ( P = 0.74) or patients with high activity levels (≥30,000 steps per week; P = 0.97). Using a convolutional neural network designed to account for missing data, we found that wearable device data could predict New York Heart Association functional class 5 months after baseline assessment similarly to standard clinical measures of electrocardiographic heart rate and 6-minute walk test (F1 score 0.56 (95% CI 0.41 to 0.70) versus 0.55 (95% CI 0.41 to 0.68); P = 0.88 for comparison). The results of this study indicate that digoxin and beta-blockers have equivalent effects on heart rate in atrial fibrillation at rest and on exertion, and suggest that dynamic monitoring of individuals with arrhythmia using wearable technology could be an alternative to in-person assessment. ClinicalTrials.gov identifier: NCT02391337.

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          Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation

          Optical sensors on wearable devices can detect irregular pulses. The ability of a smartwatch application (app) to identify atrial fibrillation during typical use is unknown.
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            A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis

            Deep learning offers considerable promise for medical diagnostics. We aimed to evaluate the diagnostic accuracy of deep learning algorithms versus health-care professionals in classifying diseases using medical imaging.
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              Isosorbide Mononitrate in Heart Failure with Preserved Ejection Fraction.

              Nitrates are commonly prescribed to enhance activity tolerance in patients with heart failure and a preserved ejection fraction. We compared the effect of isosorbide mononitrate or placebo on daily activity in such patients.
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                Journal
                Nature Medicine
                Nat Med
                Springer Science and Business Media LLC
                1078-8956
                1546-170X
                July 15 2024
                Article
                10.1038/s41591-024-03094-4
                67dfb1b1-e97a-4fb8-ad85-8d7f8048eda6
                © 2024

                https://creativecommons.org/licenses/by/4.0

                https://creativecommons.org/licenses/by/4.0

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