In a rapid response published online by the British Medical Journal, Sommerstein and Gräni¹ pushed forward the hypothesis that angiotensin-converting enzyme (ACE) inhibitors (ACE-Is) could act as a potential risk factor for fatal Corona virus disease 2019 (COVID-19) by up-regulating ACE2. This notion was quickly picked up by the lay press and sparked concerns among physicians and patients regarding the intake of inhibitors of the renin–angiotensin–aldosterone system (RAAS) by severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) infected individuals.¹ In this article, we try to shed light on what is known and unknown regarding the RAAS and SARS-CoV2 interaction. We find translational evidence for diverse roles of the RAAS, which allows to formulate also the opposite hypothesis, i.e. that inhibition of the RAAS might be protective in COVID-19.

BACKGROUND: Alcohol use disorder has a detrimental impact on global health and new treatment targets are needed. Preclinical studies show attenuating effects of glucagon-like peptide-1 (GLP-1) agonists on addiction-related behaviors in rodents and nonhuman primates. Some trials have shown an effect of GLP-1 agonism on reward processes in humans; however, results from clinical studies remain inconclusive. METHODS: This is a predefined secondary analysis of a double-blind, randomized, placebo-controlled trial evaluating the GLP-1 agonist dulaglutide as a therapy for smoking cessation. The main objective was to assess differences in alcohol consumption after 12 weeks of treatment with dulaglutide compared to placebo. The effect of dulaglutide on alcohol consumption was analyzed using a multivariable generalized linear model. RESULTS: In the primary analysis, participants out of the cohort ( n = 255) who reported drinking alcohol at baseline and who completed 12 weeks of treatment ( n = 151; placebo n = 75, dulaglutide n = 76) were included. The median age was 42 (IQR 33–53) with 61% ( n = 92) females. At week 12, participants receiving dulaglutide drank 29% less (relative effect = 0.71, 95% CI 0.52–0.97, P = 0.04) than participants receiving placebo. Changes in alcohol consumption were not correlated with smoking status at week 12. CONCLUSION: These results provide evidence that dulaglutide reduces alcohol intake in humans and contribute to the growing body of literature promoting the use of GLP-1 agonists in treatment of substance use disorders. TRIAL REGISTRATION: ClinicalTrials.gov NCT03204396. FUNDING: Swiss National Foundation, Gottfried Julia Bangerter-Rhyner Foundation, Goldschmidt-Jacobson Foundation, Hemmi Foundation, University of Basel, University Hospital Basel, Swiss Academy of Medical Science.

The purpose of this study was to evaluate prevalence, progression, treatment, and outcome of silent coronary artery disease (CAD) in asymptomatic patients with diabetes (DM) at high coronary risk. Despite the close association of diabetes and CAD, general CAD screening in asymptomatic patients with DM is discouraged even though outcome data in patients at high coronary risk are lacking. Prospective multicenter outcome study-with a pilot randomized treatment substudy. The study comprised 400 asymptomatic patients with DM (type 2) without history or symptoms of CAD at high CAD risk. They underwent clinical evaluation and myocardial perfusion single-photon emission computed tomography (MPS) at baseline and after 2 years. Patients with normal MPS received usual care; those with abnormal MPS received medical or combined invasive and medical management. An abnormal MPS was found in 87 of 400 patients (22%). In patients with normal MPS, MACE occurred in 2.9% and ischemia or new scar in 3.2%. Patients with abnormal MPS had more MACE (9.8%; hazard ratio: 3.44; 95% confidence interval [CI]: 1.32 to 8.95; p = 0.011) and ischemia or new scar (34.2%; odds ratio: 15.91; 95% CI: 7.24 to 38.03; p < 0.001) despite therapy, resulting in "overt or silent CAD progression" of 35.6% versus 4.6% (odds ratio: 11.53; 95% CI: 5.63 to 24.70; p < 0.001). Patients with abnormal MPS randomized to medical versus invasive-medical strategies had similar event rates (p = 0.215), but more ischemic or new scar findings (54.3% vs. 15.8%; p < 0.001). High-risk asymptomatic patients with DM and normal MPS (78%) have a low rate of first manifestations of CAD. Patients with abnormal MPS at baseline (22%) have a 7-fold higher rate of progression to "overt or silent CAD," despite therapy. Randomized patients' outcomes suggest that a combined invasive and medical strategy for silent CAD may reduce scintigraphic but not symptomatic CAD progression versus medical therapy alone. (Trial of Invasive versus Medical therapy of Early coronary artery disease in Diabetes Mellitus ISRCTN87953632).

Atrial fibrillation (AF) is the most common arrhythmia encountered in clinical practice, and its paroxysmal nature makes its detection challenging. In this trial, we evaluated a novel App for its accuracy to differentiate between patients in AF and patients in sinus rhythm (SR) using the plethysmographic sensor of an iPhone 4S and the integrated LED only. For signal acquisition, we used an iPhone 4S, positioned with the camera lens and LED light on the index fingertip. A 5 min video file was recorded with the pulse wave extracted from the green light spectrum of the signal. RR intervals were automatically identified. For discrimination between AF and SR, we tested three different statistical methods. Normalized root mean square of successive difference of RR intervals (nRMSSD), Shannon entropy (ShE), and SD1/SD2 index extracted from a Poincaré plot. Eighty patients were included in the study (40 patients in AF and 40 patients in SR at the time of examination). For discrimination between AF and SR, ShE yielded the highest sensitivity and specificity with 85 and 95%, respectively. Applying a tachogram filter resulted in an improved sensitivity of 87.5%, when combining ShE and nRMSSD, while specificity remained stable at 95%. A combination of SD1/SD2 index and nRMSSD led to further improvement and resulted in a sensitivity and specificity of 95%. The algorithm tested reliably discriminated between SR and AF based on pulse wave signals from a smartphone camera only. Implementation of this algorithm into a smartwatch is the next logical step.