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The Acetazolamide in Decompensated Heart Failure with Volume Overload (ADVOR) trial showed that the addition of acetazolamide to loop diuretic therapy in patients with acute decompensated heart failure (ADHF) in a greater incidence of successful decongestion. 1,2 Description The goal of the trial was to evaluate whether acetazolamide, a carbonic anhydrase inhibitor that reduces proximal tubular sodium reabsorp-tion, can improve the efficiency of loop diuretics, potentially leading to more and faster decongestion in patients with ADHF with volume overload. 3 Study design • Randomization • Parallel • Double-blind • Placebo-controlled • Multicentre (nationwide) • Outcome based on a congestion score (evaluated by a single observer) Patients with ADHF, clinical signs of volume overload (i.e. oedema, pleural effusion, or ascites), and an N-terminal pro-B-type natriuret-ic peptide (NT-proBNP) level of more than 1000 pg per milliliter or a B-type natriuretic peptide (BNP) level of more than 250 pg per milliliter were randomized to receive either intravenous acetazola-mide (500 mg once daily) (n = 259) or placebo (n = 260) added to standardized intravenous loop diuretics (at a dose equivalent to twice the oral maintenance dose). 3 Randomization was stratified according to the left ventricular ejection fraction (≤40% or >40%) and trial site. At randomization, oral loop diuretics were stopped, and the patient received an intravenous loop diuretic at double the oral maintenance dose, administered as a single bolus immediately after randomization and split into two doses (separated by ≥6 h) on each of the next 2 days. The bolus of acetazolamide or matching placebo was administered simultaneously with the first dose of loop diuretics each day. All patients received the same maintenance infusion with 500 mL dextrose 5% and 3 g MgSO4 administered over 24 h until the end of the study treatment phase. Daily oral intake of fluids and sodium was restricted to 1500 mL and 1.5 g, respectively. Patient population • Total number of trial participants: 519 subjects • Duration of follow-up: 3 months • Mean patient age: 78 years • Percentage female: 37% Other salient features/ characteristics • Left ventricular ejection fraction ≤40%: 43% • Median congestion score at baseline [interquartile range (IQR)]: 4 (3-6) • Median NT-proBNP level (IQR): 6173 (3068-10 896) pg per millilitre • Median home maintenance dose of furosemide equivalent (IQR): 60 (40-100) mg Inclusion criteria Patients with an elective or emergency hospital admission and clinical diagnosis of acute heart failure were eligible for the trial if: • ≥1 clinical sign of volume overload (i.e. oedema, ascites confirmed by abdominal ultrasound, or pleural effusion confirmed by a chest X-ray or chest ultrasound). • Maintenance therapy with oral loop diuretics at a dose of ≥1 mg bumetanide or≥40 mg furosemide or≥20 mg torsemide for ≥1 month. • Plasma NT-proBNP level > 1000 pg/mL or BNP level > 250 ng/mL at screening. None declared.

Risk assessment and risk prediction have become essential in the prevention of cardiovascular disease. Even though risk prediction tools are recommended in the European guidelines, they are not adequately implemented in clinical practice. Risk prediction tools are meant to estimate prognosis in an unbiased and reliable way and to provide objective information on outcome probabilities. They support informed treatment decisions about the initiation or adjustment of preventive medication. Risk prediction tools facilitate risk communication to the patient and their family, and this may increase commitment and motivation to improve their health. Over the years many risk algorithms have been developed to predict 10-year cardiovascular mortality or lifetime risk in different populations, such as in healthy individuals, patients with established cardiovascular disease and patients with diabetes mellitus. Each risk algorithm has its own limitations, so different algorithms should be used in different patient populations. Risk algorithms are made available for use in clinical practice by means of - usually interactive and online available - tools. To help the clinician to choose the right tool for the right patient, a summary of available tools is provided. When choosing a tool, physicians should consider medical history, geographical region, clinical guidelines and additional risk measures among other things. Currently, the website is the only risk prediction tool providing prediction algorithms for all patient categories, and its implementation in clinical practice is suggested/advised by the European Association of Preventive Cardiology. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: this paper was produced within the framework of the ESC Prevention of Cardiovascular Disease Programme which is led by the European Association of Preventive Cardiology (EAPC) in collaboration with the Acute Cardiovascular Care Association (ACCA) and the Association of Cardiovascular Nursing and Allied Professions (ACNAP). The ESC Prevention of Cardiovascular Disease Programme is supported by unrestricted educational grants. The authors received no financial support for the research, authorship, and/or publication of this article. Rossello, X (corresponding author), Ctr Nacl Invest Cardiovasc CNIC Carlos III, Melchor Fernandez Almagro 3, Madrid 28029, Spain. fjrossello@cnic.es