ABC | Volume 110, Nº1, January 2018

Original Article Stephan et al Mobile health and atrial fibrillation Arq Bras Cardiol. 2018; 110(1):7-15 Table 1 – Socioeconomic characteristics of the population and time in anticoagulation therapy Characteristics Age (years) 67.7 ± 9.4 Male sex (%) 60 White (%) 83.3 Who patients live with Alone (%) 16.7 Companion (%) 26.7 Family (%) 53.3 Institutionalized (%) 3.3 Schooling years 0-4 years (%) 33.3 5-8 years (%) 40 > 8 years (%) 26.7 Family income 4-10 minimum wages (%) 26.7 2-4 minimum wages (%) 20 < 2 minimum wages (%) 53.3 Time in anticoagulation therapy < 1 month (%) 13.3 1 – 11 months (%) 13.3 1-5 years (%) 33.3 > 5 years (%) 33.4 Not in current use 3.3 the application, from 4.7 (± 1.8) to 7.2 (± 1.0), p < 0.001. Figure 2 depicts the mean number of correct answers before and after the interaction. DCSH administered to the patients after selecting the therapy with the aid of the app resulted in an average of 11 ± 16/100 points. Regarding risk perception, before interacting with the app, 20% of patients had an appropriate perception of their risk of stroke, and 75% believed to have a risk lower than the real risk. After the interaction, adequate perception increased to 30%, with a non-significant p-value (0.608). With respect to the risk of bleeding, before using the app, 45% of patients had a correct perception and 35% believed they had a higher risk than the real one. After using the app, there was a non-significant increase (0.218) in the adequate perception for 60% of patients. Figure 3 depicts variations in risk perception. Discussion The development of mHealth apps for specific populations and health problems is viable and should be stimulated. This study with low income and low educational level patients demonstrated increased knowledge about AF and anticoagulation after the use of the app, enabling a shared decision-making about anticoagulation, with low decisional conflict. However, the perception of stroke and bleeding risk was not affected by the application use. Thromboembolic prophylaxis in AF is a global problem. It is generally underused, of difficult management and known to be prone to poor adherence. 23 One of the proposed strategies to optimize the use of OAC is the shared decision-making, which is currently recommended in the guidelines as part of an integrated management of the disease, and a clinical performance indicator. 8,24 Patients’ understanding of the therapy and their individual risk-benefit analysis is crucial in this process. 25 Nevertheless, there are significant gaps in this knowledge, even in patients treated for years. 18 Table 2 – Prevalence of the variables present in the CHA 2 DS 2 -VASc, HAS-BLED and SAMe-TT2R2 scores and average scores Systemic arterial hypertension (%) 80 Systolic blood pressure > 160 mmHg (%) 10 Diabetes Mellitus (%) 30 Congestive heart failure and ejection fraction < 40% (%) 30 Cardiovascular disease (%) 23.3 Stroke or transient ischemic accident (%) 16.7 Liver disease* (%) 0 Kidney disease † (%) 6.7 Pulmonary disease (%) 16.7 Labile or difficult-to-control INR ‡ (%) 23.3 History of or predisposition to major bleeding (%) 16.7 Use of antiplatelet or anti-inflammatory agents (%) 26.7 Use of medications that interact with coumarins (%) 43.3 Abusive use of alcohol (%) 3.3 Smoking (%) 10 CHA 2 DS 2 -VASc ≥ 2 § (%) 86.6 CHA 2 DS 2 -VASc per score (%) 0 3.3 1 10 2 23.4 3 23.4 4 20 5 13.3 7 3.3 8 3.3 Mean CHA 2 DS 2 -VASc 3 ± 1.8 Mean HAS-BLED 2 ± 1.2 SAMe-TT2R2 ≥ 2 // (%) 76.6 *Chronic liverdisease(e.g.:cirrhosis),orbiochemicalevidenceofsignificant liver dysfunction (bilirubin > 2 - 3 times the upper level, transaminase or alkaline phosphatase > 3 times the upper level); † Chronic hemodialysis, kidney transplant, serum creatinine > 2.2 mg/dl; ‡ in the target range < 60% of times; § A score ≥ 2 indicates the necessity of anticoagulation; // A score ≥ indicates patients who require additional interventions to achieve an acceptable anticoagulation control with coumarins. 10