e-ciudadanos, e-salud y redes sociales. Organizarse y formarse en alimentación y salud = e-citizens, e-health and social networks. How to organize and learn about food and health

Resumen: Con un simple clic, tenemos a nuestro alcance todo tipo de información. Un 30% de las visitas a las redes son búsquedas sobre salud. Aunque es prometedor el potencial de las nuevas tecnologías para ser utilizadas como fuente de mejora de la salud pública, de momento el uso que se le está dando es incierto.La información sobre salud en internet está fragmentada, faltan páginas web institucionales propias del SNS, acudiendo los ciudadanos a fuentes muy diversas, lo que favorece que pueda circular información no contrastada y que se mezcle información con publicidad. El e-paciente busca información contrastada sobre su enfermedad, comparte experiencias con otros pacientes y en ocasiones puede tener dificultad para identificar qué respuesta tiene suficiente garantía. Las aplicaciones móviles y los videojuegos han mostrado que pueden ser utilizadas de forma eficaz en mejorar los conocimientos sobre nutrición, mejorar hábitos cardiosaludables y conseguir adherencia a las pautas de ejercicio y alimentación en el hipertenso y dislipémico, entre otras. La utilización de aplicaciones o herramientas tecnológicas para mejorar la prevención o el tratamiento del e-paciente debe ser una de nuestras opciones terapéuticas, pero más estudios deben realizarse para poder llegar a conocer su utilidad real. Palabras clave: e-salud, e-pacientes, nutrición, e-health, prevención. Abstract: With just a click, we have any kind of information within reach. A 30% of internet visits are health searches. Although the potential new technologies have as a source to improve public health is promising, its application is uncertain at the moment.Information about health on the internet is fragmented, there is a lack of institutional websites of the National Health System (SNS), making the population to turn to various sources, which may enable the dissemination of non-contrasted information and, advertising may be mixed with information. The e-patient seeks contrasted information about his disease, shares experiences with other patients and may occasionally have difficulties identifying which answers offer enough guarantees. Mobile apps and videogames have shown they can be efficiently used improving knowledge about nutrition, heart-healthy habits and acquiring adherence in exercise and diet guidelines in hypertensive, dyslipidaemic subjects, among others. The use of apps or technological tools to improve the prevention or treatment of the e-patient must be one of our therapeutic options, but more studies must be conducted to know their real utility. Keywords: e-health, e-patients, nutrition, prevention doi: http://dx.doi.org/10.20318/recs.2016.313

The effect of post-discharge educational intervention on patients in achieving objectives in modifiable risk factors six months after discharge following an episode of acute coronary syndrome, (CAM-2 Project): a randomized controlled trial

<p>Abstract</p> <p>Objectives</p> <p>We investigated whether an intervention mainly consisting of a signed agreement between patient and physician on the objectives to be reached, improves reaching these secondary prevention objectives in modifiable cardiovascular risk factors six-months after discharge following an acute coronary syndrome.</p> <p>Background</p> <p>There is room to improve mid-term adherence to clinical guidelines' recommendations in coronary heart disease secondary prevention, specially non-pharmacological ones, often neglected.</p> <p>Methods</p> <p>In CAM-2, patients discharged after an acute coronary syndrome were randomly assigned to the intervention or the usual care group. The primary outcome was reaching therapeutic objectives in various secondary prevention variables: smoking, obesity, blood lipids, blood pressure control, exercise and taking of medication.</p> <p>Results</p> <p>1757 patients were recruited in 64 hospitals and 1510 (762 in the intervention and 748 in the control group) attended the six-months follow-up visit. After adjustment for potentially important variables, there were, between the intervention and control group, differences in the mean reduction of body mass index (0.5 vs. 0.2; p < 0.001) and waist circumference (1.6 cm vs. 0.6 cm; p = 0.05), proportion of patients who exercise regularly and those with total cholesterol below 175 mg/dl (64.7% vs. 56.5%; p = 0.001). The reported intake of medications was high in both groups for all the drugs considered with no differences except for statins (98.1% vs. 95.9%; p = 0.029).</p> <p>Conclusions</p> <p>At least in the short term, lifestyle changes among coronary heart disease patients are achievable by intensifying the responsibility of the patient himself by means of a simple and feasible intervention.</p

Factors related to early readmissions after acute heart failure: a nested case–control study

Abstract Aims To describe the main characteristics of patients who were readmitted to hospital within 1 month after an index episode for acute decompensated heart failure (ADHF). Methods and results This is a nested case–control study in the ReIC cohort, cases being consecutive patients readmitted after hospitalization for an episode of ADHF and matched controls selected from those who were not readmitted. We collected clinical data and also patient-reported outcome measures, including dyspnea, Minnesota Living with Heart Failure Questionnaire (MLHFQ), Tilburg Frailty Indicator (TFI) and Hospital Anxiety and Depression Scale scores, as well as symptoms during a transition period of 1 month after discharge. We created a multivariable conditional logistic regression model. Despite cases consulted more than controls, there were no statistically significant differences in changes in treatment during this first month. Patients with chronic decompensated heart failure were 2.25 [1.25, 4.05] more likely to be readmitted than de novo patients. Previous diagnosis of arrhythmia and time since diagnosis ≥ 3 years, worsening in dyspnea, and changes in MLWHF and TFI scores were significant in the final model. Conclusion We present a model with explanatory variables for readmission in the short term for ADHF. Our study shows that in addition to variables classically related to readmission, there are others related to the presence of residual congestion, quality of life and frailty that are determining factors for readmission for heart failure in the first month after discharge. Trial Registration: ClinicalTrials.gov Identifier: NCT03300791. First registration: 03/10/2017