Simulación de trayectorias y modelos de medición en plataformas multisensor

El objetivo de este trabajo es generar una trayectoria simulada en el entorno virtual de Matlab mediante B-splines cúbicos, para la obtención de este objetivo se han introducido conceptos de teoría y ejemplo de otras trayectorias más sencillas, los cuales nos van a ayudar al mejor entendimiento y comprensión de nuestra trayectoria generada. Cabe destacar que todas las trayectorias creadas en este trabajo van a ser generadas de manera aleatoria, es decir los puntos de paso de cada trayectoria van a ser elegidos aleatoriamente por nuestro programa de cálculo. La creación de esta trayectoria es debido a que se desea su implementación en un vehículo de movimiento en 3D. El hecho de querer implementar un vehículo de movimiento en 3D nos produce la necesidad del modelado de una serie de sensores, para que dicho vehículo sea capaz de percibir su entorno y su movimiento, en este trabajo se han simulado tres sensores: Sensor de velocidad, Sensor de aceleración y GPS. En definitiva se va a generar un vehículo simulado de movimiento 3D en el entorno virtual de Matlab, que realice una trayectoria acelerada y curvilínea y posea una serie de sensores

La Brigada de Tesla. Educación online y gamificación para el aprendizaje de la electricidad

La Brigada de Tesla es una página web creada para la enseñanza de la unidad didáctica de la electricidad en 3º de la ESO. Un proyecto en el que la gamificación, el uso de las TIC y las redes sociales están muy presentes, tres herramientas que se perfilan como indispensables para avanzar en materia de innovación educativa y motivar a los estudiantes. En este trabajo se expone el desarrollo y la aplicación del mismo en el aula y los resultados obtenidos en el alumnado, en los que se ha apreciado cómo la situación de excepción de este curso escolar -marcada por la suspensión de las clases y la promoción general- ha influido de manera notable en su rendimiento académico.<br /

Long-term effect of 2 intensive statin regimens on treatment and incidence of cardiovascular events in familial hypercholesterolemia: The SAFEHEART study

[Background] Maximal doses of potent statins are the basement of treatment of familial hypercholesterolemia (FH). Little is known about the use of different statin regimens in FH.[Objectives] The objectives of the study were to describe the treatment changes and low-density lipoprotein cholesterol (LDL-C) goal achievement with atorvastatin (ATV) and rosuvastatin (RV) in the SAFEHEART cohort, as well as to analyze the incidence of atherosclerotic cardiovascular events (ACVEs) and changes in the cardiovascular risk.[Methods] SAFEHEART is a prospective follow-up nationwide cohort study in a molecularly defined FH population. The patients were contacted on a yearly basis to obtain relevant changes in life habits, medication, and ACVEs.[Results] A total of 1939 patients were analyzed. Median follow-up was 6.6 years (5–10). The estimated 10-year risk according the SAFEHEART risk equation was 1.61 (0.67–3.39) and 1.22 (0.54–2.93) at enrollment for ATV and RV, respectively (P < .001). There were no significant differences at the follow-up: 1.29 (0.54–2.82) and 1.22 (0.54–2.76) in the ATV and RV groups, respectively (P = .51). Sixteen percent of patients in primary prevention with ATV and 18% with RV achieved an LDL-C <100 mg/dL and 4% in secondary prevention with ATV and 5% with RV achieved an LDL-C <70 mg/dL. The use of ezetimibe was marginally greater in the RV group. One hundred sixty ACVEs occurred during follow-up, being its incidence rate 1.1 events/100 patient-years in the ATV group and 1.2 in the RV group (P = .58).[Conclusion] ATV and RV are 2 high-potency statins widely used in FH. Although the reduction in LDL-C levels was greater with RV than with ATV, the superiority of RV for reducing ACVEs was not demonstrated.This study was supported by Fundación Hipercolesterolemia Familiar; Grant G03/181 and FIS PI12/01289 from Instituto de Salud Carlos III (ISCIII), Grant 08-2008 Centro Nacional de Investigación Cardiovascular (CNIC)

Predicting Cardiovascular Events in Familial Hypercholesterolemia: The SAFEHEART Registry (Spanish Familial Hypercholesterolemia Cohort Study).

Although risk factors for atherosclerotic cardiovascular disease (ASCVD) in familial hypercholesterolemia (FH) have been described, models for predicting incident ASCVD have not been reported. Our aim was to use the SAFEHEART registry (Spanish Familial Hypercholesterolemia Cohort Study) to define key risk factors for predicting incident ASCVD in patients with FH. SAFEHEART is a multicenter, nationwide, long-term prospective cohort study of a molecularly defined population with FH with or without previous ASCVD. Analyses to define risk factors and to build a risk prediction equation were developed, and the risk prediction equation was tested for its ability to discriminate patients who experience incident ASCVD from those who did not over time. We recruited 2404 adult patients with FH who were followed up for a mean of 5.5 years (SD, 3.2 years), during which 12 (0.5%) and 122 (5.1%) suffered fatal and nonfatal incident ASCVD, respectively. Age, male sex, history of previous ASCVD, high blood pressure, increased body mass index, active smoking, and low-density lipoprotein cholesterol and lipoprotein(a) levels were independent predictors of incident ASCVD from which a risk equation with a Harrell C index of 0.85 was derived. The bootstrap resampling (100 randomized samples) of the original set for internal validation showed a degree of overoptimism of 0.003. Individual risk was estimated for each person without an established diagnosis of ASCVD before enrollment in the registry by use of the SAFEHEART risk equation, the modified Framingham risk equation, and the American College of Cardiology/American Heart Association ASCVD Pooled Cohort Risk Equations. The Harrell C index for these models was 0.81, 0.78, and 0.8, respectively, and differences between the SAFEHEART risk equation and the other 2 were significant (P=0.023 and P=0.045). The risk of incident ASCVD may be estimated in patients with FH with simple clinical predictors. This finding may improve risk stratification and could be used to guide therapy in patients with FH. URL: http://clinicaltrials.gov. Unique identifier: NCT02693548

The Added Value of Coronary Calcium Score in Predicting Cardiovascular Events in Familial Hypercholesterolemia

International audienceObjectivesThis study aimed at investigating the additional contribution of coronary artery calcium (CAC) score to SAFEHEART (Spanish Familial Hypercholesterolemia Cohort Study) risk equation (SAFEHEART-RE) for cardiovascular risk prediction in heterozygous familial hypercholesterolemia (HeFH).BackgroundCommon cardiovascular risk equations are imprecise for HeFH. Because of the high phenotype variability of HeFH, CAC score could help to better stratify the risk of atherosclerotic cardiovascular disease (ASCVD).MethodsREFERCHOL (French Registry of Familial Hypercholesterolemia) and SAFEHEART are 2 ongoing national registries on HeFH. We analyzed data from primary prevention HeFH patients undergoing CAC quantification. We used probability-weighted Cox proportional hazards models to estimate HRs. Area under the receiver-operating characteristic curve (AUC) and net reclassification improvement (NRI) were used to compare the incremental contribution of CAC score when added to the SAFEHEART-RE for ASCVD prediction. ASCVD was defined as coronary heart disease, stroke or transient ischemic attack, peripheral artery disease, resuscitated sudden death, and cardiovascular death.ResultsWe included 1,624 patients (mean age: 48.5 ± 12.8 years; men: 45.7%) from both registries. After a median follow-up of 2.7 years (interquartile range: 0.4-5.0 years), ASCVD occurred in 81 subjects. The presence of a CAC score of >100 was associated with an HR of 32.05 (95% CI: 10.08-101.94) of developing ASCVD as compared to a CAC score of 0. Receiving-operating curve analysis showed a good performance of CAC score alone in ASCVD prediction (AUC: 0.860 [95% CI: 0.853-0.869]). The addition of log(CAC + 1) to SAFEHEART-RE resulted in a significantly improved prediction of ASCVD (AUC: 0.884 [95% CI: 0.871-0.894] for SAFEHEART-RE + log(CAC + 1) vs AUC: 0.793 [95% CI: 0.779-0.818] for SAFEHEART-RE; P < 0.001). These results were confirmed also when considering only hard cardiovascular endpoints. The addition of CAC score was associated with an estimated overall net reclassification improvement of 45.4%.ConclusionsCAC score proved its use in improving cardiovascular risk stratification and ASCVD prediction in statin-treated HeFH

Patient-Level, Institutional, and Temporal Variations in Use of Imaging Modalities to Confirm Pulmonary Embolism

International audienceBackground: The choice of the imaging modality for diagnosis of pulmonary embolism (PE) could be influenced by provider, patient or hospital characteristics, or over time. However, little is known about the choice of the diagnostic modalities in practice. The aim of this study was to evaluate the variations in the use of imaging modalities for patients with acute PE. Methods: Using the data from Registro Informatizado Enfermedad TromboEmbolica (RIETE), a prospective international registry of patients with venous thromboembolism (March 2001–January 2019), we explored the imaging modalities used in patients with acute PE. The imaging modalities included computed tomography pulmonary angiography, ventilation/perfusion scanning, pulmonary angiography, a combination of these tests, or PE signs and symptoms plus imaging-confirmed proximal deep vein thrombosis but no chest imaging. Results: Among 38 025 patients with confirmed PE (53.1% female, age: 67.3±17 years), computed tomography pulmonary angiography was the dominant modality of diagnosis in all RIETE enrollees (78.2% [99% CI, 77.6–78.7]); including pregnant patients (58.9% [99% CI, 47.7%–69.4%]) and patients with severe renal insufficiency (62.5% [99% CI, 59.9–65.0]). A greater proportion of patients underwent ventilation/perfusion scanning in larger hospitals compared with smaller hospitals (13.1% versus 7.3%, P <0.001). The use of computed tomography pulmonary angiography varied between 13.3% and 98.3% across the countries, and its use increased over time (46.5% in 2002 to 91.7% in 2018, P <0.001). Conclusions: In a large multinational PE registry, variations were observed in the use of imaging modalities according to patient or institutional factors and over time. However, computed tomography pulmonary angiography was the dominant modality of diagnosis, even in pregnancy and severe renal insufficiency. The safety, costs, and downstream effects of these tests on PE-related and non-PE-related outcomes warrant further investigation