[Impact on weight loss and body composition of a food education intervention associated with Liraglutide treatment to address obesity]. / Impacto en la pérdida de peso y la composición corporal de una intervención de educación alimentaria asociada al tratamiento con liraglutida para el abordaje de la obesidad.

Introduction: Introduction: clinical practice guidelines recommend considering pharmacological treatment of obesity only as a complement to lifestyle modification. Drugs alone are usually ineffective in the long term after discontinuation, so pharmacological weight loss strategies should always be accompanied by lifestyle modifications. Objective: to analyze the changes in weight, body mass index and body composition by means of electrical bioimpedance after a 32-week treatment with liraglutide in patients with obesity, associated or not with a food education program. Materials and methods: the study involved 68 patients who were randomly divided into 2 groups. One group received treatment with liraglutide 3.0 mg/day along with individual dietary education, and the other group was treated with liraglutide 3.0 mg/day and standard medical follow-up for 32 weeks. The data collected were weight (kg), height (m) (Seca® brand), body mass index (kg/m2) and body composition using multifrequency bioimpedance (SECA 112® brand). The variables were analyzed at the beginning and at the end of the treatment. Results: after 32 weeks of treatment, both study groups lost weight significantly. The group treated with liraglutide and individual dietary education had a reduction of 8.77 kg (9.08 %) (p < 0.001) and the group treated with liraglutide without education had a reduction of 3.55 kg (3.45 %) (p < 0.001). The BMI of the participants treated with liraglutide and education decreased by -4,04 kg/m2 (10.35 %) (p < 0.001) and in the group without education it decreased by -3.22 kg/m2 (8.30 %) (p = 0.003). In the educated group, fat mass decreased by -7.65 kg (15.89 %) (p < 0.001), although skeletal muscle mass also decreased by -1.62 kg (6.8 %) (p < 0.001). In those treated with liraglutide without education, a reduction in fat mass and skeletal muscle mass was also observed - fat mass by -4.72 kg (9.43 %) (p < 0.001) and skeletal muscle mass by -0.17 kg (0.70 %) (p < 0.001). Differences were also observed between groups, observing a greater reduction in weight, BMI, fat mass and skeletal muscle mass in the group with liraglutide and education compared to the group without education, although these differences were not statistically significant. Conclusions: dietary education associated with liraglutide treatment may contribute to increasing weight and fat mass losses. However, it was also associated with an unwanted loss of skeletal muscle mass, probably related to the greater intensity of weight loss, which will have to be reversed in future therapeutic approaches. Habit modification through multidisciplinary treatment, including nutritional education, combined strength and resistance exercise, and cognitive-behavioral therapy, could be an effective way to treat obesity and maintain weight, body composition, and adherence to a lifestyle.

Introducción: Introducción: las guías de práctica clínica recomiendan considerar el tratamiento farmacológico de la obesidad únicamente como complemento de la modificación del estilo de vida. Objetivo: analizar los cambios sobre el peso, el índice de masa corporal y la composición corporal mediante bioimpedancia eléctrica tras un tratamiento de 32 semanas con liraglutida en pacientes con obesidad, asociado o no a un programa de educación alimentaria. Materiales y métodos: participaron 68 pacientes que fueron divididos aleatoriamente en 2 grupos. Uno recibió tratamiento con liraglutida 3,0 mg/día junto con educación alimentaria individual y el otro fue tratado con liraglutida 3,0 mg/día y seguimiento médico estándar durante 32 semanas.Datos recogidos:l peso, talla, IMCl y composición corporal mediante bioimpedancia multifrecuencia. Se analizaron las variables al inicio y al final del tratamiento. Resultados: tras 32 semanas de tratamiento, los dos grupos de estudio redujeron el peso de manera significativa. El grupo tratado con liraglutida y educación alimentaria individual tuvo una reducción de 8,77 kg (9,08 %) (p < 0,001) y el grupo tratado con liraglutida sin educación tuvo una reducción de 3,55 kg (3,45 %) (p < 0,001). El IMC de los participantes tratados con liraglutida y educación disminuyó en -4,04 kg/m2 (10,35 %) (p < 0,001) y en el grupo sin educación se redujo en -3,22 kg/m2 (8,30 %) (p = 0,003). En el grupo con educación disminuyó la masa grasa en -7,65 kg (15,89 %) (p < 0,001), aunque también la masa muscular esquelética en -1,62 kg (6,8 %) (p < 0,001). En los tratados con liraglutida sin educación también se observó una reducción de la masa grasa y masa muscular esquelética: la masa grasa en -4,72 kg (9,43 %) (p < 0,001) y la masa muscular esquelética en -0,17 kg (0,70 %) (p < 0,001). También se observaron diferencias entre grupos, observándose mayor reducción del peso, del IMC, de lamasa grasa y de la masa muscular esquelética en el grupo con liraglutida y educación con respecto al grupo sin educación, aunque estas diferencias no llegaron a ser estadísticamente significativas. Conclusiones: la educación alimentaria asociada al tratamiento con liraglutida puede contribuir a incrementar la pérdida de peso y de la masa grasa. Sin embargo, llevó también asociada una pérdida no deseada de masa muscular esquelética, probablemente relacionada con la mayor intensidad de pérdida de peso, que habrá que revertir en futuras aproximaciones terapéuticas.

Estimating vertical ground reaction forces during gait from lower limb kinematics and vertical acceleration using wearable inertial sensors.

One of the most important forces generated during gait is the vertical ground reaction force (vGRF). This force can be measured using force plates, but these can limit the scope of gait analysis. This paper presents a method to estimate the vGRF using inertial measurement units (IMU) and machine learning techniques. Four wearable IMUs were used to obtain flexion/extension angles of the hip, knee, and ankle joints, and an IMU placed over the C7 vertebra to measure vertical acceleration. We trained and compared the performance of two machine learning algorithms: feedforward neural networks (FNN) and random forest (RF). We investigated the importance of the inputs introduced into the models and analyzed in detail the contribution of lower limb kinematics and vertical acceleration to model performance. The results suggest that the inclusion of vertical acceleration increases the root mean square error in the FNN, while the RF appears to decrease it. We also analyzed the ability of the models to construct the force signal, with particular emphasis on the magnitude and timing of the vGRF peaks. Using the proposed method, we concluded that FNN and RF models can estimate the vGRF with high accuracy.