Monitorización flash en pacientes con diabetes mellitus tipo 1: adherencia, complicaciones y parámetros clínicos / Flash monitoring in patients with type 1 diabetes mellitus: treatment adherence, complications and clinical parameters

Objetivos: describir el perfil sociodemográfico y clínico de las personas con diabetes mellitus tipo 1 (DM1), así como el uso del dispositivo de monitorización flash Freestyle Libre (FL) en quienes se lo habían costeado por cuenta propia, y analizar las diferencias (parámetros analíticos, complicaciones de la enfermedad y adherencia al tratamiento) frente a pacientes con DM1 que utilizaban los controles glucémicos tradicionales mediante punción capilar.Método: estudio descriptivo transversal en 206 pacientes con DM1 de un área de salud en la región de Castilla-La Mancha. Variables de estudio: tener dispositivo FL por cuenta propia, variables sociodemográficas y clínicas (incluyendo parámetros analíticos) y el cuestionario validado Self Care Inventory Revised (SCI-R). Se realizaron análisis univariante y bivariante, así como un análisis multivariante de regresión logística (variable dependiente: tener el dispositivo FL por cuenta propia).Resultados: el análisis multivariante mostró que no tener el dispositivo FL era más probable en quienes tenían estudios primarios/sin estudios (OR 4,86 (IC95%: 1,03-22,88); Referencia (Ref): estudios secundarios/universitarios), dislipemia (OR 3,18 (IC95% 1,39-7,26); Ref: no dislipemia), 6 o más hipoglucemias/semana (OR 3,21 (IC95%: 1,44-7,16); Ref: menos de 6) y 4 o más punciones/día (OR: 17,56 (IC95%: 6,09-50,64); Ref: menos de 4). Tanto le media de glucosa basal como la HBA1c eran más bajas (p< 0,001) en quienes tenían el dispositivo, así como mejores puntuaciones en el SCI-R (p< 0,001).Conclusión: el uso de los dispositivos de control glucémico permite un mejor manejo de las complicaciones de la DM1: menor número de hiper e hipoglucemias, punciones y mejor adherencia al tratamiento.(AU)

Objectives: to describe the sociodemographic and clinical profile of persons with Type 1 Diabetes Mellitus (T1D), as well as the use of the FreeStyle Libre (FL) flash monitoring device in those who had paid for it out of their own pocket, and to analyse the differences (lab test parameters, disease complications and treatment adherence) vs. T1D patients using traditional glycemic monitoring through finger prick.Method: a descriptive cross-sectional study in 206 patients with T1D from a health area in the Castilla-La Mancha region. Study variables: to have a FL device purchased out of pocket, sociodemographic and clinical variables (including lab test parameters) and the validated Self Care Inventory Revised (SCI-R) questionnaire. Univariate and bivariate analyses were conducted, as well as multivariate logistical regression analysis (dependent variable: to have purchased the FL out of pocket).Results: the multivariate analysis showed that not having the FL device was more likely among those with primary education / no education (OR 4.86 (CI95%: 1.03-22.88); Reference (Ref): secondary / university education, dyslipidemias (OR 3.18 (CI95% 1.39-7.26); Ref: no dyslipidemia, 6 or more hypoglycaemias/ week (OR 3.21 (CI95%: 1.44-7.16); Ref: less than 4, or more finger pricks/day (OR: 17.56 (CI95%: 6.09-50.64); Ref: less than 4. Both the mean baseline glucose and the HBA1c were lower (p< 0.001) among those who had the device, who also had better scores in the SCI-R questionnaire (p< 0.001).Conclusion: the use of the glycemic control devices allows better management of TDI complications: a lower number of hyper and hypoglycaemias and finger pricks, and better treatment adherence.(AU)

Longitudinal study of the flash glucose monitoring system in type 1 diabetics: An mHealth ally in times of COVID-19.

AIMS AND OBJECTIVES: The aim of this study was to assess the effect of the FreeStyle Libre device implantation in adult type 1 diabetics in a Health Area of Castilla La Mancha (Spain) during the COVID-19 pandemic. BACKGROUND: FreeStyle Libre is a so-called mHealth device that supports health care. During COVID-1 confinement, diabetic patients could have improved their glycaemic monitoring thanks to these devices, although health care in these patients may have been limited due to confinement. METHODS: A 12-month longitudinal study in which a total of 206 type I diabetics participated, belonging to a single health area. Sociodemographic and analytical data and the Self Care Inventory Revised questionnaire (SCI-R) were collected. STROBE checklist was followed. RESULTS: The analysis showed differences related to the use of the sensor. After the study period, patients obtained better levels of basal glucose, glycosylated haemoglobin, creatinine, cholesterol, triglycerides and LDL. In addition, a significant increase in the total score of the SCI-R questionnaire was observed after the use of the monitor (MD -7.77; 95% CI -10.43, -8.29). The same occurred with different SCI-R items such as diet (MD -2.995; 95% CI -3.24, -2.57), glucose determination (MD -3.21; 95% CI -3.52, -2.91), medication administration (MD -2.58; 95% CI -2.53, -1.96) and hypoglycaemic episodes (MD -1.07; 95% CI -1.21, -0.93). In the analysis by groups, worse values of glycosylated haemoglobin and adherence to treatment (p < .05) were observed in overweight/obese subjects versus those with normal weight after one year of study. CONCLUSION: The use of flash monitoring is related to better adherence to most of the recommended habits in diabetes. Nevertheless, there seems to be no relationship with an improvement in physical exercise and preventive aspects of diabetes. A good nursing intervention to support physical exercise and the use of mHealth devices could improve the control of diabetic patients. RELEVANCE TO CLINICAL PRACTICE: The use of this mHealth device has shown positive results and reduced complications. Despite less contact with healthcare facilities due to the pandemic, type 1 diabetic patients have improved their blood results and adherence after using the device for one year. Nursing staff should focus on promoting physical activity and routine disease care in type 1 diabetics.

Estudio comparativo del consumo de comida basura en ancianos del ámbito rural frente al ámbito urbano / Comparative study of the fast food consumption in elder people living rural areas versus urban areas

Objetivo: analizar el consumo de comida basura en ancianos del ámbito rural y del ámbito urbano, comprobando si hay diferencias significativas entre ambos grupos. Método: estudio descriptivo transversal en 346 ancianos con una horquilla de edad de 65-95 años, residentes en Porzuna y Madrid. Recogida de datos: encuesta autoadministrada con escala Likert. Análisis de datos: Chi-cuadrado, valor de significación p, intervalos de confianza. Resultados: un 27% de los ancianos rurales (n=46; DE=16,26; IC95%=53,87-61,13) y un 39% de los ancianos urbanitas (n=69) consumen comida basura, existiendo diferencias significativas: X2(1) = 6,1052; X2 crítico = 3,8415; p = 0,014 < 0,05. Si hablamos de las repercusiones en la salud, un 45% de los ancianos rurales (n=42; DE=14,14; IC95%=48,84-55,16) y un 90% de los urbanos (n=62) las percibe como negativas, sin que existan diferencias estadísticamente significativas: X2(1) = 0,067; X2 crítico = 3,8415; p = 0,7957 > 0,05. Discusión: la Escuela de Administración de Empresas ha registrado en España un ascenso del gasto en comida basura por habitante del 49,65% respecto a 2014. Según García y Villalobos su consumo en ancianos se debe a la disminución de poder adquisitivo, la muerte del cónyuge y/o la falta de apoyo social. Conclusiones: existen diferencias estadísticamente significativas en el consumo de comida basura, pero no en la percepción que tienen los ancianos de ambos grupos sobre su estado de salud derivada de su consumo

Objective: to analyze the consumption of junk food in elder people living in rural and urban areas, as well as to verify if there are significant differences between both. Method: cross-sectional descriptive study in 346 elder people in a fork of age 65-95 years, living in Porzuna and Madrid. Data collection: self-administered survey with Likert scale. Data analysis: Chi-square, significance value p, confidence intervals. Results: 27% of rural elder people (n=46, SD=16,26; CI95%=53,87-61,13) and 39% of urban elder people (n=69) consume junk food, with significant differences: X2(1) = 6,1052; X2 crítico = 3,8415; p = 0,014 < 0,05. If we talk about the consequences in elder people's health, 45% of the rural elder people (n=42, SD=14,14; CI95%=48,84-55,16) and 90% of the urban elder people (n=62) perceive them as negative without statistically significant differences: X2(1) = 0,067; X2 crítico = 3,8415; p = 0,7957 > 0,05. Discussion: the Business School has registered in Spain an increase in spending on "junk food" per capita of 49.65% compared to 2014. According to Garcia and Villalobos, their consumption in the elderly is due to the decrease in purchasing power, wife's death and/or the lack of social support. Conclusions: there are statistically significant differences in the consumption of "junk food", but not in the perception that the elderly of both groups have about their state of health derived from their consumption

Estudio comparativo del consumo de comida basura en ancianos del ámbito rural frente al ámbito urbano / Comparative study of the fast food consumption in elder people living rural area versus urban areas

Objetivo: analizar el consumo de comida basura en ancianos del ámbito rural y del ámbito urbano, comprobando si hay diferencias significativas entre ambos grupos. Método: estudio descriptivo transversal en 346 ancianos con una horquilla de edad de 65-95 años, residentes en Porzuna y Madrid. Recogida de datos: encuesta autoadministrada con escala Likert. Análisis de datos: Chi-cuadrado, valor de significación p, intervalos de confianza. Resultados: un 27% de los ancianos rurales (n=46; DE=16,26; IC95%=53,87-61,13) y un 39% de los ancianos urbanitas (n=69) consumen comida basura, existiendo diferencias significativas: X2(1) = 6,1052; X2 crítico = 3,8415; p = 0,014 < 0,05. Si hablamos de las repercusiones en la salud, un 45% de los ancianos rurales (n=42; DE=14,14; IC95%=48,84-55,16) y un 90% de los urbanos (n=62) las percibe como negativas, sin que existan diferencias estadísticamente significativas: X2(1) = 0,067; X2 crítico = 3,8415; p = 0,7957 > 0,05. Discusión: la Escuela de Administración de Empresas ha registrado en España un ascenso del gasto en comida basura por habitante del 49,65% respecto a 2014. Según García y Villalobos su consumo en ancianos se debe a la disminución de poder adquisitivo, la muerte del cónyuge y/o la falta de apoyo social. Conclusiones: existen diferencias estadísticamente significativas en el consumo de comida basura, pero no en la percepción que tienen los ancianos de ambos grupos sobre su estado de salud derivada de su consumo

Objective: to analyze the consumption of junk food in elder people living in rural and urban areas, as well as to verify if there are significant differences between both. Method: cross-sectional descriptive study in 346 elder people in a fork of age 65-95 years, living in Porzuna and Madrid. Data collection: self-administered survey with Likert scale. Data analysis: Chi-square, significance value p, confidence intervals. Results: 27% of rural elder people (n=46, SD=16,26; CI95%=53,87-61,13) and 39% of urban elder people (n=69) consume junk food, with significant differences: X2(1) = 6,1052; X2 crítico = 3,8415; p = 0,014 < 0,05. If we talk about the consequences in elder people's health, 45% of the rural elder people (n=42, SD=14,14; CI95%=48,84-55,16) and 90% of the urban elder people (n=62) perceive them as negative without statistically significant differences: X2(1) = 0,067; X2 crítico = 3,8415; p = 0,7957 > 0,05. an increase in spending on "junk food" per capita of 49.65% compared to 2014. According to Garcia and Villalobos, their consumption in the elderly is due to the decrease in purchasing power, wife's death and/or the lack of social support. Conclusions: there are statistically significant differences in the consumption of "junk food", but not in the perception that the elderly of both groups have about their state of health derived from their consumption