Telehealth model versus in-person standard care for persons with type 1 diabetes treated with multiple daily injections: an open-label randomized controlled trial

ObjectiveIncreasing evidence indicates that the telehealth (TH) model is noninferior to the in-person approach regarding metabolic control in type 1 diabetes (T1D) and offers advantages such as a decrease in travel time and increased accessibility for shorter/frequent visits. The primary aim of this study was to compare the change in glycated hemoglobin (HbA1c) at 6 months in T1D care in a rural area between TH and in-person visits.Research design and methodsRandomized controlled, open-label, parallel-arm study among adults with T1D. Participants were submitted to in-person visits at baseline and at months 3 and 6 (conventional group) or teleconsultation in months 1 to 4 plus 2 in-person visits (baseline and 6 months) (TH group). Mixed effects models estimated differences in HbA1c changes.ResultsFifty-five participants were included (29 conventional/26 TH). No significant differences in HbA1c between groups were found. Significant improvement in time in range (5.40, 95% confidence interval (CI): 0.43-10.38; p < 0.05) and in time above range (-6.34, 95% CI: -12.13- -0.55;p < 0.05) in the TH group and an improvement in the Diabetes Quality of Life questionnaire (EsDQoL) score (-7.65, 95% CI: -14.67 - -0.63; p < 0.05) were observed. In TH, the costs for the participants were lower.ConclusionsThe TH model is comparable to in-person visits regarding HbA1c levels at the 6-month follow-up, with significant improvement in some glucose metrics and health-related quality of life. Further studies are necessary to evaluate a more efficient timing of the TH visits

La càrrega futura de l'excés de casos de diabetis mellitus de tipus 1 durant la pandèmia de COVID a Catalunya: avaluació econòmica

Diabetis mellitus de tipus 1; COVID-19; Avaluació econòmicaDiabetes mellitus de tipo 1; COVID-19; Evaluación económicaType 1 diabetes mellitus; COVID-19; Economic evaluationThis paper aims to provide a comprehensive assessment of the impact of the excess cases of DM1 during the first two years of the COVID-19 pandemic on health outcomes and health spending in Catalonia.Este documento pretende proporcionar una evaluación exhaustiva del impacto del exceso de casos de DM1 durante los dos primeros años de la pandemia COVID-19 en resultados de salud y gasto sanitario en Cataluña.Aquest document pretén proporcionar una avaluació exhaustiva de l'impacte de l'excés de casos de DM1 durant els dos primers anys de la pandèmia COVID-19 en els resultats de salut i la despesa sanitària a Catalunya

Seven-year mortality in heart failure patients with undiagnosed diabetes : an observational study

Background: Patients with type 2 diabetes mellitus and heart failure have adverse clinical outcomes, but the characteristics and prognosis of those with undiagnosed diabetes in this setting has not been established. Methods: In total, 400 patients admitted consecutively with acute heart failure were grouped in three glycaemic categories: no diabetes, clinical diabetes (previously reported or with hypoglycaemic treatment) and undiagnosed diabetes. The latter was defined by the presence of at least two measurements of fasting plasma glycaemia ≥ 7 mmol/L before or after the acute episode.Group differences were tested by proportional hazards models in all-cause and cardiovascular mortality during a 7-year follow-up. Results: There were 188 (47%) patients without diabetes, 149 (37%) with clinical diabetes and 63 (16%) with undiagnosed diabetes. Patients with undiagnosed diabetes had a lower prevalence of hypertension, dyslipidaemia, peripheral vascular disease and previous myocardial infarction than those with clinical diabetes and similar to that of those without diabetes. The adjusted hazards ratios for 7-year total and cardiovascular mortality compared with the group of subjects without diabetes were 1.69 (95% CI: 1.17-2.46) and 2.45 (95% CI: 1.58-3.81) for those with undiagnosed diabetes, and 1.48 (95% CI: 1.10-1.99) and 2.01 (95% CI: 1.40-2.89) for those with clinical diabetes. Conclusions: Undiagnosed diabetes is common in patients requiring hospitalization for acute heart failure. Patients with undiagnosed diabetes, despite having a lower cardiovascular risk profile than those with clinical diabetes, show a similar increased mortality

La incidència de diabetis mellitus de tipus 1 durant la pandèmia de COVID-19 a Catalunya

Coronavirus SARS-CoV-2; COVID-19; 2019-nCoV; Diabetis mellitus de tipus 1; Malaltia crònicaCoronavirus SARS-CoV-2; COVID-19; 2019-nCoV; Diabetes mellitus de tipo 1; Enfermedad crónicaCoronavirus SARS-CoV-2; COVID-19; 2019-nCoV; Type 1 diabetes mellitus; Chronic diseaseIntroducció: la diabetis de tipus 1 és una malaltia crònica que es caracteritza per la falta de producció d’insulina per part del pàncrees, el que provoca un augment dels nivells de glucosa en sang. En alguns països s’ha reportat un increment en la incidència de diabetis de tipus 1 durant la pandèmia de COVID-19. Objectiu: comprovar si ha augmentat la incidència de diabetis de tipus 1 durant la pandèmia de COVID-19 a Catalunya. Mètodes: estimació de la incidència esperada de diabetis de tipus 1 per als anys 2020-2021 a través d’una regressió Poisson, i comparació amb la incidència observada. La incidència observada es va obtenir a partir del registre poblacional de diabetis de tipus 1 del programa PADRIS d’analítica de dades d’AQuAS. Resultats: de forma agregada, l’any 2020 la incidència no va augmentar significativament respecte a l’any anterior, però per a l’any 2021 va augmentar significativament en un 28 %. Els majors augments, en tots dos anys, es van donar entre les persones menors de 18 anys i les dones. Conclusions i discussió: durant la pandèmia de COVID-19 es va produir un augment notable i estadísticament significatiu de la incidència de casos de DM1 a Catalunya, encara que no és possible establir una relació de causalitat entre la pandèmia i la diabetis. Es requereixen més estudis per investigar els possibles mecanismes biològics o socials que podrien explicar aquest fenomen i les seves implicacions clíniques i sanitàries.Introducción: la diabetes tipo 1 es una enfermedad crónica que se caracteriza por la falta de producción de insulina por parte del páncreas, lo que provoca un aumento de los niveles de glucosa en sangre. En algunos países se ha reportado un incremento en la incidencia de diabetes tipo 1 durante la pandemia de COVID-19. Objetivo: comprobar si ha aumentado la incidencia de diabetes tipo 1 durante la pandemia de COVID-19 en Cataluña. Métodos: estimación de la incidencia esperada de diabetes tipo 1 para los años 2020-2021 a través de una regresión Poisson, y comparación con la incidencia observada. La incidencia observada se obtuvo a partir del registro poblacional de diabetes tipo 1 del programa PADRIS de analítica de datos de AQuAS. Resultados: de forma agregada, en el año 2020 la incidencia no aumentó significativamente respecto al año anterior, pero para el año 2021 aumentó significativamente en un 28%. Los mayores aumentos, en ambos años, se dieron entre las personas menores de 18 años y las mujeres. Conclusiones y discusión: durante la pandemia de COVID-19 se produjo un aumento notable y estadísticamente significativo de la incidencia de casos de DM1 en Cataluña, aunque no es posible establecer una relación de causalidad entre la pandemia y la diabetes. Se requieren más estudios para investigar los posibles mecanismos biológicos o sociales que podrían explicar este fenómeno y sus implicaciones clínicas y sanitarias.Introduction: Type 1 diabetes (T1D) is a chronic disease characterized by insufficient insulin production by the pancreas, leading to high blood glucose levels. Some countries have reported an increase in the incidence of T1D during the COVID-19 pandemic. Objective: To examine whether the incidence of T1D has increased during the COVID-19 pandemic in Catalonia. Methods: We estimated the expected incidence of T1D for 2020-2021 using a Poisson regression model based on historical data from 2010 to 2019. We compared the expected incidence with the observed incidence obtained from the population-based T1D registry of the PADRIS data analysis program of AQuAS. Results: In 2020, there was no significant increase in incidence compared to 2019, but in 2021 there was a significant increase of 28%. The largest increases occurred among people under 18 years old and women. Conclusions and discussion: There was a notable and statistically significant increase in T1D cases in Catalonia during the COVID-19 pandemic, although a causal relationship between the pandemic and diabetes cannot be established. Further studies are needed to explore the possible biological or social mechanisms that could explain this phenomenon and its clinical and health implications

Contribution of cardio-vascular risk factors to depressive status in the PREDIMED-PLUS Trial. A cross-sectional and a 2-year longitudinal study

Background Cardio-vascular disease and depression are thought to be closely related, due to shared risk factors. The aim of the study was to determine the association between cardio-vascular risk (CVR) factors and depressive status in a population (55-75 years) with metabolic syndrome (MetS) from the PREDIMED-Plus trial. Methods and findings Participants were classified into three groups of CVR according to the Framingham-based REGICOR function: (1) low (LR), (2) medium (MR) or (3) high/very high (HR). The Beck Depression Inventory-II (BDI-II) was used to assess depressive symptoms at baseline and after 2 years. The association between CVR and depressive status at baseline (n = 6545), and their changes after 2 years (n = 4566) were evaluated through multivariable regression models (logistic and linear models). HR women showed higher odds of depressive status than LR [OR (95% CI) = 1.78 (1.26, 2.50)]. MR and HR participants with total cholesterol <160 mg/mL showed higher odds of depression than LR [OR (95% CI) = 1.77 (1.13, 2.77) and 2.83 (1.25, 6.42) respectively)] but those with total cholesterol ¿280 mg/mL showed lower odds of depression than LR [OR (95% CI) = 0.26 (0.07, 0.98) and 0.23 (0.05, 0.95), respectively]. All participants decreased their BDI-II score after 2 years, being the decrease smaller in MR and HR diabetic compared to LR [adjusted mean±SE = -0.52±0.20, -0.41 ±0.27 and -1.25±0.31 respectively). MR and HR participants with total cholesterol between 240-279 mg/mL showed greater decreases in the BDI-II score compared to LR (adjusted mean±SE = -0.83±0.37, -0.77±0.64 and 0.97±0.52 respectively). Conclusions Improving cardiovascular health could prevent the onset of depression in the elderly. Diabetes and total cholesterol in individuals at high CVR, may play a specific role in the precise response.The PREDIMED-Plus trial was supported by the European Research Council through a grant to MAM (Advanced Research Grant 2013-2018; 340918). The project was also supported by the official funding agency for biomedical research of the Spanish Government (ISCIII) through the Fondo de Investigación para la Salud (FIS), which is co-funded by the European Regional Development Fund (four coordinated FIS projects), who awarded grants to JS and JV (PI13/00673, PI13/00492, PI13/00272, PI13/01123, PI13/00462, PI13/00233, PI13/02184, PI13/00728, PI13/01090, PI13/01056, PI14/01722, PI14/00636, PI14/00618, PI14/00696, PI14/01206, PI14/01919, PI14/00853, PI14/01374, PI16/00473, PI16/00662, PI16/01873, PI16/01094, PI16/00501, PI16/00533, PI16/00381, PI16/00366, PI16/01522, PI16/01120, PI17/00764, PI17/01183, PI17/00855, PI17/01347, PI17/00525, PI17/01827, PI17/00532, PI17/00215, PI17/01441, PI17/00508, PI17/01732 and PI17/00926). The International Nut&Dried Fruit Council-FESNAD also provided funding through a grant to MAM (201302), and Recercaixa also awarded a grant to JS (2013ACUP00194). The Department of Health, Generalitat de Cataluña by the calls 'Acció instrumental de programes de recerca orientats en lámbit de la recercaila innovació en salut' and 'Pla estrategic de recerca i innovació en salut (PERIS),' also awarded a grant to FF (SLT006/17/00246). This research was also partially funded by: Consejería de Salud de la Junta de Andalucía (PI0458/2013, PS0358/2016, PI0137/2018); Generalitat Valenciana (PROMETEO/2017/017); SEMERGEN, CIBEROBN, FEDER and ISCIII (CB06/03); EU-H2020 Grants (Eat2beNICE/h2020-sfs-2016-2, ref.728018; PRIME/h2020-SC1-BHC-2018-2020, ref: 847879)

Associating mutations causing cystinuria with disease severity with the aim of providing precision medicine

Background Cystinuria is an inherited disease that results in the formation of cystine stones in the kidney, which can have serious health complications. Two genes (SLC7A9 and SLC3A1) that form an amino acid transporter are known to be responsible for the disease. Variants that cause the disease disrupt amino acid transport across the cell membrane, leading to the build-up of relatively insoluble cystine, resulting in formation of stones. Assessing the effects of each mutation is critical in order to provide tailored treatment options for patients. We used various computational methods to assess the effects of cystinuria associated mutations, utilising information on protein function, evolutionary conservation and natural population variation of the two genes. We also analysed the ability of some methods to predict the phenotypes of individuals with cystinuria, based on their genotypes, and compared this to clinical data. Results Using a literature search, we collated a set of 94 SLC3A1 and 58 SLC7A9 point mutations known to be associated with cystinuria. There are differences in sequence location, evolutionary conservation, allele frequency, and predicted effect on protein function between these mutations and other genetic variants of the same genes that occur in a large population. Structural analysis considered how these mutations might lead to cystinuria. For SLC7A9, many mutations swap hydrophobic amino acids for charged amino acids or vice versa, while others affect known functional sites. For SLC3A1, functional information is currently insufficient to make confident predictions but mutations often result in the loss of hydrogen bonds and largely appear to affect protein stability. Finally, we showed that computational predictions of mutation severity were significantly correlated with the disease phenotypes of patients from a clinical study, despite different methods disagreeing for some of their predictions. Conclusions The results of this study are promising and highlight the areas of research which must now be pursued to better understand how mutations in SLC3A1 and SLC7A9 cause cystinuria. The application of our approach to a larger data set is essential, but we have shown that computational methods could play an important role in designing more effective personalised treatment options for patients with cystinuria

Associating mutations causing cystinuria with disease severity with the aim of providing precision medicine

Background Cystinuria is an inherited disease that results in the formation of cystine stones in the kidney, which can have serious health complications. Two genes (SLC7A9 and SLC3A1) that form an amino acid transporter are known to be responsible for the disease. Variants that cause the disease disrupt amino acid transport across the cell membrane, leading to the build-up of relatively insoluble cystine, resulting in formation of stones. Assessing the effects of each mutation is critical in order to provide tailored treatment options for patients. We used various computational methods to assess the effects of cystinuria associated mutations, utilising information on protein function, evolutionary conservation and natural population variation of the two genes. We also analysed the ability of some methods to predict the phenotypes of individuals with cystinuria, based on their genotypes, and compared this to clinical data. Results Using a literature search, we collated a set of 94 SLC3A1 and 58 SLC7A9 point mutations known to be associated with cystinuria. There are differences in sequence location, evolutionary conservation, allele frequency, and predicted effect on protein function between these mutations and other genetic variants of the same genes that occur in a large population. Structural analysis considered how these mutations might lead to cystinuria. For SLC7A9, many mutations swap hydrophobic amino acids for charged amino acids or vice versa, while others affect known functional sites. For SLC3A1, functional information is currently insufficient to make confident predictions but mutations often result in the loss of hydrogen bonds and largely appear to affect protein stability. Finally, we showed that computational predictions of mutation severity were significantly correlated with the disease phenotypes of patients from a clinical study, despite different methods disagreeing for some of their predictions. Conclusions The results of this study are promising and highlight the areas of research which must now be pursued to better understand how mutations in SLC3A1 and SLC7A9 cause cystinuria. The application of our approach to a larger data set is essential, but we have shown that computational methods could play an important role in designing more effective personalised treatment options for patients with cystinuria