Comorbid autoimmune diseases and burden of diabetes-related complications in patients with type 1 diabetes from a Mediterranean area

Autoimmunity; Glycemic control; Type 1 diabetes mellitus;Autoinmunidad; Control Glicémico; Diabetes mellitus tipo 1Autoimmunitat; Control glucèmic; Diabetis mellitus tipus 1Aim: To assess the prevalence of autoimmune diseases (AID) in patients with type 1 diabetes (T1D) and to evaluate whether the rate of diabetes-related complications differs depending on the presence of AID. Methods: Cross-sectional analysis of 13,570 T1D patients aged ≥ 18 years registered in the SIDIAP database. The association between AID and diabetes-related complications was assessed by multivariable logistic regression models. Results: The prevalence of AID was 18.3% with thyroid AID being the most common. Patients with T1D and AID were more often female and their current age, age of diabetes onset and diabetes duration were higher. Patients with only thyroid AID experienced a lower risk of peripheral artery disease (odds ratio [OR] = 0.51, 95%; confidence interval [CI] 0.31 to 0.81) and kidney disease (OR = 0.68, 95%; 95% CI 0.54 to 0.85), whereas patients with other AID had an increased risk of ischemic heart disease (OR = 1.48, 95%; 95% CI 1.04 to 2.06). Conclusions: The burden of diabetes-related complications in patients with T1D differs according to the type of additional AID. The presence of diabetes complications is lower in those with autoimmune thyroid disease while the presence of other AID is associated with higher rates of ischemic heart disease

Evaluation of clinical and antidiabetic treatment characteristics of different sub-groups of patients with type 2 diabetes : Data from a Mediterranean population database

Altres ajuts: Institut Universitari d'Investigació en Atenció Primària Jordi GolAltres ajuts: MSD Spain 4R16/062-1Aims: To describe the characteristics and antidiabetic treatment among type 2 diabetes patients according to the clinical conditions prioritized in the Spanish 2020 RedGDPS (Primary Care Diabetes Study Groups Network) therapeutic algorithm: obesity, older than 75 years, chronic kidney disease, cardiovascular disease, and heart failure. Methods: Retrospective, cross-sectional study. Clinical characteristics, the use of antidiabetic drugs and the KDIGO renal risk categories at 31.12.2016 were retrieved from the SIDIAP (Information System for Research in Primary Care) database (Catalonia, Spain). Results: From a total of 373,185 type 2 diabetes patients, 37% were older than 75 years, 45% obese, 33% had chronic kidney disease, 23.2% cardiovascular disease and 6.9% heart failure. Insulin was more frequently prescribed in chronic kidney disease, cardiovascular disease and heart failure whereas Sodium-Glucose cotransporter 2 inhibitors and Glucagon Like Peptide 1 receptor agonists were scarcely prescribed (2.6% and 1.4%, respectively). Among patients with severe renal failure, contraindicated drugs like metformin (16%) and sulfonylureas (6.1%) were still in use. The 2012 KDIGO renal risk categories distribution was: Low: 60.9%, Moderate: 21.6%, High: 9.8% and Very high: 7.7%. Conclusions: Almost 80% of our T2DM patients meet one of the five clinical conditions that should be considered for treatment individualization. Importantly, a relevant number of patients with severe renal failure were found to use contraindicated drugs

Comorbid autoimmune diseases and burden of diabetes-related complications in patients with type 1 diabetes from a Mediterranean area

AIM: To assess the prevalence of autoimmune diseases (AID) in patients with type 1 diabetes (T1D) and to evaluate whether the rate of diabetes-related complications differs depending on the presence of AID. METHODS: Cross-sectional analysis of 13,570 T1D patients aged ≥ 18 years registered in the SIDIAP database. The association between AID and diabetes-related complications was assessed by multivariable logistic regression models. RESULTS: The prevalence of AID was 18.3% with thyroid AID being the most common. Patients with T1D and AID were more often female and their current age, age of diabetes onset and diabetes duration were higher. Patients with only thyroid AID experienced a lower risk of peripheral artery disease (odds ratio [OR] = 0.51, 95%; confidence interval [CI] 0.31 to 0.81) and kidney disease (OR = 0.68, 95%; 95% CI 0.54 to 0.85), whereas patients with other AID had an increased risk of ischemic heart disease (OR = 1.48, 95%; 95% CI 1.04 to 2.06). CONCLUSIONS: The burden of diabetes-related complications in patients with T1D differs according to the type of additional AID. The presence of diabetes complications is lower in those with autoimmune thyroid disease while the presence of other AID is associated with higher rates of ischemic heart disease

Potential Risk of Overtreatment in Patients with Type 2 Diabetes Aged 75 Years or Older : Data from a Population Database in Catalonia, Spain

Altres ajuts: Institut Universitari d'Investigació en Atenció Primària Jordi Gol (IDIAP Jordi Gol); Merck Sharp & Dohme de España S.A.Aim: To assess the potential risk of overtreatment in patients with type 2 diabetes (T2DM) aged 75 years or older in primary care. Methods: Electronic health records retrieved from the SIDIAP database (Catalonia, Spain) in 2016. Variables: age, gender, body mass index, registered hypoglycemia, last HbA1c and glomerular filtration rates, and prescriptions for antidiabetic drugs. Potential overtreatment was defined as having HbA1c < 7% or HbA1c < 6.5% in older patients treated with insulin, sulfonylureas, or glinides. Results: From a total population of 138,374 T2DM patients aged 75 years or older, 123,515 had at least one HbA1c available. An HbA1c below 7.0% was present in 59.1% of patients, and below 6.5% in 37.7%. Overall, 23.0% of patients were treated with insulin, 17.8% with sulfonylureas, and 6.6% with glinides. Potential overtreatment (HbA1c < 7%) was suspected in 26.6% of patients treated with any high-risk drug, 47.8% with sulfonylureas, 43.5% with glinides, and 28.1% with insulin. Using the threshold of HbA1c < 6.5%, these figures were: 21.6%, 24.4%, 17.9%, and 12.3%, respectively. Conclusion: One in four older adults with T2DM treated with antidiabetic drugs associated with a high risk of hypoglycemia might be at risk of overtreatment. This risk is higher in those treated with sulfonylureas or glinides than with insulin

INTEGRA study protocol: primary care intervention in type 2 diabetes patients with poor glycaemic control

Background The management of hyperglycaemia and associated cardiovascular risk factors in patients with type 2 diabetes mellitus (T2DM) may reduce diabetes-related complications. The strategy to broaden the knowledge base of primary care professionals to improve health care has mainly been prompted by the current reality of limited resources and access to specialized care. The main objective of this study is to assess the effectiveness of comprehensive interventions focused on treatment intensification, decrease clinical inertia and reduce possible barriers to treatment adherence in patients with poorly controlled diabetes in a primary care setting. Methods This is a two-phase mixed method study, whose aims are the development of complex interventions and the assessment of their effectiveness. The main study outcome is a change in glycated haemoglobin (HbA1c) levels. The INTEGRA study is divided into two phases. Phase 1: A qualitative study with a phenomenological approach using semi-structured interviews with the objective of determining the factors related to the participants and health care professionals that influence the development and implementation of a specific intervention strategy aimed at patients with poor glycaemic control of T2DM in primary care. Phase 2: Exploratory intervention study to be conducted in Primary Health Care Centres in Catalonia (Spain), including 3 specific health care areas. The intervention study has two arms: Intervention Group 1 and 2. Each intervention group will recruit 216 participants (the same as in the control group) between the ages of 30 and 80 years with deficient glycaemic control (HbA1c > 9%). The control group will be established based on a randomized selection from the large SIDIAP (Sistema d’Informació per al desenvolupament de la Investigació en Atenció Primària) database of patients with comparable socio-demographic and clinical characteristics from the three provinces. Discussion This study is a comprehensive, pragmatic intervention based on glycaemic treatment intensification and the control of other cardiovascular risk factors. It is also aimed at improving treatment adherence and reducing clinical inertia, which could lead to improved glycaemic control and could likewise be feasible for implementation in the actual clinical practice of primary care.The study is partially supported by unrestricted grant from Sanofi. The study has also intramural support from Institut Universitari d’Investigació en Atenció Primària Jordi Gol. The funder does not have any role in writing the study protocol. This funding source will not have any role during its execution, analyses, interpretation of the data, or decision to submit results

Analysis of the Adherence and Safety of Second Oral Glucose-Lowering Therapy in Routine Practice From the Mediterranean Area : A Retrospective Cohort Study

Altres ajuts: AstraZeneca/ESR-16-12628Altres ajuts: Applied Research Collaboration East Midlands (ARC EM)Altres ajuts: National Institute for Health Research (NIHR)Altres ajuts: Imperial Biomedical Research Centre (NIHR)The aims of our study was compare adherence measured by the medical possession ratio (MPR), time until discontinuation and describe adverse events after adding a DPP-4i, SGLT-2i, or sulfonylureas (SU) to metformin in a primary care population with insufficient glycemic control. We used routinely-collected health data from the SIDIAP database. The included subjects were matched by propensity score. The follow-up period was up to 24 months or premature discontinuation. The primary outcomes were the percentage of subjects with good adherence, treatment discontinuation and adverse events among treatment groups. The proportion of patients with good adherence (MPR> 0.8) after the addition of DPP-4i, SGLT-2i or SU was 53.6%, 68.7%, and 43.0%, respectively. SGLT-2i users were 1.7 times more likely to achieve good adherence compared with DPP-4i users (odds ratio [OR]:1.72, 98% confidence interval [CI]:1.51, 1.96), and 2.8 times more likely compared with SU users (OR: 0.35, 98% CI: 0.07, 0.29). The discontinuation hazard ratios were 1.43 (98%CI: 1.26; 1.62) and 1.60 (98%CI: 1.42; 1.81) times higher among SGLT-2i and SU users than DPP-4i users during the follow-up period. No differences were observed for adverse events among the treatment groups. In conclusion, in our real-world setting, the combination of SGLT-2i with metformin was associated with better adherence. The mean time until discontinuation was longer in the SGLT-2i group in comparison with the DPP-4i or SU groups

Prevalence and risk factors of diabetic foot disease among the people with type 2 diabetes using real-world practice data from Catalonia during 2018

Altres ajuts: 8a Convocatòria d'Ajuts a projectes de Institut Català de la Salut with SIDIAP (financing code 4R18/187-1 and file number SIDIAP-18/7).Background: Our study aimed to assess the prevalence of diabetic foot disease (DFD) and its associated risk factors among subjects attending primary care centers in Catalonia (Spain). Methods: We undertook a cross-sectional analysis of data from the primary health care (SIDIAP) database. The presence of comorbidities and concomitant medication were analyzed for subjects with or without DFD. DFD prevalence was estimated from 1st January 2018 to 31st December 2018. Results: During the 12-month observational period, out of 394,266 people with type 2 diabetes, we identified 3,277 (0.83%) active episodes of DFD in the database. The majority of these episodes were foot ulcers (82%). The mean age of patients with DFD was 70.3 (± 12.5) years and 55% were male. In the multivariable descriptive models, male gender, diabetes duration, hypertension, macrovascular, microvascular complications, and insulin and antiplatelet agents were strongly associated with DFD. A previous history of DFD was the stronger risk factor for DFD occurrence in subjects with T2DM (OR: 13.19, 95%CI: 11.81; 14.72). Conclusions: In this real-world primary care practice database, we found a lower prevalence of DFD compared to similar previous studies. Risk factors such as male sex, duration of diabetes, diabetes complications and previous history of DFD were associated with the presence of DFD

Obesity and related comorbidities in a large population-based cohort of subjects with type 1 diabetes in Catalonia

Obesity; Type 1 diabetes; Cardiovascular risk factorsObesidad; Diabetes tipo 1; Factores de riesgo cardiovascularObesitat; Diabetis tipus 1; Factors de risc cardiovascularIntroduction: Obesity, an increasing global health problem, can affect people with other disease conditions. The prevalence of obesity in people with type 1 diabetes (T1D) is not well known. The aim of this study was to describe extensively the characteristics and prevalence of different classes of obesity according to BMI (body mass index) categories in a large cohort of patients with T1D. Material and methods: This was a retrospective, cross-sectional study in Catalonia. We reviewed all patients with T1D diagnosis, ≥ 18 years old and with BMI data from the SIDIAP database. Sociodemographic and clinical data, cardiovascular risk factors, laboratory parameters and concomitant medications were collected. Results: A total of 6,068 patients with T1D were analyzed. The prevalence of obesity in the total sample was 18% (13.8% with class 1 obesity [BMI 30-34.9 kg/m2]). Patients with obesity had a higher prevalence of other cardiovascular risk factors (i.e. hypertension was 61.4% vs. 37.5%; dyslipidemia 63.6% vs 44%, and chronic kidney disease 38.4% vs. 24.4%; p 25 kg/m2. Patients with obesity did not have poorer glycemic control. Conclusion: The presence of obesity in people with T1D is frequent and cardiovascular risk factors are more common and more poorly controlled in T1D patients with obesity

Longitudinal deep learning clustering of Type 2 Diabetes Mellitus trajectories using routinely collected health records

Altres ajuts: Networking Biomedical Research Centre in the subject area of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN); Instituto de Investigación Carlos III (ISCIII); CIBER of Diabetes and Associated Metabolic Diseases (CIBERDEM).Type 2 diabetes mellitus (T2DM) is a highly heterogeneous chronic disease with different pathophysiological and genetic characteristics affecting its progression, associated complications and response to therapies. The advances in deep learning (DL) techniques and the availability of a large amount of healthcare data allow us to investigate T2DM characteristics and evolution with a completely new approach, studying common disease trajectories rather than cross sectional values. We used an Kernelized-AutoEncoder algorithm to map 5 years of data of 11,028 subjects diagnosed with T2DM in a latent space that embedded similarities and differences between patients in terms of the evolution of the disease. Once we obtained the latent space, we used classical clustering algorithms to create longitudinal clusters representing different evolutions of the diabetic disease. Our unsupervised DL clustering algorithm suggested seven different longitudinal clusters. Different mean ages were observed among the clusters (ranging from 65.3±11.6 to 72.8±9.4). Subjects in clusters B (Hypercholesteraemic) and E (Hypertensive) had shorter diabetes duration (9.2±3.9 and 9.5±3.9 years respectively). Subjects in Cluster G (Metabolic) had the poorest glycaemic control (mean glycated hemoglobin 7.99±1.42%), while cluster E had the best one (mean glycated hemoglobin 7.04±1.11%). Obesity was observed mainly in clusters A (Neuropathic), C (Multiple Complications), F (Retinopathy) and G. A dashboard is available at dm2.b2slab.upc.edu to visualize the different trajectories corresponding to the 7 clusters

Longitudinal deep learning clustering of Type 2 Diabetes Mellitus trajectories using routinely collected health records

Diabetes tipus 2; Complicacions diabètiques; Registres de salut electrònicsDiabetes tipo 2; Complicaciones diabéticas; Registros de salud electrónicosType 2 diabetes; Diabetic complications; Electronic health recordsType 2 diabetes mellitus (T2DM) is a highly heterogeneous chronic disease with different pathophysiological and genetic characteristics affecting its progression, associated complications and response to therapies. The advances in deep learning (DL) techniques and the availability of a large amount of healthcare data allow us to investigate T2DM characteristics and evolution with a completely new approach, studying common disease trajectories rather than cross sectional values. We used an Kernelized-AutoEncoder algorithm to map 5 years of data of 11,028 subjects diagnosed with T2DM in a latent space that embedded similarities and differences between patients in terms of the evolution of the disease. Once we obtained the latent space, we used classical clustering algorithms to create longitudinal clusters representing different evolutions of the diabetic disease. Our unsupervised DL clustering algorithm suggested seven different longitudinal clusters. Different mean ages were observed among the clusters (ranging from 65.3±11.6 to 72.8±9.4). Subjects in clusters B (Hypercholesteraemic) and E (Hypertensive) had shorter diabetes duration (9.2±3.9 and 9.5±3.9 years respectively). Subjects in Cluster G (Metabolic) had the poorest glycaemic control (mean glycated hemoglobin 7.99±1.42%), while cluster E had the best one (mean glycated hemoglobin 7.04±1.11%). Obesity was observed mainly in clusters A (Neuropathic), C (Multiple Complications), F (Retinopathy) and G. A dashboard is available at dm2.b2slab.upc.edu to visualize the different trajectories corresponding to the 7 clusters