Person: Cambra Contin, Koldo
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Cambra Contin
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Koldo
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Ciencias de la Salud
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0000-0002-1355-8412
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811013
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Publication Open Access Socioeconomic inequalities in cardiometabolic control in patients with type 2 diabetes(BioMed Central, 2018) Ibáñez Beroiz, Berta; Galbete Jiménez, Arkaitz; Goñi, María José; Forga, Lluís; Cambra Contin, Koldo; Ciencias de la Salud; Osasun ZientziakBackground: The aim of this study was to determine if the achievement of control targets in patients with type 2 diabetes was associated with personal socioeconomic factors and if these associations were sex-dependent. Methods: This cross-sectional, population-based study was conducted in Spain. Glycated haemoglobin (HbA1c) level and other clinical parameters were obtained from electronic primary care records (n = 32,638 cases). Socioeconomic status was determined using education level and yearly income. Among patients, having their HbA1c level checked during the previous year was considered as an indirect measure of the process of care, whereas tobacco use and clinical parameters such as HbA1c, low-density lipoprotein cholesterol (LDL-c) and blood pressure (BP) were considered intermediate control outcomes. General linear mixed effect models were used to assess associations. Results: The achievement of metabolic and cardiovascular control targets in patients with type 2 diabetes was associated with educational level and income, and socioeconomic gradients differed by sex. The probability of having had an HbA1c test performed in the previous year was higher in patients with lower education levels. Patients in the lowest income and education level categories were less likely to have reached the recommended HbA1c level. Males in the lowest education level categories were less likely to be non-smokers or to have achieved the blood pressure targets. In contrast, patients within the low income categories had a higher probability of reaching the recommended LDL-c level. Conclusions: Our results suggest the presence of socioeconomic inequalities in the achievement of cardiovascular and metabolic control that differed in direction and magnitude depending on the measured outcome and sex of the patient. These findings may help health professionals focus on high-risk individuals to decrease health inequalities.Publication Open Access Cardiovascular risk in patients with type 2 diabetes: a systematic review of prediction models(Elsevier, 2022) Galbete Jiménez, Arkaitz; Tamayo Rodríguez, Ibai; Librero, Julián; Enguita Germán, Mónica; Cambra Contin, Koldo; Ibáñez Beroiz, Berta; Ciencias de la Salud; Osasun Zientziak; Estadística, Informática y Matemáticas; Estatistika, Informatika eta MatematikaAims: to identify all cardiovascular disease risk prediction models developed in patients with type 2 diabetes or in the general population with diabetes as a covariate updating previous studies, describing model performance and analysing both their risk of bias and their applicability. Methods: a systematic search for predictive models of cardiovascular risk was performed in PubMed. The CHARMS and PROBAST guidelines for data extraction and for the assessment of risk of bias and applicability were followed. Google Scholar citations of the selected articles were reviewed to identify studies that conducted external validations. Results: the titles of 10,556 references were extracted to ultimately identify 19 studies with models developed in a population with diabetes and 46 studies in the general population. Within models developed in a population with diabetes, only six were classified as having a low risk of bias, 17 had a favourable assessment of applicability, 11 reported complete model information, and also 11 were externally validated. Conclusions: there exists an overabundance of cardiovascular risk prediction models applicable to patients with diabetes, but many have a high risk of bias due to methodological shortcomings and independent validations are scarce. We recommend following the existing guidelines to facilitate their applicability.Publication Open Access Effect of physical activity on cardiovascular event risk in a population-based cohort of patients with type 2 diabetes(MDPI, 2021) Enguita Germán, Mónica; Tamayo Rodríguez, Ibai; Galbete Jiménez, Arkaitz; Librero, Julián; Cambra Contin, Koldo; Ibáñez Beroiz, Berta; Estadística, Informática y Matemáticas; Estatistika, Informatika eta MatematikaCardiovascular disease (CVD) is the most common cause of morbidity and mortality among patients with type 2 diabetes (T2D). Physical activity (PA) is one of the few modifiable factors that can reduce this risk. The aim of this study was to estimate to what extent PA can contribute to reducing CVD risk and all-cause mortality in patients with T2D. Information from a population-based cohort including 26,587 patients with T2D from the Navarre Health System who were fol-lowed for five years was gathered from electronic clinical records. Multivariate Cox regression models were fitted to estimate the effect of PA on CVD risk and all-cause mortality, and the approach was complemented using conditional logistic regression models within a matched nested case–con-trol design. A total of 5111 (19.2%) patients died during follow-up, which corresponds to 37.8% of the inactive group, 23.9% of the partially active group and 12.4% of the active group. CVD events occurred in 2362 (8.9%) patients, which corresponds to 11.6%, 10.1% and 7.6% of these groups. Compared with patients in the inactive group, and after matching and adjusting for confounders, the OR of having a CVD event was 0.84 (95% CI: 0.66–1.07) for the partially active group and 0.71 (95% CI: 0.56–0.91) for the active group. A slightly more pronounced gradient was obtained when focused on all-cause mortality, with ORs equal to 0.72 (95% CI: 0.61–0.85) and 0.50 (95% CI: 0.42–0.59), respectively. This study provides further evidence that physically active patients with T2D may have a reduced risk of CVD-related complications and all-cause mortality.Publication Open Access Cohort Profile: CArdiovascular Risk in patients with DIAbetes in NAvarra (CARDIANA cohort)(BMJ, 2023) Tamayo Rodríguez, Ibai; Librero, Julián; Galbete Jiménez, Arkaitz; Cambra Contin, Koldo; Enguita Germán, Mónica; Forga, Lluís; Goñi, María José; Lecea, Óscar; Gorricho, Javier; Olazarán Santesteban, Álvaro; Arnedo Ajona, Laura; Moreno Iribas, C.; Lafita, Javier; Ibáñez Beroiz, Berta; Ciencias de la Salud; Osasun Zientziak; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Gestión de Empresas; Enpresen KudeaketaPurpose The CArdiovascular Risk in patients with DIAbetes in Navarra (CARDIANA cohort) cohort was established to assess the effects of sociodemographic and clinical variables on the risk of cardiovascular events in patients with type 1 (T1D) or type 2 (T2D) diabetes, with a special focus on socioeconomic factors, and to validate and develop cardiovascular risk models for these patients. Participants The CARDIANA cohort included all patients with T1D and T2D diabetes registered in the Public Health Service of Navarra with prevalent disease on 1 January 2012. It consisted of 1067 patients with T1D (ages 2–88 years) and 33842 patients with T2D (ages 20–105 years), whose data were retrospectively extracted from the Health and Administrative System Databases. Findings to date The follow-up period for wave 1 was from 1 January 2012 to 31 December 2016. During these 5 years, 9 patients (0.8%; 95%CI (0.4% to 1.6%)) in the T1D cohort developed a cardiovascular disease event, whereas for the T2D cohort, 2602 (7.7%; 95%CI (7.4% to 8.0%)) had an event. For the T2D cohort, physical activity was associated with a reduced risk of cardiovascular events, with adjusted estimated ORs equal to 0.84 (95% CI 0.66 to 1.07) for the partially active group and 0.71 (95% CI 0.56 to 0.91) for the active group, compared with patients in the non-active group. Future plans The CARDIANA cohort is currently being used to assess the effect of sociodemographic risk factors on CV risk at 5 years and to externally validate cardiovascular predictive models. A second wave is being conducted in late 2022 and early 2023, to extend the follow-up other 5 years, from 1 January 2016 to 31 December 2021. Periodic data extractions are planned every 5 years.