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 Matematika
Aims: 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.
Open Access
Sex-dependent effect of socioeconomic status on cardiovascular event risk in a population-based cohort of patients with type 2 diabetes
(Oxford University Press, 2024) Enguita Germán, Mónica; Tamayo Rodríguez, Ibai; Librero, Julián; Ballesteros-Domínguez, Asier; Oscoz-Villanueva, Ignacio; Galbete Jiménez, Arkaitz; Arnedo Ajona, Laura; Cambra Contin, Koldo; Gorricho Mendívil, Javier; Moreno Iribas, Conchi; Millán-Ortuondo, Eduardo; Ibáñez Beroiz, Berta; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Ciencias de la Salud; Osasun Zientziak; Gestión de Empresas; Enpresen Kudeaketa
Background: Socioeconomic status (SES) factors often result in profound health inequalities among populations, and their impact may differ between sexes. The aim of this study was to estimate and compare the effect of socioeconomic status indicators on incident cardiovascular disease (CVD)-related events among males and females with type 2 diabetes (T2D). Methods: A population-based cohort from a southern European region including 24,650 patients with T2D was followed for five years. The sex-specific associations between SES indicators and the first occurring CVD event were modeled using multivariate Fine-Gray competing risk models. Coronary Heart Disease (CHD) and stroke were considered secondary outcomes. Results: Patients without a formal education had a significantly higher risk of CVD than those with a high school or university education, with adjusted hazard ratios (HRs) equal to 1.24 (95%CI: 1.09-1.41) for males and 1.50 (95%CI: 1.09-2.06) for females. Patients with <18 000euro income had also higher CVD risk than those with >= 18 000euro, with HRs equal to 1.44 (95%CI: 1.29-1.59) for males and 1.42 (95%CI: 1.26-1.60) for females. Being immigrant showed a HR equal to 0.81 (95%CI: 0.66-0.99) for males and 1.13 (95%CI: 0.68-1.87) for females. Similar results were observed for stroke, but differed for CHD when income is used, which had higher effect in females. Conclusion: Socioeconomic inequalities in CVD outcomes are present among T2D patients, and their magnitude for educational attainment is sex-dependent, being higher in females, suggesting the need to consider them when designing tailored primary prevention and management strategies.
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 Matematika
Cardiovascular 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.
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 Mendívil, Javier; Olazarán Santesteban, Álvaro; Arnedo Ajona, Laura; Moreno Iribas, Conchi; Lafita, Javier; Ibáñez Beroiz, Berta; Ciencias de la Salud; Osasun Zientziak; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Gestión de Empresas; Enpresen Kudeaketa
Purpose 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.

Tamayo Rodríguez, Ibai

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