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Incremental value of risk factor variability for cardiovascular risk prediction in individuals with type 2 diabetes: results from UK primary care electronic health records.
Xu, Zhe; Arnold, Matthew; Sun, Luanluan; Stevens, David; Chung, Ryan; Ip, Samantha; Barrett, Jessica; Kaptoge, Stephen; Pennells, Lisa; Di Angelantonio, Emanuele; Wood, Angela M.
Afiliación
  • Xu Z; British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
  • Arnold M; British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
  • Sun L; British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
  • Stevens D; British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
  • Chung R; British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
  • Ip S; British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
  • Barrett J; Medical Research Council Biostatistics Unit, Cambridge Institute of Public Health, University of Cambridge, Cambridge, UK.
  • Kaptoge S; British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
  • Pennells L; National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK.
  • Di Angelantonio E; British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
  • Wood AM; British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Int J Epidemiol ; 51(6): 1813-1823, 2022 12 13.
Article en En | MEDLINE | ID: mdl-35776101
BACKGROUND: Cardiovascular disease (CVD) risk prediction models for individuals with type 2 diabetes are important tools to guide intensification of interventions for CVD prevention. We aimed to assess the added value of incorporating risk factors variability in CVD risk prediction for people with type 2 diabetes. METHODS: We used electronic health records (EHRs) data from 83 910 adults with type 2 diabetes but without pre-existing CVD from the UK Clinical Practice Research Datalink for 2004-2017. Using a landmark-modelling approach, we developed and validated sex-specific Cox models, incorporating conventional predictors and trajectories plus variability of systolic blood pressure (SBP), total and high-density lipoprotein (HDL) cholesterol, and glycated haemoglobin (HbA1c). Such models were compared against simpler models using single last observed values or means. RESULTS: The standard deviations (SDs) of SBP, HDL cholesterol and HbA1c were associated with higher CVD risk (P < 0.05). Models incorporating trajectories and variability of continuous predictors demonstrated improvement in risk discrimination (C-index = 0.659, 95% CI: 0.654-0.663) as compared with using last observed values (C-index = 0.651, 95% CI: 0.646-0.656) or means (C-index = 0.650, 95% CI: 0.645-0.655). Inclusion of SDs of SBP yielded the greatest improvement in discrimination (C-index increase = 0.005, 95% CI: 0.004-0.007) in comparison to incorporating SDs of total cholesterol (C-index increase = 0.002, 95% CI: 0.000-0.003), HbA1c (C-index increase = 0.002, 95% CI: 0.000-0.003) or HDL cholesterol (C-index increase= 0.003, 95% CI: 0.002-0.005). CONCLUSION: Incorporating variability of predictors from EHRs provides a modest improvement in CVD risk discrimination for individuals with type 2 diabetes. Given that repeat measures are readily available in EHRs especially for regularly monitored patients with diabetes, this improvement could easily be achieved.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedades Cardiovasculares / Diabetes Mellitus Tipo 2 Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Aspecto: Patient_preference Límite: Adult / Female / Humans / Male País/Región como asunto: Europa Idioma: En Revista: Int J Epidemiol Año: 2022 Tipo del documento: Article Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedades Cardiovasculares / Diabetes Mellitus Tipo 2 Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Aspecto: Patient_preference Límite: Adult / Female / Humans / Male País/Región como asunto: Europa Idioma: En Revista: Int J Epidemiol Año: 2022 Tipo del documento: Article Pais de publicación: Reino Unido