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dc.contributor.authorMatsushita, Kunihiro
dc.contributor.authorKaptoge, Stephen
dc.contributor.authorHageman, Steven H J
dc.contributor.authorSang, Yingying
dc.contributor.authorBallew, Shoshana H.
dc.contributor.authorGrams, Morgan E.
dc.contributor.authorSurapaneni, Aditya
dc.contributor.authorSun, Luanluan
dc.contributor.authorArnlov, Johan
dc.contributor.authorBozic, Milica
dc.contributor.authorBrenner, Hermann
dc.contributor.authorBrunskill, Nigel J.
dc.contributor.authorChang, Alex R.
dc.contributor.authorChinnadurai, Rajkumar
dc.contributor.authorCirillo, Massimo
dc.contributor.authorCorrea, Adolfo
dc.contributor.authorEbert, Natalie
dc.contributor.authorEckardt, Kai-Uwe
dc.contributor.authorGansevoort, Ron T.
dc.contributor.authorGutierrez, Orlando
dc.contributor.authorHadaegh, Farzad
dc.contributor.authorHe, Jiang
dc.contributor.authorHwang, Shih-Jen
dc.contributor.authorJafar, Tazeen H.
dc.contributor.authorJassal, Simerjot K.
dc.contributor.authorKayama, Takamasa
dc.contributor.authorKovesdy, Csaba P.
dc.contributor.authorLandman, Gijs W.
dc.contributor.authorLevey, Andrew S.
dc.contributor.authorLloyd-Jones, Donald M.
dc.contributor.authorMajor, Rupert W.
dc.contributor.authorMiura, Katsuyuki
dc.contributor.authorMuntner, Paul
dc.contributor.authorNadkarni, Girish N.
dc.contributor.authorNowak, Christoph
dc.contributor.authorOhkubo, Takayoshi
dc.contributor.authorPena, Michelle J.
dc.contributor.authorPolkinghorne, Kevan R.
dc.contributor.authorSairenchi, Toshimi
dc.contributor.authorSchaeffner, Elke
dc.contributor.authorSchneider, Markus P.
dc.contributor.authorShalev, Varda
dc.contributor.authorShlipak, Michael G.
dc.contributor.authorSolbu, Marit Dahl
dc.contributor.authorStempniewicz, Nikita
dc.contributor.authorTollitt, James
dc.contributor.authorValdivielso, José M
dc.contributor.authorvan der Leeuw, Joep
dc.contributor.authorWang, Angela Yee-Moon
dc.contributor.authorWen, Chi-Pang
dc.contributor.authorWoodward, Mark
dc.contributor.authorYamagishi, Kazumasa
dc.contributor.authorYatsuya, Hiroshi
dc.contributor.authorZhang, Luxia
dc.contributor.authorDorresteijn, Jannick A N
dc.contributor.authorDi Angelantonio, Emanuele
dc.contributor.authorVisseren, Frank L J
dc.contributor.authorPennells, Lisa
dc.contributor.authorCoresh, Josef
dc.date.accessioned2024-02-12T12:26:35Z
dc.date.available2024-02-12T12:26:35Z
dc.date.issued2022-08-16
dc.description.abstractAims - The 2021 European Society of Cardiology (ESC) guideline on cardiovascular disease (CVD) prevention categorizes moderate and severe chronic kidney disease (CKD) as high and very-high CVD risk status regardless of other factors like age and does not include estimated glomerular filtration rate (eGFR) and albuminuria in its algorithms, systemic coronary risk estimation 2 (SCORE2) and systemic coronary risk estimation 2 in older persons (SCORE2-OP), to predict CVD risk. We developed and validated an ‘Add-on’ to incorporate CKD measures into these algorithms, using a validated approach.<p> <p>Methods - In 3,054 840 participants from 34 datasets, we developed three Add-ons [eGFR only, eGFR + urinary albumin-to-creatinine ratio (ACR) (the primary Add-on), and eGFR + dipstick proteinuria] for SCORE2 and SCORE2-OP. We validated C-statistics and net reclassification improvement (NRI), accounting for competing risk of non-CVD death, in 5,997 719 participants from 34 different datasets.<p> <p>Results - In the target population of SCORE2 and SCORE2-OP without diabetes, the CKD Add-on (eGFR only) and CKD Add-on (eGFR + ACR) improved C-statistic by 0.006 (95%CI 0.004–0.008) and 0.016 (0.010–0.023), respectively, for SCORE2 and 0.012 (0.009–0.015) and 0.024 (0.014–0.035), respectively, for SCORE2-OP. Similar results were seen when we included individuals with diabetes and tested the CKD Add-on (eGFR + dipstick). In 57 485 European participants with CKD, SCORE2 or SCORE2-OP with a CKD Add-on showed a significant NRI [e.g. 0.100 (0.062–0.138) for SCORE2] compared to the qualitative approach in the ESC guideline.<p> <p>Conclusion - Our Add-ons with CKD measures improved CVD risk prediction beyond SCORE2 and SCORE2-OP. This approach will help clinicians and patients with CKD refine risk prediction and further personalize preventive therapies for CVD.en_US
dc.identifier.citationMatsushita, Kaptoge, Hageman, Sang, Ballew, Grams, Surapaneni, Sun, Arnlov, Bozic, Brenner, Brunskill, Chang, Chinnadurai, Cirillo, Correa, Ebert, Eckardt, Gansevoort, Gutierrez, Hadaegh, He, Hwang, Jafar, Jassal, Kayama, Kovesdy, Landman, Levey, Lloyd-Jones, Major, Miura, Muntner, Nadkarni, Nowak, Ohkubo, Pena, Polkinghorne, Sairenchi, Schaeffner, Schneider, Shalev, Shlipak, Solbu, Stempniewicz, Tollitt, Valdivielso, van der Leeuw, Wang, Wen, Woodward, Yamagishi, Yatsuya, Zhang, Dorresteijn, Di Angelantonio, Visseren, Pennells, Coresh. Including measures of chronic kidney disease to improve cardiovascular risk prediction by SCORE2 and SCORE2-OP. European Journal of Preventive Cardiology (EJPC). 2023;30(1):8-16en_US
dc.identifier.cristinIDFRIDAID 2138757
dc.identifier.doi10.1093/eurjpc/zwac176
dc.identifier.issn2047-4873
dc.identifier.issn2047-4881
dc.identifier.urihttps://hdl.handle.net/10037/32910
dc.language.isoengen_US
dc.publisherOxford University Pressen_US
dc.relation.journalEuropean Journal of Preventive Cardiology (EJPC)
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2023 The Author(s)en_US
dc.titleIncluding measures of chronic kidney disease to improve cardiovascular risk prediction by SCORE2 and SCORE2-OPen_US
dc.type.versionacceptedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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