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000181232 0247_ $$2doi$$a10.1093/eurjpc/zwac176
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000181232 1001_ $$00000-0002-7179-718X$$aMatsushita, Kunihiro$$b0
000181232 245__ $$aIncluding Measures of Chronic Kidney Disease to Improve Cardiovascular Risk Prediction by SCORE2 and SCORE2-OP.
000181232 260__ $$aLondon [u.a.]$$bSage Publ.$$c2023
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000181232 500__ $$a2023 Jan 11;30(1):8-16
000181232 520__ $$aThe 2021 ESC guideline on cardiovascular disease (CVD) prevention categorizes moderate and severe chronic kidney disease (CKD) as high and very-high CVD risk status regardless of other factors like age and does not include estimated glomerular filtration rate (eGFR) and albuminuria in its algorithms, SCORE2 and SCORE2-OP, to predict CVD risk. We developed and validated an 'Add-on' to incorporate CKD measures into these algorithms, using a validated approach.In 3,054,840 participants from 34 datasets, we developed three Add-ons (eGFR only, eGFR + urinary albumin-to-creatinine ratio [ACR] [the primary Add-on], and eGFR + dipstick proteinuria) for SCORE2 and SCORE2-OP. We validated c-statistics and net reclassification improvement (NRI), accounting for competing risk of non-CVD death, in 5,997,719 participants from 34 different datasets.In the target population of SCORE2 and SCORE2-OP without diabetes, the CKD Add-on (eGFR only) and CKD Add-on (eGFR + ACR) improved c-statistic by 0.006 (95%CI 0.004-0.008) and 0.016 (0.010-0.023), respectively, for SCORE2 and 0.012 (0.009-0.015) and 0.024 (0.014-0.035), respectively, for SCORE2-OP. Similar results were seen when we included individuals with diabetes and tested the CKD Add-on (eGFR + dipstick). In 57,485 European participants with CKD, SCORE2 or SCORE2-OP with a CKD Add-on showed a significant NRI (e.g., 0.100 [0.062-0.138] for SCORE2) compared to the qualitative approach in the ESC guideline.Our Add-ons with CKD measures improved CVD risk prediction beyond SCORE2 and SCORE2-OP. This approach will help clinicians and patients with CKD refine risk prediction and further personalize preventive therapies for CVD.
000181232 536__ $$0G:(DE-HGF)POF4-313$$a313 - Krebsrisikofaktoren und Prävention (POF4-313)$$cPOF4-313$$fPOF IV$$x0
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000181232 650_7 $$2Other$$acardiovascular disease
000181232 650_7 $$2Other$$achronic kidney disease
000181232 650_7 $$2Other$$ameta-analysis
000181232 650_7 $$2Other$$arisk prediction
000181232 7001_ $$00000-0002-1155-4872$$aKaptoge, Stephen$$b1
000181232 7001_ $$00000-0003-2299-6745$$aHageman, Steven Hj$$b2
000181232 7001_ $$aSang, Yingying$$b3
000181232 7001_ $$00000-0002-7547-3764$$aBallew, Shoshana H$$b4
000181232 7001_ $$00000-0002-4430-6023$$aGrams, Morgan E$$b5
000181232 7001_ $$aSurapaneni, Aditya$$b6
000181232 7001_ $$aSun, Luanluan$$b7
000181232 7001_ $$aArnlov, Johan$$b8
000181232 7001_ $$aBozic, Milica$$b9
000181232 7001_ $$0P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2$$aBrenner, Hermann$$b10$$udkfz
000181232 7001_ $$aBrunskill, Nigel J$$b11
000181232 7001_ $$aChang, Alex R$$b12
000181232 7001_ $$00000-0003-3973-6595$$aChinnadurai, Rajkumar$$b13
000181232 7001_ $$aCirillo, Massimo$$b14
000181232 7001_ $$aCorrea, Adolfo$$b15
000181232 7001_ $$00000-0002-4463-3315$$aEbert, Natalie$$b16
000181232 7001_ $$00000-0003-3823-0920$$aEckardt, Kai Uwe$$b17
000181232 7001_ $$aGansevoort, Ron T$$b18
000181232 7001_ $$aGutierrez, Orlando$$b19
000181232 7001_ $$aHadaegh, Farzad$$b20
000181232 7001_ $$00000-0002-8286-9652$$aHe, Jiang$$b21
000181232 7001_ $$00000-0002-2129-5704$$aHwang, Shih Jen$$b22
000181232 7001_ $$aJafar, Tazeen H$$b23
000181232 7001_ $$aJassal, Simerjot K$$b24
000181232 7001_ $$aKayama, Takamasa$$b25
000181232 7001_ $$aKovesdy, Csaba P$$b26
000181232 7001_ $$aLandman, Gijs W$$b27
000181232 7001_ $$aLevey, Andrew S$$b28
000181232 7001_ $$aLloyd-Jones, Donald M$$b29
000181232 7001_ $$aMajor, Rupert W$$b30
000181232 7001_ $$00000-0002-2646-9582$$aMiura, Katsuyuki$$b31
000181232 7001_ $$aMuntner, Paul$$b32
000181232 7001_ $$aNadkarni, Girish N$$b33
000181232 7001_ $$00000-0001-8435-3978$$aNowak, Christoph$$b34
000181232 7001_ $$aOhkubo, Takayoshi$$b35
000181232 7001_ $$aPena, Michelle J$$b36
000181232 7001_ $$aPolkinghorne, Kevan R$$b37
000181232 7001_ $$aSairenchi, Toshimi$$b38
000181232 7001_ $$aSchaeffner, Elke$$b39
000181232 7001_ $$aSchneider, Markus P$$b40
000181232 7001_ $$aShalev, Varda$$b41
000181232 7001_ $$aShlipak, Michael G$$b42
000181232 7001_ $$00000-0002-4331-7548$$aSolbu, Marit D$$b43
000181232 7001_ $$aStempniewicz, Nikita$$b44
000181232 7001_ $$00000-0002-9825-701X$$aTollitt, James$$b45
000181232 7001_ $$aValdivielso, José M$$b46
000181232 7001_ $$avan der Leeuw, Joep$$b47
000181232 7001_ $$aWang, Angela Yee Moon$$b48
000181232 7001_ $$aWen, Chi Pang$$b49
000181232 7001_ $$aWoodward, Mark$$b50
000181232 7001_ $$aYamagishi, Kazumasa$$b51
000181232 7001_ $$aYatsuya, Hiroshi$$b52
000181232 7001_ $$aZhang, Luxia$$b53
000181232 7001_ $$00000-0002-0190-8526$$aDorresteijn, Jannick An$$b54
000181232 7001_ $$00000-0001-8776-6719$$aDi Angelantonio, Emanuele$$b55
000181232 7001_ $$aVisseren, Frank Lj$$b56
000181232 7001_ $$00000-0002-8594-3061$$aPennells, Lisa$$b57
000181232 7001_ $$aCoresh, Josef$$b58
000181232 7001_ $$aConsortium, Chronic Kidney Disease Prognosis$$b59$$eCollaboration Author
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