• Incorporating kidney disease measures into cardiovascular risk prediction: Development and validation in 9 million adults from 72 datasets 

      Matsushita, K; Jassal, Simerjot; Solbu, Marit Dahl; Sang, Yingying; Ballew, Shoshana H.; Grams, Morgan E.; Surapaneni, Aditya; Arnlov, Johan; Bansal, Nisha; Bozic, Milica; Brenner, Hermann; Brunskill, Nigel J.; Chang, Alex R.; Chinnadurai, Rajkumar; Cirillo, Massimo; Correa, Adolfo; Ebert, Natalie; Eckardt, Kai-Uwe; Gansevoort, Ron T.; Gutierrez, Orlando; Hadaegh, Farzad; He, Jiang; Hwang, Shih-Jen; Jafar, Tazeen H.; Kayama, Takamasa; Kovesdy, Csaba P.; Landman, Gijs W.; Levey, Andrew S.; Lloyd-Jones, Donald M.; Major, Rupert W.; Miura, Katsuyuki; Muntner, Paul; Nadkarni, Girish N.; Naimark, David M.J.; Nowak, Christoph; Ohkubo, Takayoshi; Pena, Michelle J.; Polkinghorne, Kevan R.; Sabanayagam, Charumathi; Sairenchi, Toshimi; Schneider, Markus P.; Shalev, Varda; Shlipak, Michael; Stempniewicz, Nikita; Tollitt, James; Valdivielso, José M.; van der Leeuw, Joep; Wang, Angela Yee-Moon; Wen, Chi-Pang; Woodward, Mark; Yatsuya, Hiroshi; Zhang, Luxia; Schaeffner, Elke; Coresh, Josef (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-10-04)
      Background: Chronic kidney disease (CKD) measures (estimated glomerular filtration rate [eGFR] and albuminuria) are frequently assessed in clinical practice and improve the prediction of incident cardiovascular disease (CVD), yet most major clinical guidelines do not have a standardized approach for incorporating these measures into CVD risk prediction. “CKD Patch” is a validated method to calibrate ...