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

• Main Authors: Matsushita, K., Jassal, S.K., Sang, Y., Ballew, S.H., Grams, M.E., Surapaneni, A., Arnlov, J., Bansal, N., Bozic, M., Brenner, H., Brunskill, N.J., Chang, A.R., Chinnadurai, R., Cirillo, M., Correa, A., Ebert, N., Eckardt, K.-U., Gansevoort, R.T., Gutierrez, O., Hadaegh, F., He, J., Hwang, S.-J., Jafar, T.H., Kayama, T., Kovesdy, C.P., Landman, G.W., Levey, A.S., Lloyd-Jones, D.M., Major, R.W., Miura, K., Muntner, P., Nadkarni, G.N., Naimark, D.M., Nowak, C., Ohkubo, T., Pena, M.J., Polkinghorne, K.R., Sabanayagam, C., Sairenchi, T., Schneider, M.P., Shalev, V., Shlipak, M., Solbu, M.D., Stempniewicz, N., Tollitt, J., Valdivielso, J.M., van der Leeuw, J., Wang, A.Y.-M., Wen, C.-P., Woodward, M., Yamagishi, K., Yatsuya, H., Zhang, L., Schaeffner, E., Coresh, J.
• Other Authors: DUKE-NUS MEDICAL SCHOOL
• Format: Article
• Published: Lancet Publishing Group 2021
• Subjects: cardiovascular disease; Chronic kidney disease; meta-analysis; risk prediction
• Online Access: https://scholarbank.nus.edu.sg/handle/10635/197437
• Institution: National University of Singapore

10.1016/j.eclinm.2020.100552