Data from: Development and validation of prediction models of adverse kidney outcomes in the population with and without diabetes mellitus

  • Morgan E Grams (Creator)
  • Nigel J Brunskill (Creator)
  • Shoshana H Ballew (Creator)
  • Yingying Sang (Creator)
  • Josef Coresh (Creator)
  • Kunihiro Matsushita (Creator)
  • Simon Sawhney (Creator)

Dataset

Description

Objective: To predict adverse kidney outcomes for use in optimizing medical management and clinical trial design.

Data type

Figshare dataset

Copyright and Open Data Licencing

CC BY-NC-SA 4.0
Date made available2022
PublisherUniversity of Aberdeen

Contact

  • Development and Validation of Prediction Models of Adverse Kidney Outcomes in the Population With and Without Diabetes Mellitus

    Grams, M. E. (Corresponding Author), Brunskill, N. J., Ballew, S. H., Sang, Y., Coresh, J. (Corresponding Author), Matsushita, K., Surapaneni, A., Bell, S., Carrero, J. J., Chodick, G., Evans, M., Heerspink, H. J. L., Inker, L. A., Iseki, K., Kalra, P. A., Kirchner, H. L., Lee, B. J., Levin, A., Major, R. W. & Medcalf, J. & 17 others, Nadkarni, G. N., Naimark, D. M. J., Ricardo, A. C., Sawhney, S., Sood, M. M., Staplin, N., Stempniewicz, N., Stengel, B., Sumida, K., Traynor, J. P., van den Brand, J., Wen, C.-P., Woodward, M., Yang, J. W., Wang, A.Y.-M., Tangri, N. & CKD Prognosis Consortium, 1 Sept 2022, In: Diabetes Care. 45, 9, p. 2055-2063 8 p.

    Research output: Contribution to journal › Article › peer-review

    20 Citations (Scopus)

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