Citations 2
Transforming nephrology through artificial intelligence: a state-of-the-art roadmap for clinical integration
Cheungpasitporn, W., Athavale, Ambarish M., Ghazi, Lama , Kashani, Kianoush B, Colicchio, Tiago K. , Koyner, Jay L. , Chen, Jin , Ix, Joachim H, Nadkarni, Girish N. , Neyra, Javier A., Kashani, Kianoush , Cheungpasitporn, Wisit , Kashani, Kianoush B , Colicchio, Tiago , Neyra, Javier A , Koyner, Jay L , Ghazi, Lama , Cheungpasitporn, Wisit , Ix, Joachim H. , Neyra, Javier A.
Clinical Kidney Journal | January 7, 2026 | Volume: 19 | Issue: 2 | Pages: No page available
ABSTRACT Artificial intelligence (AI), encompassing machine learning, deep learning and generative AI, is poised to redefine nephrology by enabling earlier detection, more precise risk stratification and workflow-integrated clinical decision support across the spectrum of kidney disease. This state-of-the-art review synthesizes emerging applications of AI in acute kidney injury (AKI), chronic kidney disease (CKD), dialysis and kidney transplantation, with attention to clinical integration, real-world validation, workflow implementation and translational challenges. In AKI, predictive models trained on high-frequency electronic health record data and intensive care unit telemetry have demonstrated strong performance in forecasting critical events, yet translation into routine clinical workflows remains limited. In CKD, machine learning tools support progression risk stratification and phenotype clustering, with the potential to inform individualized surveillance and therapy. AI-enabled dialysis management systems optimize ultrafiltration, anemia control and vascular access surveillance, while generative AI and large language models offer novel capabilities for clinical documentation, triage and patient education. In transplantation, AI applications span organ allocation, dynamic graft monitoring and digital pathology-assisted rejection classification, with validated tools such as the iBox system gaining regulatory recognition. Implementation challenges include data heterogeneity, bias, interpretability, regulatory uncertainty and workflow integration. Looking ahead, multimodal integration of imaging, pathology and multi-omics data may support biologically informed precision nephrology. Reinforcement learning, digital twins and ambient intelligence are emerging as adaptive decision-support paradigms rather than autonomous care systems. Regulatory frameworks are evolving to accommodate adaptive algorithms, underscoring the need for clinician engagement in model development, validation and deployment. As AI matures from pilot to practice, nephrologists who embrace and help shape these tools will lead the transition toward a more personalized, efficient and equitable future for kidney care.
The longitudinal relationship between patient-reported outcomes and clinical characteristics among patients with focal segmental glomerulosclerosis in the Nephrotic Syndrome Study Network
Troost, Jonathan P. , Waldo, Anne, Carlozzi, Noelle E. , Murphy, Shannon L., Modersitzki, Frank , Trachtman, Howard , Nachman, Patrick H. , Reidy, Kimberly J. , Selewski, David T. , Herreshoff, Emily, Srivastava, Tarak, Gibson, Keisha L. , Derebail, Vimal K. , Lin, Jen Jar, Hingorani, Sangeeta, Sambandam, Kamalanathan K. , Athavale, Ambarish M., Reich, Heather N. , Adler, Sharon G. , Dell, Katherine M., Appel, Gerald B., Wang, Chia-shi , Kaskel, Frederick J. , Lafayette, Richard , Atkinson, Meredith A. , Kretzler, Matthias , Lemley, Kevin V. , Brown, Elizabeth , Meyers, Kevin , Gadegbeku, Crystal A., Holzman, Lawrence B. , Jefferson, Jonathan Ashley, Tuttle, Katherine R, Singer, Pamela, Hogan, Marie C. , Cattran, Daniel C., Network, the Nephrotic Syndrome Study, Dell, K, Schachere, M., Lemley, K, Whitted, L, Haney, Connie J, Gurusinghe, Sayuri , Toledo, Michelly Louise Sartório Altoé, Greenbaum, L, Wang, C, Lee, B, Nast, Cynthia C. , Page, J La, Stroger, John H, Itteera, M. , Neu, Alicia M. , Boynton, Sara Ashley, Chernitskiy, Vladimir, Reidy, K, Kopp, J, Castro-Rubio, E, Brede, E, Blake, J. Thomas, Modersitzki, F, Lafayette, R, Mehta, K. , Johnstone, Duncan B., Pfeffer, Zoe, Cattran, D, Hladunewich, M, Reich, H, Ling, P., Romano, M, Barisoni, L, Bidot, Carlos, Kretzler, M, Williams, A, Pitter, R, Gibson, K, Grubbs, S, Froment, Anne, Holzman, L, Kallem, K., Cerecino, F J, Johnson, N, Jefferson, A, Tuttle, Katherine R. , Klepach, K, Kelton, M, Cooper, Ann , Lin, J J, Spainhour, Mitzie, Gray, S, Barisoni, L, Gillespie, B, Gipson, D, Holzman, L, Mariani, Laura , Song, Peter X.‐K. , Kincaid, Colleen, Lienczewski, Chrysta, Mainieri, T, Williams, Anna , Ávila-Casado, Carmen , Bagnasco, Serena M. , Gaut, Joseph P. , Hewitt, Stephen M. , Palmer, M, Rosenberg, A, Royal, Virginie , Barisoni, L, Nast, C, Roy, Cindy N., Urv, T, Dell, K, Greenbaum, L, Lee, B, Page, J La, Stroger, John H, Reidy, K, Kopp, J, Brede, E, Modersitzki, F, Lafayette, R, Gadegbeku, C, Cattran, D, Hladunewich, M, Reich, H, Romano, M, Pitter, R, Gibson, K, Cerecino, F J, Jefferson, A, Lin, J J, Gray, S, Kretzler, M, Gillespie, B, Gipson, D, Mariani, L, Mainieri, T, Williams, A, Mariani, L, Palmer, M, Rosenberg, A, Barisoni, L, Urv, T, Wang, Chia-Shi , Tuttle, Katherine R , Hogan, Marie C , Fornoni, Alessia , Fervenza, Fernando C. , Kopp, Jeffrey B. , Greenbaum, Larry A. , Sedor, John R. , Lieske, John C. , Srivastava, Tarak , Hladunewich, Michelle , Tuttle, Katherine R, Singer, Pamela S. , Barisoni, Laura , Gipson, Debbie S , Network, the Nephrotic Syndrome Study, Dell, K, Lemley, K, Greenbaum, L, Lee, B, Page, J La, Stroger, John H, Reidy, K, Kopp, J, Brede, E, Zhdanova, Olga A. , Modersitzki, F, Vento, Sandro , Lafayette, R, Cattran, D, Hladunewich, M, Reich, H, Romano, M, Barisoni, L, Bidot, C, Kretzler, M, Williams, A, Pitter, R, Gibson, K, Holzman, L, Cerecino, F J, Jefferson, A, Freedman, Barry I. , Lin, J J, Gray, S, Barisoni, L, Gillespie, B, Gipson, D, Holzman, L, Sampson, Matthew Gordon , Zee, Jarcy , Mainieri, T, Hodgin, Jeffrey B. , Palmer, M, Rosenberg, A, Thomas, D, Barisoni, L, Nast, C, Abbott, Kevin C. , Roy, C, Urv, T, Brooks, Philip John , Dell, K, Greenbaum, L, Lee, B, Page, J La, Stroger, John H, Reidy, K, Kopp, J, Brede, E, Modersitzki, F, Lafayette, R, Gadegbeku, C, Cattran, D, Hladunewich, M, Reich, H, Romano, M, Bidot, C, Pitter, R, Gibson, K, Cerecino, F J, Jefferson, A, Lin, J J, Gray, S, Kretzler, M, Gillespie, B, Gipson, D, Mariani, L, Mainieri, T, Williams, A, Mariani, L, Palmer, M, Rosenberg, A, Thomas, D, Barisoni, L, Roy, C, Urv, T, Troost, Jonathan P.
Clinical Kidney Journal | July 3, 2019 | Volume: 13 | Issue: 4 | Pages: 597-606
Abstract Background Understanding the relationship between clinical and patient-reported outcomes (PROs) will help support clinical care and future clinical trial design of novel therapies for focal segmental glomerulosclerosis (FSGS). Methods FSGS patients ≥8 years of age enrolled in the Nephrotic Syndrome Study Network completed Patient-Reported Outcomes Measurement Information System PRO measures of health-related quality of life (HRQoL) (children: global health, mobility, fatigue, pain interference, depression, anxiety, stress and peer relationships; adults: physical functioning, fatigue, pain interference, sleep impairment, mental health, depression, anxiety and social satisfaction) at baseline and during longitudinal follow-up for a maximum of 5 years. Linear mixed-effects models were used to determine which demographic, clinical and laboratory features were associated with PROs for each of the eight children and eight adults studied. Results There were 45 children and 114 adult FSGS patients enrolled that had at least one PRO assessment and 519 patient visits. Multivariable analyses among children found that edema was associated with global health (−7.6 points, P = 0.02) and mobility (−4.2, P = 0.02), the number of reported symptoms was associated with worse depression (−2.7 per symptom, P = 0.009) and anxiety (−2.3, P = 0.02) and the number of emergency room (ER) visits in the prior 6 months was associated with worse mobility (−2.8 per visit, P < 0.001) and fatigue (−2.4, P = 0.03). Multivariable analyses among adults found the number of reported symptoms was associated with worse function in all eight PROMIS measures and the number of ER visits was associated with worse fatigue, pain interference, sleep impairment, depression, anxiety and social satisfaction. Laboratory markers of disease severity (i.e. proteinuria, estimated glomerular filtration rate and serum albumin) did not predict PRO in multivariable analyses, with the single exception of complete remission and better pain interference scores among children (+9.3, P = 0.03). Conclusions PROs provide important information about HRQoL for persons with FSGS that is not captured solely by the examination of laboratory-based markers of disease. However, it is critical that instruments capture the patient experience and FSGS clinical trials may benefit from a disease-specific instrument more sensitive to within-patient changes.