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Kidney Medicine Journal
May 14, 2023

Individualization of Serum-to-Dialysate Potassium Concentrations to Reduce the Risk of Sudden Cardiac Death Conferred by QT-Prolonging Antibiotics in Patients Receiving Hemodialysis

Jonathan S Chávez-Iñiguez, Jochen G Raimann

No abstract available

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About the Author

Jochen G. Raimann, MD, PhD, MPH

Director, Data Analytics

Jochen has worked as a full-time scientist at RRI since his start as a postdoctoral research fellow in 2007. As Senior Manager of Clinical Data Analytics, Jochen conducts epidemiological research in dialysis and oversees many analytical projects. He has first- and co-authored numerous papers and also serves as Associate Editor of the journals Trials and Scientific Reports. ochen earned his MD from the Medical University Graz, his PhD from Maastricht University, and his MPH with a focus on epidemiology and biostatistics from the City University of New York School of Public Health.

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    May 11, 2023

    Inclement Weather and Risk of Missing Scheduled Hemodialysis...

    Richard V Remigio, Jochen G Raimann, Peter Kotanko...
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  • Kidney360
    May 04, 2023

    Dynamics of Plasma Refill Rate and Intradialytic Hypotension...

    Hanjie Zhang, Sabrina Casper, Peter Kotanko, Joche...
    Abstract Background: Attaining the optimal balance between achieving adequate volume removal while preserving organ perfusion is a challenge for patients receiving maintenance hemodialysis. Current strategies to guide ultrafiltration are inadequate. Methods: We developed an approach to calculate plasma refill rate throughout hemodialysis using hematocrit and ultrafiltration data in a retrospective cohort of patients receiving maintenance hemodialysis at...
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    Apr 19, 2023

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    null, Xiaoling Ye, Yuedong Wang, Len A Usvyat, Fra...
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    Jan 27, 2023

    Artificial Intelligence and Machine Learning in Dialysis: Re...

    Peter Kotanko, Hanjie Zhang, Yuedong Wang
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    Nov 20, 2022

    Predicting mortality risk in dialysis: Assessment of risk fa...

    Sheetal Chaudhuri, John W Larkin, Murilo Guedes, Y...
    Abstract Introduction: Several factors affect the survival of End Stage Kidney Disease (ESKD) patients on dialysis. Machine learning (ML) models may help tackle multivariable and complex, often non-linear predictors of adverse clinical events in ESKD patients. In this study, we used advanced ML method as well as a traditional statistical method to develop and compare the...