Paul E Drawz1, Nayanjot Kaur Rai1, Kristin Macfarlane Lenoir2, Maritza Suarez3, James R Powell4, Dominic S Raj5, Srinivasan Beddhu6, Anil K Agarwal7, Sandeep Soman8, Paul K Whelton9, James Lash10, Frederic F Rahbari-Oskoui11, Mirela Dobre12, Mark A Parkulo13, Michael V Rocco14, Andrew McWilliams15, Jamie P Dwyer16, George Thomas17, Mahboob Rahman18, Suzanne Oparil19, Edward Horwitz20, Nicholas M Pajewski2, Areef Ishani1,21. 1. Division of Renal Diseases and Hypertension, University of Minnesota Medical School, Minneapolis, Minnesota. 2. Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, North Carolina. 3. Department of Medicine, University of Miami Miller School of Medicine, Miami, Florida. 4. Division of General Internal Medicine, Brody School of Medicine, East Carolina University, Greenville, North Carolina. 5. Division of Kidney Diseases and Hypertension, George Washington University, Washington, DC. 6. Division of Nephrology and Hypertension, Department of Internal Medicine, University of Utah Health, Salt Lake City, Utah. 7. Department of Medicine, Veterans Affairs Central California Health Care System, Fresno, California. 8. Division of Nephrology and Hypertension, Henry Ford Hospital, Detroit, Michigan. 9. Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana. 10. Division of Nephrology, University of Illinois at Chicago, Chicago, Illinois. 11. Renal Division, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia. 12. Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, Ohio. 13. Department of Medicine, Division of Community Internal Medicine, Mayo Clinic, Jacksonville, Florida. 14. Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina. 15. Department of Internal Medicine and Center for Outcomes Research and Evaluation, Atrium Health, Charlotte, North Carolina. 16. Division of Nephrology & Hypertension, University of Utah Health, Salt Lake City, Utah. 17. Department of Kidney Medicine, Cleveland Clinic, Cleveland, Ohio. 18. Case Western Reserve University, University Hospitals Cleveland Medical Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, Ohio. 19. Department of Medicine, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama. 20. Case Western Reserve University, MetroHealth Medical Center, Cleveland, Ohio. 21. Minneapolis Veterans Affairs Health Care System, Minneapolis, Minnesota.
Abstract
Background: Adjudication of inpatient AKI in the Systolic Blood Pressure Intervention Trial (SPRINT) was based on billing codes and admission and discharge notes. The purpose of this study was to evaluate the effect of intensive versus standard BP control on creatinine-based inpatient and outpatient AKI, and whether AKI was associated with cardiovascular disease (CVD) and mortality. Methods: We linked electronic health record (EHR) data from 47 clinic sites with trial data to enable creatinine-based adjudication of AKI. Cox regression was used to evaluate the effect of intensive BP control on the incidence of AKI, and the relationship between incident AKI and CVD and all-cause mortality. Results: A total of 3644 participants had linked EHR data. A greater number of inpatient AKI events were identified using EHR data (187 on intensive versus 155 on standard treatment) as compared with serious adverse event (SAE) adjudication in the trial (95 on intensive versus 61 on standard treatment). Intensive treatment increased risk for SPRINT-adjudicated inpatient AKI (HR, 1.51; 95% CI, 1.09 to 2.08) and for creatinine-based outpatient AKI (HR, 1.40; 95% CI, 1.15 to 1.70), but not for creatinine-based inpatient AKI (HR, 1.20; 95% CI, 0.97 to 1.48). Irrespective of the definition (SAE or creatinine based), AKI was associated with increased risk for all-cause mortality, but only creatinine-based inpatient AKI was associated with increased risk for CVD. Conclusions: Creatinine-based ascertainment of AKI, enabled by EHR data, may be more sensitive and less biased than traditional SAE adjudication. Identifying ways to prevent AKI may reduce mortality further in the setting of intensive BP control.
Background: Adjudication of inpatient AKI in the Systolic Blood Pressure Intervention Trial (SPRINT) was based on billing codes and admission and discharge notes. The purpose of this study was to evaluate the effect of intensive versus standard BP control on creatinine-based inpatient and outpatient AKI, and whether AKI was associated with cardiovascular disease (CVD) and mortality. Methods: We linked electronic health record (EHR) data from 47 clinic sites with trial data to enable creatinine-based adjudication of AKI. Cox regression was used to evaluate the effect of intensive BP control on the incidence of AKI, and the relationship between incident AKI and CVD and all-cause mortality. Results: A total of 3644 participants had linked EHR data. A greater number of inpatient AKI events were identified using EHR data (187 on intensive versus 155 on standard treatment) as compared with serious adverse event (SAE) adjudication in the trial (95 on intensive versus 61 on standard treatment). Intensive treatment increased risk for SPRINT-adjudicated inpatient AKI (HR, 1.51; 95% CI, 1.09 to 2.08) and for creatinine-based outpatient AKI (HR, 1.40; 95% CI, 1.15 to 1.70), but not for creatinine-based inpatient AKI (HR, 1.20; 95% CI, 0.97 to 1.48). Irrespective of the definition (SAE or creatinine based), AKI was associated with increased risk for all-cause mortality, but only creatinine-based inpatient AKI was associated with increased risk for CVD. Conclusions: Creatinine-based ascertainment of AKI, enabled by EHR data, may be more sensitive and less biased than traditional SAE adjudication. Identifying ways to prevent AKI may reduce mortality further in the setting of intensive BP control.
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