Lesley A Inker1, Morgan E Grams2, Andrew S Levey1, Josef Coresh3, Massimo Cirillo4, John F Collins5, Ron T Gansevoort6, Orlando M Gutierrez7, Takayuki Hamano8, Gunnar H Heine9, Shizukiyo Ishikawa10, Sun Ha Jee11, Florian Kronenberg12, Martin J Landray13, Katsuyuki Miura14, Girish N Nadkarni15, Carmen A Peralta16, Dietrich Rothenbacher17, Elke Schaeffner18, Sanaz Sedaghat19, Michael G Shlipak16, Luxia Zhang20, Arjan D van Zuilen21, Stein I Hallan22, Csaba P Kovesdy23, Mark Woodward24, Adeera Levin25. 1. Division of Nephrology, Tufts Medical Center, Boston, MA. 2. Johns Hopkins Bloomberg School of Public Health, Baltimore, MD. 3. Johns Hopkins Bloomberg School of Public Health, Baltimore, MD. Electronic address: ckdpc@jhmi.edu. 4. Department "Scuola Medica Salernitana", University of Salerno, Italy. 5. Department of Renal Medicine, Auckland City Hospital, Auckland, New Zealand. 6. Department of Nephrology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands. 7. Division of Nephrology, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL; Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL. 8. Department of Comprehensive Kidney Disease Research, Osaka University Graduate School of Medicine, Osaka, Japan. 9. Department for Internal Medicine IV, Nephrology and Hypertension, Saarland University Medical Center, Homburg, Germany. 10. Division of Community and Family Medicine, Center for Community Medicine, Jichi Medical University, Tochigi, Japan. 11. Department of Epidemiology and Health Promotion, Graduate School of Public Health, Yonsei University, Seoul, Korea. 12. Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Medical University of Innsbruck, Innsbruck, Austria and German Chronic Kidney Disease Study, Oxford, United Kingdom. 13. Medical Research Council-Population Health Research Unit, Clinical Trial Service Unit and Epidemiological Studies Unit, and Big Data Institute, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom. 14. Department of Public Health and Center for Epidemiologic Research in Asia, Shiga University of Medical Science, Otsu, Japan. 15. Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY. 16. Kidney Health Research Collaborative, San Francisco VA Medical Center and University of California, San Francisco, CA. 17. Division of Clinical Epidemiology and Ageing Research, German Cancer Centre (DKFZ), Heidelberg; Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany. 18. Institute of Public Health, Charite, Universitätsmedizin Berlin. 19. Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands. 20. Peking University Institute of Nephrology, Division of Nephrology, Peking University First Hospital, Beijing, China. 21. Department of Nephrology and Hypertension, University Medical Center Utrecht, Utrecht, the Netherlands. 22. Department of Clinical and Molecular Medicine, Faculty of Medicine, Norwegian University of Science Technology, Trondheim, Norway; Division of Nephrology, Department of Medicine, St Olav University Hospital, Trondheim, Norway. 23. Memphis Veterans Affairs Medical Center, Memphis, TN; University of Tennessee Health Science Center, Memphis, TN. 24. Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; The George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia; The George Institute for Global Health, University of Oxford, Oxford, United Kingdom. 25. BC Provincial Renal Agency and University of British Columbia, Canada.
Abstract
RATIONALE & OBJECTIVE: Chronic kidney disease (CKD) is complicated by abnormalities that reflect disruption in filtration, tubular, and endocrine functions of the kidney. Our aim was to explore the relationship of specific laboratory result abnormalities and hypertension with the estimated glomerular filtration rate (eGFR) and albuminuria CKD staging framework. STUDY DESIGN: Cross-sectional individual participant-level analyses in a global consortium. SETTING & STUDY POPULATIONS: 17 CKD and 38 general population and high-risk cohorts. SELECTION CRITERIA FOR STUDIES: Cohorts in the CKD Prognosis Consortium with data for eGFR and albuminuria, as well as a measurement of hemoglobin, bicarbonate, phosphorus, parathyroid hormone, potassium, or calcium, or hypertension. DATA EXTRACTION: Data were obtained and analyzed between July 2015 and January 2018. ANALYTICAL APPROACH: We modeled the association of eGFR and albuminuria with hemoglobin, bicarbonate, phosphorus, parathyroid hormone, potassium, and calcium values using linear regression and with hypertension and categorical definitions of each abnormality using logistic regression. Results were pooled using random-effects meta-analyses. RESULTS: The CKD cohorts (n=254,666 participants) were 27% women and 10% black, with a mean age of 69 (SD, 12) years. The general population/high-risk cohorts (n=1,758,334) were 50% women and 2% black, with a mean age of 50 (16) years. There was a strong graded association between lower eGFR and all laboratory result abnormalities (ORs ranging from 3.27 [95% CI, 2.68-3.97] to 8.91 [95% CI, 7.22-10.99] comparing eGFRs of 15 to 29 with eGFRs of 45 to 59mL/min/1.73m2), whereas albuminuria had equivocal or weak associations with abnormalities (ORs ranging from 0.77 [95% CI, 0.60-0.99] to 1.92 [95% CI, 1.65-2.24] comparing urinary albumin-creatinine ratio > 300 vs < 30mg/g). LIMITATIONS: Variations in study era, health care delivery system, typical diet, and laboratory assays. CONCLUSIONS: Lower eGFR was strongly associated with higher odds of multiple laboratory result abnormalities. Knowledge of risk associations might help guide management in the heterogeneous group of patients with CKD.
RATIONALE & OBJECTIVE: Chronic kidney disease (CKD) is complicated by abnormalities that reflect disruption in filtration, tubular, and endocrine functions of the kidney. Our aim was to explore the relationship of specific laboratory result abnormalities and hypertension with the estimated glomerular filtration rate (eGFR) and albuminuria CKD staging framework. STUDY DESIGN: Cross-sectional individual participant-level analyses in a global consortium. SETTING & STUDY POPULATIONS: 17 CKD and 38 general population and high-risk cohorts. SELECTION CRITERIA FOR STUDIES: Cohorts in the CKD Prognosis Consortium with data for eGFR and albuminuria, as well as a measurement of hemoglobin, bicarbonate, phosphorus, parathyroid hormone, potassium, or calcium, or hypertension. DATA EXTRACTION: Data were obtained and analyzed between July 2015 and January 2018. ANALYTICAL APPROACH: We modeled the association of eGFR and albuminuria with hemoglobin, bicarbonate, phosphorus, parathyroid hormone, potassium, and calcium values using linear regression and with hypertension and categorical definitions of each abnormality using logistic regression. Results were pooled using random-effects meta-analyses. RESULTS: The CKD cohorts (n=254,666 participants) were 27% women and 10% black, with a mean age of 69 (SD, 12) years. The general population/high-risk cohorts (n=1,758,334) were 50% women and 2% black, with a mean age of 50 (16) years. There was a strong graded association between lower eGFR and all laboratory result abnormalities (ORs ranging from 3.27 [95% CI, 2.68-3.97] to 8.91 [95% CI, 7.22-10.99] comparing eGFRs of 15 to 29 with eGFRs of 45 to 59mL/min/1.73m2), whereas albuminuria had equivocal or weak associations with abnormalities (ORs ranging from 0.77 [95% CI, 0.60-0.99] to 1.92 [95% CI, 1.65-2.24] comparing urinary albumin-creatinine ratio > 300 vs < 30mg/g). LIMITATIONS: Variations in study era, health care delivery system, typical diet, and laboratory assays. CONCLUSIONS: Lower eGFR was strongly associated with higher odds of multiple laboratory result abnormalities. Knowledge of risk associations might help guide management in the heterogeneous group of patients with CKD.
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