The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Comparison of Risk Prediction Using the CKD-EPI Equation and the MDRD Study Equation for Estimated Glomerular Filtration Rate
Open accessAbstract
CONTEXT: The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation more accurately estimates glomerular filtration rate (GFR) than the Modification of Diet in Renal Disease (MDRD) Study equation using the same variables, especially at higher GFR, but definitive evidence of its risk implications in diverse settings is lacking. OBJECTIVE: To evaluate risk implications of estimated GFR using the CKD-EPI equation compared with the MDRD Study equation in populations with a broad range of demographic and clinical characteristics. DESIGN, SETTING, AND PARTICIPANTS: A meta-analysis of data from 1.1 million adults (aged ≥ 18 years) from 25 general population cohorts, 7 high-risk cohorts (of vascular disease), and 13 CKD cohorts. Data transfer and analyses were conducted between March 2011 and March 2012. MAIN OUTCOME MEASURES: All-cause mortality (84,482 deaths from 40 cohorts), cardiovascular mortality (22,176 events from 28 cohorts), and end-stage renal disease (ESRD) (7644 events from 21 cohorts) during 9.4 million person-years of follow-up; the median of mean follow-up time across cohorts was 7.4 years (interquartile range, 4.2-10.5 years). RESULTS: Estimated GFR was classified into 6 categories (≥90, 60-89, 45-59, 30-44, 15-29, and <15 mL/min/1.73 m(2)) by both equations. Compared with the MDRD Study equation, 24.4% and 0.6% of participants from general population cohorts were reclassified to a higher and lower estimated GFR category, respectively, by the CKD-EPI equation, and the prevalence of CKD stages 3 to 5 (estimated GFR <60 mL/min/1.73 m(2)) was reduced from 8.7% to 6.3%. In estimated GFR of 45 to 59 mL/min/1.73 m(2) by the MDRD Study equation, 34.7% of participants were reclassified to estimated GFR of 60 to 89 mL/min/1.73 m(2) by the CKD-EPI equation and had lower incidence rates (per 1000 person-years) for the outcomes of interest (9.9 vs 34.5 for all-cause mortality, 2.7 vs 13.0 for cardiovascular mortality, and 0.5 vs 0.8 for ESRD) compared with those not reclassified. The corresponding adjusted hazard ratios were 0.80 (95% CI, 0.74-0.86) for all-cause mortality, 0.73 (95% CI, 0.65-0.82) for cardiovascular mortality, and 0.49 (95% CI, 0.27-0.88) for ESRD. Similar findings were observed in other estimated GFR categories by the MDRD Study equation. Net reclassification improvement based on estimated GFR categories was significantly positive for all outcomes (range, 0.06-0.13; all P < .001). Net reclassification improvement was similarly positive in most subgroups defined by age (<65 years and ≥65 years), sex, race/ethnicity (white, Asian, and black), and presence or absence of diabetes and hypertension. The results in the high-risk and CKD cohorts were largely consistent with the general population cohorts. CONCLUSION: The CKD-EPI equation classified fewer individuals as having CKD and more accurately categorized the risk for mortality and ESRD than did the MDRD Study equation across a broad range of populations.
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Cites
A New Equation to Estimate Glomerular Filtration Rate
Levey, A. S., Stevens, L. A., Schmid, C. H., Zhang, Y. (., Castro, A. F., Feldman, H. I., Kusek, J. W., Eggers, P., Van Lente, F., Greene, T., et al. (2009) · Annals of Internal Medicine · doi:10.7326/0003-4819-150-9-200905050-00006 · Cited by 25,603
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Levey, A. S., de Jong, P. E., Coresh, J., El Nahas, M., Astor, B. C., Matsushita, K., Gansevoort, R. T., Kasiske, B. L., & Eckardt, K.-U. (2011) · Kidney International · doi:10.1038/ki.2010.483 · Cited by 2,345
Self-citationKlahr, S., Levey, A. S., Beck, G. J., Caggiula, A. W., Hunsicker, L., Kusek, J. W., & Striker, G. (1994) · New England Journal of Medicine · doi:10.1056/nejm199403313301301 · Cited by 2,328
Self-citationNoda, H., Iso, H., Irie, F., Sairenchi, T., Ohtaka, E., Doi, M., Izumi, Y., & Ohta, H. (2009) · Circulation · doi:10.1161/circulationaha.108.795666 · Cited by 150
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European Guidelines on cardiovascular disease prevention in clinical practice (version 2012)
Authors/Task Force Members:, Perk, J., De Backer, G., Gohlke, H., Graham, I., Reiner, Ž., Verschuren, M., Albus, C., Benlian, P., Boysen, G., et al. (2012) · European Heart Journal · doi:10.1093/eurheartj/ehs092 · Cited by 8,490
2016 European Guidelines on cardiovascular disease prevention in clinical practice
Piepoli, M. F., Hoes, A. W., Agewall, S., Albus, C., Brotons, C., Catapano, A. L., Cooney, M.-T., Corrà, U., Cosyns, B., Deaton, C., et al. (2016) · European Heart Journal · doi:10.1093/eurheartj/ehw106 · Cited by 6,457
Mancia, G., Fagard, R., Narkiewicz, K., Redón, J., Zanchetti, A., Böhm, M., Christiaens, T., Cifkova, R., De Backer, G., Dominiczak, A., et al. (2013) · Journal of Hypertension · doi:10.1097/01.hjh.0000431740.32696.cc · Cited by 5,655
Webster, A. C., Nagler, E. V., Morton, R. L., & Masson, P. (2017) · The Lancet · doi:10.1016/s0140-6736(16)32064-5 · Cited by 3,842
Mancia, G., Kreutz, R., Brunström, M., Burnier, M., Grassi, G., Januszewicz, A., Muiesan, M. L., Tsioufis, K., Agabiti-Rosei, E., Algharably, E. A. E., et al. (2023) · Journal of Hypertension · doi:10.1097/hjh.0000000000003480 · Cited by 3,473
Metadata
- Authors
- Matsushita, K., Mahmoodi, B. K., Woodward, M., Emberson, J. R., Jafar, T. H., Jee, S. H., Polkinghorne, K. R., Shankar, A., Smith, D. H., Tonelli, M., Warnock, D. G., Wen, C.-P., Coresh, J., Gansevoort, R. T., Hemmelgarn, B. R., Levey, A. S., & Chronic Kidney Disease Prognosis Consortium, F. T.
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2012-05-09
- Volume
- 307
- Issue
- 18
- Pages
- 1941-51
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- OpenAlex
- W2081231656
- Cited by
- 988
- References
- 5
- FWCI
- 67.27
- Type
- journal article
- Language
- en
- Open access
- green
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