Información de la revista
Vol. 33. Núm. 2.Marzo 2013
Páginas 0-288
Compartir
Compartir
Descargar PDF
Más opciones de artículo
Vol. 33. Núm. 2.Marzo 2013
Páginas 0-288
Acceso a texto completo
Estrategia para estimar la progresión del riesgo de la enfermedad renal crónica, del riesgo cardiovascular y la remisión a nefrología: el estudio EPIRCE
Strategy to estimate risk progression of chronic kidney disease, cardiovascular risk, and referral to nephrology: the EPIRCE Study
Visitas
...
Pilar Gayoso-Diza, Alfonso Otero-Gonzálezb, Alfonso Otero-Gonzalezc, M. Xosé Rodríguez-Álvarezd, Maria Xose Rodriguez-Alvareze, Fernando Garcíaf, Fernando Garciag, Arturo González-Quintelah, Arturo Gonzalez-Quintelai, Ángel M. de Franciscoj, Angel M De Franciscok
a Unidad de Epidemiolog??a Cl??nica, CHU de Santiago, Santiago de Compostela, A Coru??a, Espa??a,
b Servicio de Nefrolog??a, Complexo Hospitalario Universitario de Ourense, Ourense, Spain,
c NEFROLOG??A, CHU de Ourense, Ourense, Ourense, Espa??a,
d Unidad de Epidemiolog??a Cl??nica, Complexo Hospitalario Universitario de Santiago, Santiago de Compostela, A Coru??a, Spain,
e Unidad Epidemiologia Clinica, CHU de Santiago, Santiago de Compostela, A Coru??a, Espa??a,
f Servicio de Nefrolog??a, Hospital Universitario Puerta de Hierro, Madrid, Spain,
g NEFROLOGIA, H. U. Puerta de Hierro, Madrid, Madrid, Espa??a,
h Servicio de Medicina Interna, Complexo Hospitalario Universitario de Santiago, Santiago de Compostela, A Coru??a, Spain,
i Medicina Interna, CHU de Santiago, Santiago de Compostela, A Coru??a, Espa??a,
j Servicio de Nefrolog??a, Hospital Universitario Marqu??s de Valdecilla, Santander, Spain,
k NEFROLOG??A, HU Valdecilla., Santander, Santander, Espa??a,
Información del artículo

Antecedentes: Si bien la prevalencia de la enfermedad renal crónica (ERC) es del 10-14 %, diversos estudios prospectivos indican que en las fases 3 y 4 existe una tasa baja de progresión hacia enfermedad renal terminal (ERT). Una clasificación correcta del riesgo de progresión basada en factores predictivos demostrados permitiría un mejor manejo de la ERC. Estudios recientes han demostrado el elevado valor predictivo de la clasificación que combina el valor estimado (e) de la tasa de filtrado glomerular (FG) con la ratio albúmina-creatinina (RAC) en orina. Realizamos una estimación del riesgo clínico de una progresión hacia una ERT y de mortalidad cardiovascular existente en la población general española basando la predicción en el uso combinado de las variables tasa (e) de FG y RAC. Materiales y métodos: Evaluación cruzada en la muestra Epirce, que era representativa de la población española mayor de 20 años. Para la estimación del FG se emplearon las fórmulas MDRD y CKD-EPI; se consideraba la existencia de microalbuminuria cuando los valores de RAC oscilaban entre 20-200 mg/g (hombres) o entre 30-300 mg/g (mujeres) y de macroalbuminuria cuando los valores superaban dichos límites. Se realizó una estimación de la prevalencia ponderada poblacionalmente del riesgo de progresión de ERC hacia ERT. Resultados: Con MDRD, el 1,4 % de la población adulta española presentaba un riesgo moderado de evolución hacia ERT; el 0,1 % un riesgo elevado y el 12,3 % un riesgo bajo. Con CKD-EPI, la tasa de riesgo moderado se elevaba hasta 1,7 % y la de riesgo bajo hasta 12,6 %; sin embargo, la tasa de riesgo elevado se mantenía estable. Conclusiones: La adición de la RAC a la tasa (e) de FG permite una mejor clasificación de la población en riesgo de deterioro renal relacionado con el Kidney/Disease Outcomes Quality Initiative, grados 3 y 4. La estimación de la tasa de FG mediante CKD-EPI modifica la distribución existente para el riesgo bajo y moderado.

Palabras clave:
Albuminuria
Palabras clave:
Pronóstico
Palabras clave:
Epidemiología
Palabras clave:
Enfermedad renal crónica
Palabras clave:
Clasificación del riesgo cardiovascular

Background: Although the prevalence of chronic kidney disease (CKD) is 10–14%, several prospective studies note a low rate of progression to end-stage renal disease (ESRD) in stages 3 and 4. A correct classification of risk of progression, based on demonstrated predictive factors, would allow better management of CKD. Recent studies have demonstrated the high predictive value of a classification that combines estimated (e) glomerular filtration rate (GFR) and urine albumin–creatinine ratio (ACR). We estimated the clinical risk of progression to ESRD and cardiovascular mortality predicted by the combined variable of eGFR and ACR in the Spanish general population. Materials and Methods: This study was a cross-sectional evaluation in the Epirce sample, representative of Spanish population older than 20 years. GFR was estimated using MDRD and CKD-EPI formulas; microalbuminuria was considered to be an ACR 20–200 mg/g (men) or 30–300 mg/g (women) and macroalbuminuria was indicated beyond these limits. Population-weighted prevalence of risk of progression of CKD to ESRD was estimated. Results: With MDRD, 1.4% of the adult Spanish population was at moderate risk of progression to ESRD, 0.1% at high risk, and 12.3% at low risk. With CKD-EPI, the moderate risk ratio rose to 1.7% and low risk to 12.6%, but high risk remained stable. Conclusions: The addition of ACR to eGFR best classifies the population at risk for renal impairment relative to Kidney/Disease Outcomes Quality Initiative grades 3 and 4. Estimating GFR with CKD-EPI modifies the distribution of low and moderate risk.

Keywords:
Albuminuria
Keywords:
Prognosis
Keywords:
Epidemiology
Keywords:
Chronic kidney disease
Keywords:
Cardiovascular risk classification
El Texto completo está disponible en PDF
Bibliografía
[1]
Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY.Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. N Engl J Med 2004;351:1296-305. [Pubmed]
[2]
Lysagrht MJ. Maintenance dialysis population dynamics: currents trends and long-term implications. Am Soc Nephrol 2002;13:37-40.
[3]
Coresh J, Astor BC, Greene T, Eknoyan G, Levey AS. Prevalence of chronic kidney disease and decreased kidney function in the adult US population: Third National Health and Nutrition Examination Survey. Am J Kidney Dis 2003;41:1-12. [Pubmed]
[4]
Cirillo M, Laurenzi M, Mancini M, Zanchetti A, Lombardi C, De Santo NG. Low glomerular filtration in the population: prevalence, associated disorders, and awareness. Kidney Int 2006;70:800-6. [Pubmed]
[5]
Keith DS, Nichols GA, Gullion CM, Brown JB, Smith DH. Longitudinal follow-up and outcomes among a population with chronic kidney disease in a large managed care organization. Arch Intern Med 2004;164:659-63. [Pubmed]
[6]
Sarnak MJ, Levey AS, Schoolwerth AC, Coresh J, Culleton B, Hamm LL, et al. Kidney disease as a risk factor for development of cardiovascular disease: a statement from the American Heart Association Councils on Kidney in Cardiovascular Disease, High Blood Pressure Research, Clinical Cardiology, and Epidemiology and Prevention. Hypertension 2003;42:1050-65.
[7]
Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D; Modification of Diet in Renal Disease Study Group. A more accurate method to estimate glomerular filtration rate from serum creatinine. Ann Intern Med 1999;130:461-70. [Pubmed]
[8]
Botev R, Mallie JP, Couchoud C, Sch??ck O, Fauvel JP, Wetzels J, et al.??Estimating glomerular filtration rate: Cockcroft-Gault and Modification of Diet in Renal Disease formulas compared to renal inulin clearance. Clin J Am Soc Nephrol 2009;4:899-906. [Pubmed]
[9]
Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF 3rd, Feldman HI, et al., CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration). A new equation to estimate glomerular filtration rate. Ann Intern Med 2009;150:604-12. [Pubmed]
[10]
Monta??es R, Bover J, Oliver A, Ballarin J, Gracia S. Valoraci??n de la nueva ecuacion CKD-EPI para la estimaci??n del filtrado glomerular. Nefrologia 2010;30:185-94. [Pubmed]
[11]
Matsushita K, Selvin E, Bash LD, Astor BC, Coresh J. Risk implications of the new CKD Epidemiology Collaboration (CKD-EPI) equation compared with the MDRD Study equation for estimated GFR: the Atherosclerosis Risk in Communities (ARIC) Study. Am J Kidney Dis 2010;55:648-59. [Pubmed]
[12]
White S, Polkinghorne KR, Atkins RC, Chadban SJ. Comparison or the prevalence and mortality risk of CKD in Australia using the CKD Epidemiology Collaboration (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) Study estimating equations: the AusDiab (Australian Diabetes, Obesity and Lifestyle) Study. Am J Kidney Dis 2010;55:660-70. [Pubmed]
[13]
Eloot S, Schepers E, Barreto DV, Barreto FC, Liabeuf S, Van Biesen W, et al. Estimated glomerular filtration rate is a poor predictor of concentration for a broad range of uremic toxins. Clin J Am Soc Nephrol 2011;6:1266-7.
[14]
Levey AS, Coresh J, Balk E, Kausz AT, Levin A, Steffes MW, et al. National Kidney Foundation practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Ann Intern Med 2003;139:137-40.
[15]
Levey AS, de Jong PE, Coresh J, El Nahas M, Astor BC, Matsushita K, et al. The definition, classification, and prognosis of chronic kidney disease: a KDIGO Controversies Conference report. 2010. Available at: http://www.kidney-international.org
[16]
Matsushita K, van der Velde M, Astor BC, et al; Chronic Kidney Disease Prognosis Consortium. Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis. Lancet 2010;375:2073-81. [Pubmed]
[17]
Gansevoort RT, Matsushita K, van der Velde M, Astor BC, Woodward M, Levey AS, et al.; Chronic Kidney Disease Prognosis Consortium. Lower estimated GFR and higher albuminuria are associated with adverse kidney outcomes: a collaborative meta-analysis of general and high-risk population cohorts. Kidney Int 2011;80:93-104. [Pubmed]
[18]
O'Hare AM, Bertenthal D, Covinsky KE, Landefeld CS, Sen S, Mehta K, et al. Mortality risk stratification in chronic kidney disease: one size for all ages? J Am Soc Nephrol 2006;17:846-53. [Pubmed]
[19]
Fliser D, Zeier M, Nowack R, Ritz E. Renal functional reserve in healthy elderly subjects. J Am Soc Nephrol 1993;3:1371-7. [Pubmed]
[20]
Hsu CY, Iribarren C, McCulloch CE, Darbinian J, Go AS. Risk factors for end-stage renal disease: 25-year follow-up. Arch Intern Med 2009;169:342-50. [Pubmed]
[21]
Van Biesen W, De Bacquer D, Verbeke F, Delanghe J, Lameire N, Vanholder R. The glomerular filtration rate in an apparently healthy population and its relation with cardiovascular mortality during 10 years. Eur Heart J 2007;28:478-83. [Pubmed]
[22]
Rogacev KS, Seiler S, Zawada AM, Reichart B, Herath E, Roth D, et al. CD14 CD16 monocytes and cardiovascular outcome in patients with chronic kidney disease. Eur Heart J 2011;32:84-92. [Pubmed]
[23]
Hallan SI, Ritz E, Lydersen S, Romundstad S, Kvenild K, Orth SR. Combining GFR and albuminuria to classify CKD improves prediction of ESRD. J Am Soc Nephrol 2009;20:1069-77. [Pubmed]
[24]
Hallan SI, Steven P. Screening for chronic kidney disease: which strategy. J Nephrol 2010;23:147-55. [Pubmed]
[25]
Otero A, De Francisco A, Gayoso P, Garcia F. Prevalence of chronic kidney disease in Spain: Results of the EPIRCE Study. Nefrologia 2010;30:78-86.
[26]
Otero A, Gayoso P, Garc??a F, De Francisco AL. Epidemiology of chronic renal disease in the Galician population: Results of the pilot Spanish EPIRCE study. Kidney Int Suppl 2005;(99):S16-9. [Pubmed]
[27]
K/DOQI clinical practice guidelines for chronic kidney disease. Evaluation, classification and stratification. Am J Kidney Dis 2002;39 Suppl 1:S1-266.
[28]
De Jong PE, Curhan GC. Screening, monitoring and treatment of albuminuria: Public health perspectives. J Am Soc Nephrol 2006;17:2120-6. [Pubmed]
[29]
Wood SN. Generalized Additive Models: An Introduction with R. Chapman and Hall/CRC Press: New York; 2006.
[30]
R Development Core Team. R: A Language and Environment for Statistical Computing [article online], 2009. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, Available at: http://www.R-project.org [Accessed:??May 5,??2012].
[31]
Hallan SI, Orth SR. The KDQI 2002 classification of chronic kidney disease for whom the bell tolls. Nephrol Dial Transplant 2010;25:2832-6. [Pubmed]
[32]
Matsushita K, Mahmoodi BK, Woodward M, Emberson JR, Jafar TH, Jee SH, et al.; Chronic Kidney Disease Prognosis Consortium. Comparison of risk prediction using the CKD-EPI equation and the MDRD study equation for estimated glomerular filtration rate. JAMA 2012;307:1941-51. [Pubmed]
[33]
Shafi T, Matsushita K, Selvin E, Sang Y, Astor BC, INker LA, et al. Comparing the association of GFR estimated by the CKD-EPI and MDRD Study equations and mortality: the third national health and nutrition examination survey (NHANES III). BMC Nephrol 2012;13:42. [Pubmed]
[34]
Hemmelgarn BR, Manns BJ, Lloyd A, James MT, Klarenbach S, Quinn RR, et al. Relation between kidney function, proteinuria, and adverse outcomes. JAMA 2010;303:423-9. [Pubmed]
[35]
White SL, Polkinghorne KR, Atkins RC, Chadban SJ. Comparison of the prevalence and mortality risk of CKD in Australia using the CKD Epidemiology Collaboration (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) Study GFR estimating equations: the AusDiab (Australian Diabetes, Obesity and Lifestyle) Study. Am J Kidney Dis 2010;55:660-70. [Pubmed]
[36]
De Jong PE, van der Velde M, Gansevoort RT, Zoccali C. Screening for chronic kidney disease: where does europe go? Clin J Am Soc Nephrol 2008;3:616-23. [Pubmed]
[37]
Chen SC, Chang JM, Chou MC, Lin MY, Chen JH, Sun JH, et al. Slowing renal function decline in chronic kidney disease patients after nephrology referral. Nephrology (Carlton) 2008;13:730-6.
[38]
Carter JL, Stevens PE, Irving JE, Lamb EJ. Estimating glomerular filtration rate: comparison of the CKD-EPI and MDRD equations in a large UK cohort with particular emphasis on the effect of age. QJM 2011;104:839-44.
[39]
Kilbride HS, Stevens PE, Eaglestone G, Knight S, Carter JL, Delaney MP, et al. Accuracy of the MDRD (Modification of Diet in Renal Disease) Study and CKD-EPI (CKD Epidemiology Collaboration) equations for estimation of GFR in the elderly. Am J Kidney Dis 2013;61(1):57-66. [Pubmed]
[40]
Jones C, Roderick P, Harris S, Rogerson M. Decline in kidney function before and after nephrology referral and the effect on survival in moderate to advanced chronic kidney disease. Nephrol Dial Transplant 2006;21:2133-43. [Pubmed]
[41]
Mart??n de Francisco AL, Aguilera Garc??a L, Fuster Carulla V. Cardiovascular disease, renal disease and other chronic diseases. Earlier intervention is needed in chronic renal disease. Aten Primaria 2009;41:511-4. [Pubmed]
[42]
Earley A, Miskulin D, Lamb EJ, Levey AS, Uhlig K. Estimating equations for glomerular filtration rate in the era of creatinine standardization: a systematic review. Ann Intern Med 2012;156:785-95.
[43]
Stevens PE, Farmer CK, Hallan SI. The primary care physician: nephrology interface for the identification and treatment of chronic kidney disease. J Nephrol 2010;23:23-32. [Pubmed]
[44]
Richards N, Harris K, Whitfield M, O'Donoghue D, Lewis R, Mansell M, et al. Primary care-based disease management of chronic kidney disease (CKD), based on estimated glomerular filtration rate (eGFR) reporting, improves patient outcomes. Nephrol Dial Transplant 2008;23:549-55. [Pubmed]
Idiomas
Nefrología

Suscríbase a la newsletter

Opciones de artículo
Herramientas
es en

¿Es usted profesional sanitario apto para prescribir o dispensar medicamentos?

Are you a health professional able to prescribe or dispense drugs?