Differences between the CKD-EPI and the MDRD equations when estimating the glomerular filtration rate in hypertensive patients
Diferencias de la ecuación CKD-EPI con la de MDRD para la estimación del filtrado glomerular en pacientes hipertensos
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"apellidos" => "García Ortiz" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "affa" ] ] ] ] "afiliaciones" => array:5 [ 0 => array:3 [ "entidad" => "Atención Primaria, Unidad de Investigación La Alamedilla, Salamanca, " "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "affa" ] 1 => array:3 [ "entidad" => "Primary Healthcare, La Alamedilla Research Unit, Salamanca, " "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "affb" ] 2 => array:3 [ "entidad" => " Autonomous University of Barcelona, Barcelona, " "etiqueta" => "<span class="elsevierStyleSup">c</span>" "identificador" => "affc" ] 3 => array:3 [ "entidad" => " Universidad Autónoma, Barcelona, " "etiqueta" => "<span class="elsevierStyleSup">d</span>" "identificador" => "affd" ] 4 => array:3 [ "entidad" => " Unidad de Investigación de Atención Primaria de Girona, Girona, " "etiqueta" => "<span class="elsevierStyleSup">e</span>" "identificador" => "affe" ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Diferencias de la ecuación CKD-EPI con la de MDRD para la estimación del filtrado glomerular en pacientes hipertensos" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:8 [ "identificador" => "fig1" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "copyright" => "Elsevier España" "figura" => array:1 [ 0 => array:4 [ "imagen" => "10321_108_7349_en_10321_f1.jpg" "Alto" => 426 "Ancho" => 510 "Tamanyo" => 27248 ] ] "descripcion" => array:1 [ "en" => "Bland-Atmann graph" ] ] ] "textoCompleto" => "<p class="elsevierStylePara"><span class="elsevierStyleBold">INTRODUCTION</span></p><p class="elsevierStylePara">Chronic kidney disease (CKD) is a health issue that affects 10% of the adult population<span class="elsevierStyleSup">1-5</span> and more than 30% of the patients diagnosed with essential hypertension (HTN).<span class="elsevierStyleSup">6</span></p><p class="elsevierStylePara">The glomerular filtration rate (GFR) is the best indicator to assess renal function in hypertensive patients, but it is not easy to measure in clinical practice. Therefore, several equations have been developed to estimate the GFR. The most widely used equations include: the Cockroft-Gault equation,<span class="elsevierStyleSup">7</span> which overestimates the GFR at low values and presents a large dispersion of data, and the MDRD study equation<span class="elsevierStyleSup">8</span> (Modification of Diet in Renal Disease), which is currently recommended by the Spanish Society of Nephrology (SEN)<span class="elsevierStyleSup">9</span> as it is more accurate when estimating the GFR, both in its traditional version (MDRD) and the MDRD-IDMS version (Modification of Diet in Renal Disease-Isotope Dilution Mass Spectrometry), according to the analytical method used in creatinine determination. However, the MDRD equation has a number of limitations arising from the fact that the study was developed in patients with chronic kidney disease,<span class="elsevierStyleSup">10</span> and as such, its main limitations are imprecision and systematic underestimation, especially for GFR values greater than 90 mL/min 1.73 m<span class="elsevierStyleSup">2</span>.</p><p class="elsevierStylePara">At present, the CKD-EPI group (Chronic Kidney Disease Epidemiology Collaboration) has published a new equation for estimating the GFR, developed from a population of 8,254 individuals, which includes serum creatinine, age, gender and race as variables, with different versions depending on ethnicity, gender and creatinine value. According to the authors, the results of this equation are more accurate and precise than those of the current by-choice equation, i.e. the MDRD-IDMS equation, especially for GFR values above 60 mL/min/1.73 m<span class="elsevierStyleSup">2</span> in a group of 3,896 individuals.<span class="elsevierStyleSup">11</span></p><p class="elsevierStylePara">The aim of this study is to compare the GFR values estimated using the new CKD-EPI equation in relation to the MDRD-IDMS equation in a cohort of hypertensive patients and to analyse the correlation between the two equations.</p><p class="elsevierStylePara"><span class="elsevierStyleBold"> </span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">MATERIALS AND METHODS</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">Design and population</span></p><p class="elsevierStylePara">Cross-sectional descriptive study carried out in the field of primary healthcare at the La Alamedilla Research Unit. All Caucasian patients between 30 and 80 years old with a clinical diagnosis of HTN over the past five years who signed the informed consent form were included consecutively from December 2005 to June 2009. The excluded patients were those who met one of the criteria for which the use of equations to estimate the GFR is not appropriate: extreme body weight (BMI below 19 kg/m² or above 35 kg/m²), major alterations in the muscle mass (amputations, loss of muscle mass, muscle disorders or paralysis), acute renal failure, pregnancy, severe liver disease, generalised oedema and ascites.<span class="elsevierStyleSup">1,12</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">Variables analysed </span></p><p class="elsevierStylePara">We analysed age, gender, family history of premature vascular disease, smoking habit, diabetes mellitus, cerebrovascular disease and ischaemic heart disease. The determinations of creatinine and glucose in the blood and the albumin-creatinine index were carried out blindly at the reference laboratory after at least eight hours of fasting.</p><p class="elsevierStylePara">The examinations carried out included: weight, height, waist circumference and blood pressure measured with an OMRON M7 sphygmomanometer (Omron Healthcare, Kyoto, Japan), which was certified according to the recommendations of the European Society of Hypertension.<span class="elsevierStyleSup">13</span> </p><p class="elsevierStylePara">The estimation of the GFR<span class="elsevierStyleSup">11</span> was performed with the MDRD-IDMS equation, where GFR = 175 x (serum creatinine)<span class="elsevierStyleSup">-1.154</span> x age<span class="elsevierStyleSup">-0.203</span> x (0.742 if female),<span class="elsevierStyleSup">8</span> and the CKD-EPI equation, with the following equations for Caucasian patients:</p><p class="elsevierStylePara">For women with creatinine <0.7 mg/dL (62 mmol): GFR = 144 x (cr/0.7)<span class="elsevierStyleSup">-0.329</span> x (0.993)<span class="elsevierStyleSup">age</span>.</p><p class="elsevierStylePara">For women with creatinine >0.7 mg/dL (62 mmol): GFR = 144 × (cr/0.7)<span class="elsevierStyleSup">-1.209</span> x (0.993)<span class="elsevierStyleSup">age</span>.</p><p class="elsevierStylePara">For men with creatinine <0.9 mg/dL (80 mmol): GFR = 141 x (cr/0.9)<span class="elsevierStyleSup">-0.411</span> x (0.993)<span class="elsevierStyleSup">age.</span></p><p class="elsevierStylePara">For men with creatinine >0.9 mg/dL (80 mmol): GFR = 141 × (cr/0.9)<span class="elsevierStyleSup">-1.209 </span>x (0.993)<span class="elsevierStyleSup">age</span>.</p><p class="elsevierStylePara"><span class="elsevierStyleBold">Statistical analysis</span></p><p class="elsevierStylePara">The characteristics of the patients studied were described using central tendency and dispersion measures for the quantitative variables and percentages for the qualitative variables. The Student’s t-test was used for independent data in order to compare quantitative and qualitative variables of two categories, while the chi-square test was used for the qualitative variables.</p><p class="elsevierStylePara">In the end, we used the intraclass correlation rate to assess the correlation between the two equations. The population was subsequently divided into the five stages of chronic kidney disease of the National Kidney Foundation,<span class="elsevierStyleSup">14</span> using the kappa index to evaluate the correlation in the classification of patients among the different categories. We used the Bland-Altman plot for the graphic representation of the correlation between the CKD-EPI and MDRD variables. All the tests were carried out using the statistical software SPSS/PC+, version 15.0 (SPSS Inc., Chicago, Illinois, USA).</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara"><span class="elsevierStyleBold">RESULTS</span></p><p class="elsevierStylePara">Table 1 shows the characteristics of the hypertensive patients studied, as well as the cardiovascular risk factors, the serum creatinine values, the albumin-creatinine index and the GFR estimated using both equations for the total group and according to gender. The average progression of the disease was 3.41 years, while the percentage of patients on medication for hypertension was 55.6%. The range of creatinine ranged between 0.5 and 2.4 mg/dL.</p><p class="elsevierStylePara">The GFR mean in the whole sample estimated using the CKD-EPI equation was 4.37 mL/min/1.73m<span class="elsevierStyleSup">2</span> (95% CI, 3.73 to 4.19), higher than that of the MDRD-IDMS equation. It was also higher in women (5.04 mL/min/1.73 m<span class="elsevierStyleSup">2</span> [95% CI, 4.07 to 6.01]) and in men (3.99 mL/min/1.73 m<span class="elsevierStyleSup">2</span> [95% CI, 3.13 to 4.79]). In addition, these differences were also similar in those younger than 65 years, with the GFR being higher in the total sample when measured with the CKD-EPI equation: 6.55 mL/min/1.73 m<span class="elsevierStyleSup">2</span> (95% CI, 5.95 to 7.15). Finally, in the same age group, the GFR in women was 6.48 mL/min/1.73 m<span class="elsevierStyleSup">2</span> (95% CI, 6.50 to 8.44) and 6.07 mL/min/11.73 m<span class="elsevierStyleSup">2</span> (95% CI, 5.32 to 6.81) in men.</p><p class="elsevierStylePara">However, although the MDRD-IDMS equation estimated the GFR in men slightly higher (1.84 mL/min/1.73 m<span class="elsevierStyleSup">2</span> [95% CI, -0.002 to 3.67]) and in women slightly lower (0.70 mL/min/1.73 m<span class="elsevierStyleSup">2</span> [95% CI, -2.31 to 0.90]), the CKD-EPI equation found no significant differences between the two methods among those over 65 years of age. The percentage of occult renal disease estimated by the two equations was 5% higher in women than in men, while age was higher in both men and women (Table 1). The correlation coefficient between the two equations was 0.904 (95% CI, 0.886 to 0.919), with 0.897 in men (95% CI, 0.873 to 0.917) and 0.917 in women (95% CI, 0.890 to 0.937).</p><p class="elsevierStylePara">The correlation in the classification of the CKD stages was lower in stage 1 (82.04%), where the CKD-EPI equation classified a greater percentage of hypertensive patients, whereas the MDRD-IDMS equation classified a higher percentage of patients (86.35%) in stage 2. In stages 3 and 4, the correlation was 92.09% and 100%, respectively. Finally, in stage 5, no patient was classified by any of the two equations. The kappa index was 0.848 (95% CI, 0.795 to 0.889). This index was higher in women (0.852 [95% CI, 0.778 to 0.926]) than in men (0.845 [95% CI, 0.786 to 0.904]). Figure 1 shows the correlation for the CKD-EPI and MDRD variables, with a -0.86 mean value of differences, and the limits of agreement.</p><p class="elsevierStylePara"><span class="elsevierStyleBold"> </span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">DISCUSSION</span></p><p class="elsevierStylePara">The results of this study indicate that if the GFR is estimated with the new equation, the rate in hypertensive patients is 4.37 mL/min/1.73 m<span class="elsevierStyleSup">2</span> higher than the rate obtained with the MDRD-IDMS equation.<span class="elsevierStyleSup">8</span> These differences increase in those under 65 years of age to 6.55 mL/min/1.73m<span class="elsevierStyleSup">2</span>, in both men (6.07) and women (7.47). However, there were no differences between the two equations in the total group or according to gender in patients over 65 years of age. This increase in the GFR value results in a reclassification of the patients to higher stages, especially concerning the CKD-EPI equation,<span class="elsevierStyleSup">11</span> which classified a higher number of hypertensive patients in stage 1, whereas the MDRD-IDMS equation<span class="elsevierStyleSup">8</span> classified them in stage 2.</p><p class="elsevierStylePara">The intraclass correlation coefficient between the GFR rates estimated by both equations was 0.904 (95% CI, 0.886 to 0.919), while the kappa index concerning the classification of the different stages of renal failure was 0.848.</p><p class="elsevierStylePara">This 4.37 mL/min/1.73 m<span class="elsevierStyleSup">2</span> difference in the GFR of hypertensive patients between the two equations is smaller than the data presented from the application of the CKD-EPI equation<span class="elsevierStyleSup">11</span> on the study population (the National Health and Nutrition Examination Survey – NHANES, 1999-2006).<span class="elsevierStyleSup">1</span> In the latter, the value of the GFR from the new equation was 9.5 mL/min/1.73 m<span class="elsevierStyleSup">2</span> higher than those obtained with the MDRD-IDMS equation,<span class="elsevierStyleSup">8</span> showing a prevalence rate of chronic kidney disease (CKD) of 11.5% compared to 13.1%. This prevalence rate is lower than that in this study, which was 14.4% and 15.9% in the CKD-EPI and the MDRD-IDMS equations,<span class="elsevierStyleSup">8</span> respectively. This datum is logical if we consider that we are analysing hypertensive patients and not the general population.</p><p class="elsevierStylePara">In a recently published study by Bermudez Montanes R. et al.<span class="elsevierStyleSup">15</span> where the GFR values were estimated using the new CKD-EPI equation<span class="elsevierStyleSup">11</span> compared with the MDRD-IDMS equation<span class="elsevierStyleSup">8</span> in a cohort of 14,427 patients, the average GFR value was 0.6 mL/min/1.73 m<span class="elsevierStyleSup">2</span> higher in the CKD-EPI equation<span class="elsevierStyleSup">11</span> than in the MDRD-IDMS equation<span class="elsevierStyleSup">8</span> in the total group. The value was 1.9 mL/min/1.73 m<span class="elsevierStyleSup">2</span> higher for women and 0.2 mL/min/1.73 m<span class="elsevierStyleSup">2</span> lower for men. These results are consistent with those obtained in hypertensive patients. Nevertheless, only the CKD-EPI equation<span class="elsevierStyleSup">11</span> estimated a lower GFR value in men over 65 years of age. Unlike in our study, the correlation was higher in men.<span class="elsevierStyleBold">  </span></p><p class="elsevierStylePara">The use of the ERC-EPI equation<span class="elsevierStyleSup">11</span> reduces the prevalence of women diagnosed with CKD, which is one of the problems with the MDRD-IDMS equation,<span class="elsevierStyleSup">8</span> which underestimates the GFR in elderly people and in women, thus increasing the diagnosis of CKD in these groups.<span class="elsevierStyleSup">16</span> However, there seems to be no improvement of the prevalence in elderly people.<span class="elsevierStyleBold"> </span></p><p class="elsevierStylePara">The main contribution of this study is that it constitutes the first publication that analyses the new CKD-EPI equation in hypertensive patients within the Spanish primary healthcare system. The major limitation is the lack of knowledge of the true GFR value, since we do not have a direct measurement from a standard method. Another limitation that we cannot overlook is whether the performance in the upper stages is the same, since only one patient reported a GFR value lower than 30 mL/min/1.73 m<span class="elsevierStyleSup">2</span>.</p><p class="elsevierStylePara">To conclude, we believe that until we have results of longitudinal studies to confirm the data this equation can be used in the clinical practice to estimate the GFR in hypertensive patients. We base our conclusion on the fact that the results obtained in hypertensive patients are consistent with those published by other authors.<span class="elsevierStyleSup">11,15</span> In addition, the new CKD-EPI equation<span class="elsevierStyleSup">11</span> for the estimation of GFR reclassifies a considerable number of hypertensive patients, mainly younger ones, to stages with a higher GFR value. It therefore yields more accurate and precise results than the MDRD-IDMS equation.<span class="elsevierStyleSup">8</span></p><p class="elsevierStylePara"><a href="grande/10321_108_7349_en_10321_f1.jpg" class="elsevierStyleCrossRefs"><img src="10321_108_7349_en_10321_f1.jpg" alt="Bland-Atmann graph"></img></a></p><p class="elsevierStylePara">Figure 1. Bland-Atmann graph</p><p class="elsevierStylePara"><a href="10321_108_7347_en_w477710395410321_18107_2043_es_10321_15491_2043_es_tabla_1_copy1_en.doc" class="elsevierStyleCrossRefs">10321_108_7347_en_w477710395410321_18107_2043_es_10321_15491_2043_es_tabla_1_copy1_en.doc</a></p><p class="elsevierStylePara">Table 1. General characteristics and gender of the hypertensive patients studied</p><p class="elsevierStylePara"><a href="10321_108_7348_en_w477710395510321_18107_2044_es_10321_15491_2044_es_tabla_2_en.doc" class="elsevierStyleCrossRefs">10321_108_7348_en_w477710395510321_18107_2044_es_10321_15491_2044_es_tabla_2_en.doc</a></p><p class="elsevierStylePara">Table 2. Correlation in the classification of the stages of chronic kidney disease between the estimated glomerular filtration rates of the MDRD-IDMS and CKD-EPI equations</p>" "pdfFichero" => "P1-E501-S2437-A10321-EN.pdf" "tienePdf" => true "PalabrasClave" => array:2 [ "es" => array:6 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec441771" "palabras" => array:1 [ 0 => "Enfermedad renal, epidemiología" ] ] 1 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec441773" "palabras" => array:1 [ 0 => "Calibración" ] ] 2 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec441775" "palabras" => array:1 [ 0 => "Ecuaciones de estimación del filtrado glomerular" ] ] 3 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec441777" "palabras" => array:1 [ 0 => "Enfermedad renal, diagnóstico" ] ] 4 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec441779" "palabras" => array:1 [ 0 => "Presión arterial" ] ] 5 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec441781" "palabras" => array:1 [ 0 => "Creatinina" ] ] ] "en" => array:6 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec441772" "palabras" => array:1 [ 0 => "Kidney diseases, epidemiology" ] ] 1 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec441774" "palabras" => array:1 [ 0 => "Calibration" ] ] 2 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec441776" "palabras" => array:1 [ 0 => "Glomerular filtration rate" ] ] 3 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec441778" "palabras" => array:1 [ 0 => "Kidney diseases, diagnosis" ] ] 4 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec441780" "palabras" => array:1 [ 0 => "Blood pressure" ] ] 5 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec441782" "palabras" => array:1 [ 0 => "Creatinine" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "es" => array:1 [ "resumen" => "<p class="elsevierStylePara"><span class="elsevierStyleBold">Objetivo: </span>Analizar las concordancias en el filtrado glomerular (FG) estimado con las ecuaciones de CKD-EPI y MDRD-IDMS en una cohorte de pacientes hipertensos. <span class="elsevierStyleBold">Métodos: </span>Se incluyeron 478 hipertensos consecutivamente, edad media 57,58 años (DE = 12,34), el 68,3% hombres. La estimación del FG se realizó con las ecuaciones de MDRD-IDMS y CKD-EPI, valorando las concordancias entre ellas. <span class="elsevierStyleBold">Resultados: </span>La estimación de FG con CKD-EPI fue 4,37 ml/min/1,73 m<span class="elsevierStyleSup">2 </span>(IC 95%, 3,73-4,19) superior al MDRD-IDMS en global y por sexos (hombres 3,99; mujeres 5,04). En menores de 65 años la diferencia fue mayor, 6,55 ml/min/1,73 m<span class="elsevierStyleSup">2 </span>(IC 95%, 5,95-7,15), tanto en hombres (6,07) como en mujeres (6,48). Sin embargo, en mayores de 65 años no se encontró diferencia significativa. El coeficiente de correlación intraclase fue 0,904 (IC 95%, 0,886-0,919), en hombres 0,897 y en mujeres 0,917, y el índice kappa fue 0,848 (IC 95%, 0,795-0,889), en hombres 0,845 y en mujeres 0,852. <span class="elsevierStyleBold">Conclusión: </span>La ecuación de CKD-EPI estima un FG más alto en mayores de 65 años y reclasifica hacia estadio 1 a hipertensos catalogados en estadío 2 por MDRD-IDMS.</p>" ] "en" => array:1 [ "resumen" => "<p class="elsevierStylePara"><span class="elsevierStyleItalic"><span class="elsevierStyleBold">Objective:</span> To analyze the agreement in glomerular filtration rate (GFR) estimated with CKD-EPI and MDRD-IDMS equations in a cohort of hypertensive patients. <span class="elsevierStyleBold">Methods</span>: We included consecutively 478 hypertensive patients, mean age 57.58 yr (SD: 12.34), 68.3% males. The estimation of GFR was performed with MDRD-IDMS and CKD-EPI equations and we analyzed the agreement between them. <span class="elsevierStyleBold">Results: </span>The estimation of GFR with CKD-EPI was 4.37 (95%:3.73-4.19) mL/min/1,73 m2 higher than MDRD-IDMS, overall and by gender (males 3.99; females 5.04). In patients under 65 years the difference was greater, 6.55 (95%:5.95-7.15) mL/min/1.73 m2 in both men 6.07 and women 6.48. However, we found no significant difference over 65 years. Intraclass correlation coefficient was 0.904 (95%CI:0.886-0.919), 0.897 men and 0.917 women and Kappa index 0.848 (95% CI :0.795-0.889), 0.845 men and 0.852 women. <span class="elsevierStyleBold">Conclusion:</span> CKD-EPI equation estimated a higher GFR in hypertensive patients under  65 years and reclassified in stage 1 patients classified in stage 2  by MDRD-IDMS.</span></p>" ] ] "multimedia" => array:3 [ 0 => array:8 [ "identificador" => "fig1" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "copyright" => "Elsevier España" "figura" => array:1 [ 0 => array:4 [ "imagen" => "10321_108_7349_en_10321_f1.jpg" "Alto" => 426 "Ancho" => 510 "Tamanyo" => 27248 ] ] "descripcion" => array:1 [ "en" => "Bland-Atmann graph" ] ] 1 => array:8 [ "identificador" => "mmc1" "etiqueta" => "Tab. 1" "tipo" => "MULTIMEDIAECOMPONENTE" "mostrarFloat" => true "mostrarDisplay" => false "copyright" => "Elsevier España" "Ecomponente" => array:2 [ "fichero" => "10321_108_7347_en_w477710395410321_18107_2043_es_10321_15491_2043_es_tabla_1_copy1_en.doc" "ficheroTamanyo" => 87040 ] "descripcion" => array:1 [ "en" => "General characteristics and gender of the hypertensive patients studied" ] ] 2 => array:8 [ "identificador" => "mmc2" "etiqueta" => "Tab. 2" "tipo" => "MULTIMEDIAECOMPONENTE" "mostrarFloat" => true "mostrarDisplay" => false "copyright" => "Elsevier España" "Ecomponente" => array:2 [ "fichero" => "10321_108_7348_en_w477710395510321_18107_2044_es_10321_15491_2044_es_tabla_2_en.doc" "ficheroTamanyo" => 36864 ] "descripcion" => array:1 [ "en" => "Correlation in the classification of the stages of chronic kidney disease between the estimated glomerular filtration rates of the MDRD-IDMS and CKD-EPI equations" ] ] ] "bibliografia" => array:2 [ "titulo" => "Bibliography" "seccion" => array:1 [ 0 => array:1 [ "bibliografiaReferencia" => array:16 [ 0 => array:3 [ "identificador" => "bib1" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:3 [ "referenciaCompleta" => "Coresh J, Selvin E, Stevens LA, Manzi J, Kusek JW, Eggers P, et al. 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| 2021 June | 41 | 27 | 68 |
| 2021 May | 55 | 35 | 90 |
| 2021 April | 212 | 99 | 311 |
| 2021 March | 131 | 21 | 152 |
| 2021 February | 113 | 21 | 134 |
| 2021 January | 70 | 16 | 86 |
| 2020 December | 53 | 9 | 62 |
| 2020 November | 57 | 17 | 74 |
| 2020 October | 66 | 16 | 82 |
| 2020 September | 48 | 3 | 51 |
| 2020 August | 50 | 7 | 57 |
| 2020 July | 50 | 6 | 56 |
| 2020 June | 48 | 8 | 56 |
| 2020 May | 60 | 12 | 72 |
| 2020 April | 75 | 15 | 90 |
| 2020 March | 83 | 15 | 98 |
| 2020 February | 88 | 1526 | 1614 |
| 2020 January | 91 | 23 | 114 |
| 2019 December | 77 | 24 | 101 |
| 2019 November | 97 | 23 | 120 |
| 2019 October | 69 | 7 | 76 |
| 2019 September | 83 | 15 | 98 |
| 2019 August | 56 | 5 | 61 |
| 2019 July | 87 | 36 | 123 |
| 2019 June | 59 | 8 | 67 |
| 2019 May | 84 | 14 | 98 |
| 2019 April | 142 | 36 | 178 |
| 2019 March | 145 | 27 | 172 |
| 2019 February | 43 | 13 | 56 |
| 2019 January | 41 | 12 | 53 |
| 2018 December | 94 | 42 | 136 |
| 2018 November | 111 | 18 | 129 |
| 2018 October | 138 | 15 | 153 |
| 2018 September | 90 | 18 | 108 |
| 2018 August | 60 | 18 | 78 |
| 2018 July | 56 | 14 | 70 |
| 2018 June | 77 | 13 | 90 |
| 2018 May | 61 | 17 | 78 |
| 2018 April | 59 | 3 | 62 |
| 2018 March | 73 | 8 | 81 |
| 2018 February | 77 | 6 | 83 |
| 2018 January | 57 | 7 | 64 |
| 2017 December | 68 | 9 | 77 |
| 2017 November | 62 | 8 | 70 |
| 2017 October | 73 | 8 | 81 |
| 2017 September | 94 | 12 | 106 |
| 2017 August | 58 | 7 | 65 |
| 2017 July | 60 | 10 | 70 |
| 2017 June | 70 | 8 | 78 |
| 2017 May | 58 | 14 | 72 |
| 2017 April | 44 | 9 | 53 |
| 2017 March | 47 | 17 | 64 |
| 2017 February | 72 | 10 | 82 |
| 2017 January | 49 | 10 | 59 |
| 2016 December | 82 | 2 | 84 |
| 2016 November | 91 | 12 | 103 |
| 2016 October | 113 | 14 | 127 |
| 2016 September | 164 | 8 | 172 |
| 2016 August | 230 | 3 | 233 |
| 2016 July | 193 | 9 | 202 |
| 2016 June | 141 | 0 | 141 |
| 2016 May | 153 | 0 | 153 |
| 2016 April | 104 | 0 | 104 |
| 2016 March | 106 | 0 | 106 |
| 2016 February | 145 | 0 | 145 |
| 2016 January | 123 | 0 | 123 |
| 2015 December | 117 | 0 | 117 |
| 2015 November | 98 | 0 | 98 |
| 2015 October | 109 | 0 | 109 |
| 2015 September | 85 | 0 | 85 |
| 2015 August | 77 | 0 | 77 |
| 2015 July | 72 | 0 | 72 |
| 2015 June | 35 | 0 | 35 |
| 2015 May | 59 | 0 | 59 |
| 2015 April | 10 | 0 | 10 |
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