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"<span class="elsevierStyleTextfn">Caso clínico</span>" "titulo" => "Acidosis tubular renal distal en dos niñas diagnosticadas de hipotiroidismo adquirido" "tienePdf" => "es" "tieneTextoCompleto" => "es" "tieneResumen" => array:2 [ 0 => "es" 1 => "en" ] "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "655" "paginaFinal" => "659" ] ] "titulosAlternativos" => array:1 [ "en" => array:1 [ "titulo" => "Distal renal tubular acidosis in two children with acquired hypothyroidism" ] ] "contieneResumen" => array:2 [ "es" => true "en" => true ] "contieneTextoCompleto" => array:1 [ "es" => true ] "contienePdf" => array:1 [ "es" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figura 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 648 "Ancho" => 950 "Tamanyo" => 48830 ] ] "descripcion" => array:1 [ "es" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Imagen de nefrocalcinosis ecográfica en el caso 1.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Norma E. Guerra-Hernández, Karen V. Ordaz-López, Rosa Vargas-Poussou, Laura Escobar-Pérez, Víctor M. García-Nieto" "autores" => array:5 [ 0 => array:2 [ "nombre" => "Norma E." "apellidos" => "Guerra-Hernández" ] 1 => array:2 [ "nombre" => "Karen V." "apellidos" => "Ordaz-López" ] 2 => array:2 [ "nombre" => "Rosa" "apellidos" => "Vargas-Poussou" ] 3 => array:2 [ "nombre" => "Laura" "apellidos" => "Escobar-Pérez" ] 4 => array:2 [ "nombre" => "Víctor M." "apellidos" => "García-Nieto" ] ] ] ] ] "idiomaDefecto" => "es" "Traduccion" => array:1 [ "en" => array:9 [ "pii" => "S2013251418301391" "doi" => "10.1016/j.nefroe.2017.12.005" "estado" => "S300" "subdocumento" => "" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:1 [ "total" => 0 ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2013251418301391?idApp=UINPBA000064" ] ] "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0211699518300407?idApp=UINPBA000064" "url" => "/02116995/0000003800000006/v2_201812130605/S0211699518300407/v2_201812130605/es/main.assets" ] "itemAnterior" => array:20 [ "pii" => "S0211699518301401" "issn" => "02116995" "doi" => "10.1016/j.nefro.2018.07.008" "estado" => "S300" "fechaPublicacion" => "2018-11-01" "aid" => "530" "copyright" => "Sociedad Española de Nefrología" "documento" => "article" "crossmark" => 0 "licencia" => "http://creativecommons.org/licenses/by-nc-nd/4.0/" "subdocumento" => "fla" "cita" => "Nefrologia. 2018;38:639-46" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:2 [ "total" => 4552 "formatos" => array:3 [ "EPUB" => 214 "HTML" => 3407 "PDF" => 931 ] ] "es" => array:13 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original breve</span>" "titulo" => "Contribución de las toxinas urémicas a la fibrosis vascular asociada a la enfermedad renal crónica" "tienePdf" => "es" "tieneTextoCompleto" => "es" "tieneResumen" => array:2 [ 0 => "es" 1 => "en" ] "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "639" "paginaFinal" => "646" ] ] "titulosAlternativos" => array:1 [ "en" => array:1 [ "titulo" => "Contribution of uraemic toxins to the vascular fibrosis associated with chronic kidney disease" ] ] "contieneResumen" => array:2 [ "es" => true "en" => true ] "contieneTextoCompleto" => array:1 [ "es" => true ] "contienePdf" => array:1 [ "es" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0020" "etiqueta" => "Figura 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 2873 "Ancho" => 2333 "Tamanyo" => 525412 ] ] "descripcion" => array:1 [ "es" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Las dosis altas de toxinas urémicas inducen la expresión de la citocina profibrótica TGF-β1 o de proteínas de matriz extracelular en células de músculo liso vascular. Las células de músculo liso de aorta humana fueron incubadas con medio suplementado con suero humano al 2,5%, durante 24<span class="elsevierStyleHsp" style=""></span>h. Posteriormente fueron tratadas durante 2, 4, 6 o 24<span class="elsevierStyleHsp" style=""></span>h (A, C y D) o 24<span class="elsevierStyleHsp" style=""></span>h (B) con toxinas urémicas: indoxil-sulfato (IS 100<span class="elsevierStyleHsp" style=""></span>μg/ml), para-cresol (pc 100<span class="elsevierStyleHsp" style=""></span>μg/ml) o una mezcla de ambas (IS<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>pc 100<span class="elsevierStyleHsp" style=""></span>μg/ml). Se enseñan Western blots representativos de TGF-β1 (A), colágeno <span class="elsevierStyleSmallCaps">i</span> (COL I, C) y fibronectina (D). Los niveles de GAPDH fueron determinados como sus respectivos controles endógenos. Las barras representan los valores del análisis densitométrico de los blots normalizados contra el control endógeno. La expresión de TGF-β1 se analizó mediante inmunofluorescencia (B). Se enseñan imágenes representativas de las fotografías obtenidas mediante microscopia confocal (×100). Los valores se representan como la media<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>SEM. *p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0,05 vs. Control (CT, células no tratadas).</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Marco Hatem-Vaquero, Sergio de Frutos, Alicia Luengo, Alba González Abajo, Mercedes Griera, Manuel Rodríguez-Puyol, Diego Rodríguez-Puyol, Laura Calleros" "autores" => array:8 [ 0 => array:2 [ "nombre" => "Marco" "apellidos" => "Hatem-Vaquero" ] 1 => array:2 [ "nombre" => "Sergio" "apellidos" => "de Frutos" ] 2 => array:2 [ "nombre" => "Alicia" "apellidos" => "Luengo" ] 3 => array:2 [ "nombre" => "Alba" "apellidos" => "González Abajo" ] 4 => array:2 [ "nombre" => "Mercedes" "apellidos" => "Griera" ] 5 => array:2 [ "nombre" => "Manuel" "apellidos" => "Rodríguez-Puyol" ] 6 => array:2 [ "nombre" => "Diego" "apellidos" => "Rodríguez-Puyol" ] 7 => array:2 [ "nombre" => "Laura" "apellidos" => "Calleros" ] ] ] ] ] "idiomaDefecto" => "es" "Traduccion" => array:1 [ "en" => array:9 [ "pii" => "S2013251418301457" "doi" => "10.1016/j.nefroe.2018.11.010" "estado" => "S300" "subdocumento" => "" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:1 [ "total" => 0 ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2013251418301457?idApp=UINPBA000064" ] ] "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0211699518301401?idApp=UINPBA000064" "url" => "/02116995/0000003800000006/v2_201812130605/S0211699518301401/v2_201812130605/es/main.assets" ] "en" => array:19 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original article</span>" "titulo" => "Influence of dietary protein intake on body composition in chronic kidney disease patients in stages 3–5: A cross-sectional study" "tieneTextoCompleto" => true "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "647" "paginaFinal" => "654" ] ] "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "Guillermina Barril, Angel Nogueira, Mar Ruperto López, Yone Castro, José Antonio Sánchez-Tomero" "autores" => array:5 [ 0 => array:4 [ "nombre" => "Guillermina" "apellidos" => "Barril" "email" => array:1 [ 0 => "gbarril43@gmail.com" ] "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">*</span>" "identificador" => "cor0005" ] ] ] 1 => array:3 [ "nombre" => "Angel" "apellidos" => "Nogueira" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] 2 => array:3 [ "nombre" => "Mar" "apellidos" => "Ruperto López" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">c</span>" "identificador" => "aff0015" ] ] ] 3 => array:3 [ "nombre" => "Yone" "apellidos" => "Castro" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">d</span>" "identificador" => "aff0020" ] ] ] 4 => array:3 [ "nombre" => "José Antonio" "apellidos" => "Sánchez-Tomero" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">e</span>" "identificador" => "aff0025" ] ] ] ] "afiliaciones" => array:5 [ 0 => array:3 [ "entidad" => "Department of Nephrology, Advanced-chronic Kidney Disease Unit, Hospital Universitario de la Princesa, C/ Diego de León n° 62, 28006 Madrid, Spain" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Advanced-chronic Kidney Disease Unit, Hospital Universitario de la Princesa, C/ Diego de León n° 62, 28006 Madrid, Spain" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Human Nutrition and Dietetics Department, Faculty of Health Sciences, Universidad Alfonso X el Sabio, Avda. Universidad s/n, 28691 Villanueva de la Cañada, Madrid, Spain" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Orientation Department, Area of Investigation, Prodis Foundation, C/ Bulevar Indalecio Prieto 2, 28032 Madrid, Spain" "etiqueta" => "d" "identificador" => "aff0020" ] 4 => array:3 [ "entidad" => "Department of Nephrology, Advanced-chronic Kidney Disease Unit, Hospital Universitario de la Princesa, 28006 Madrid, Spain" "etiqueta" => "e" "identificador" => "aff0025" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "<span class="elsevierStyleItalic">Corresponding author</span>." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Influencia del consumo de proteínas en la composición corporal de pacientes con enfermedad renal crónica en estadios 3-5: estudio transversal" ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Background</span><p id="par0005" class="elsevierStylePara elsevierViewall">Dietary protein intake is a pivotal issue in the progression and treatment of the chronic kidney disease (CKD) patients. The early primary care on moderate-to-advanced CKD stages of well-known causative factors such as reduction of accumulation of nitrogenous wastes, metabolic derangements and protein-energy wasting (PEW), have showed a central role to slow onset of dialysis<a class="elsevierStyleCrossRefs" href="#bib0185"><span class="elsevierStyleSup">1,2</span></a> and mortality rates<a class="elsevierStyleCrossRef" href="#bib0370"><span class="elsevierStyleSup">3</span></a> in CKD population.</p><p id="par0010" class="elsevierStylePara elsevierViewall">Guidelines on CKD<a class="elsevierStyleCrossRefs" href="#bib0375"><span class="elsevierStyleSup">4,5</span></a> and Nutrition,<a class="elsevierStyleCrossRefs" href="#bib0210"><span class="elsevierStyleSup">6,7</span></a> recommend two tentative nutritional approaches for managing dietary protein intake in CKD stages 4,5. A low-protein diet (LPD), consists of 0.6–0.8<span class="elsevierStyleHsp" style=""></span>g/kg BW/day or a very low-protein diet (VLPD), providing a protein intake between 0.3 and 0.4<span class="elsevierStyleHsp" style=""></span>g/kg BW/day supplemented with essential aminoacids (EAA) and ketoanalogues (KA). Both therapeutic strategies preserve renal function in well-nourished patients<a class="elsevierStyleCrossRefs" href="#bib0385"><span class="elsevierStyleSup">8–10</span></a> whereas, the ideal recommendation of dietary protein restriction on the progression of CKD, and its potential consequences on nutritional status and body composition still unclear.</p><p id="par0015" class="elsevierStylePara elsevierViewall">PEW is frequently associated with higher risk of morbidity and mortality.<a class="elsevierStyleCrossRef" href="#bib0370"><span class="elsevierStyleSup">3</span></a> Lack of appetite and uremic anorexia interferes on nutritional status and body composition measures in CKD patients. Bioelectrical impedance (BIA), is a non-invasive method for the assessment of body composition and conditions associated with expanded extracellular water (ECW).<a class="elsevierStyleCrossRef" href="#bib0395"><span class="elsevierStyleSup">11</span></a> Previous studies<a class="elsevierStyleCrossRefs" href="#bib0400"><span class="elsevierStyleSup">12,13</span></a> reported that BIA-derived measures may be important in glomerular filtration rate (GFR) prediction and several studies<a class="elsevierStyleCrossRefs" href="#bib0250"><span class="elsevierStyleSup">14,15</span></a> demonstrated that the inclusion of muscle mass improved GFR estimations. Dumler et al.,<a class="elsevierStyleCrossRef" href="#bib0260"><span class="elsevierStyleSup">16</span></a> showed that CKD patients with stable renal function following a daily dietary protein intake (0.6–0.8<span class="elsevierStyleHsp" style=""></span>g/kg normalized body weight/day), had no loss of body cell mass (BCM) or fat-free mass (FFM) over a 9-month period measured by BIA. Thus, assessment and follow-up by nutritional indicators and body composition measures could be useful to early diagnosis of being wasted. These results push up to study whether the body composition in CKD patients stages 3–5 according to their daily dietary protein intake might predispose to muscle wasting because of dietary restrictions and the catabolic effects of uremia. There is little evidence with regard to the dietary protein intake restriction on body composition in moderate-advanced CKD. This study aimed to analyze usual dietary protein intake and its potential contribution on body composition in CKD patients on stages 3–5.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Patients and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Study design</span><p id="par0020" class="elsevierStylePara elsevierViewall">This cross-sectional study was carried out at Hospital Universitario de La Princesa, Madrid (Spain) in 134 CKD patients on stages 3–5. Eligible participants were CKD adults (≥18 years) stabilized for at least (minimum) of 3 months before enrolment. Patients with amputated limbs, clinically evident active infection, liver disease, autoimmune diseases, or malignancies were excluded to avoid the possible effects of these comorbid conditions on inflammatory markers and on body composition status. Informed consent was obtained from every participant. The study was conducted in accordance with the Declaration of Helsinki and was approved by the Medical Ethic Committee of Hospital de la Princesa (code number: 2849).</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Clinical assessment</span><p id="par0025" class="elsevierStylePara elsevierViewall">Demographic, clinical and nutritional data were obtained from the medical history of each patient. The monographic nutrition CKD consultation at advanced-CKD unit, was usually recommended 0.8<span class="elsevierStyleHsp" style=""></span>g/kg BW/day of protein intake and dietary salt-restriction according to the guidelines for CKD patients.<a class="elsevierStyleCrossRef" href="#bib0375"><span class="elsevierStyleSup">4</span></a> Nutritional counseling and follow-up is carried out every three months for ensuring adherence to nutritional recommendations. Serial nPna measures and body composition analysis at each three-month visit, are routinely performed in order to check compliance with protein prescription. LPD supplemented with KA, were not currently used for managing CKD at the advanced CKD-unit. Glomerular filtration rate was estimated by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation for the estimated glomerular filtration rate (e-GFR).<a class="elsevierStyleCrossRef" href="#bib0410"><span class="elsevierStyleSup">17</span></a></p><p id="par0030" class="elsevierStylePara elsevierViewall">Normalized protein nitrogen appearance (nPna) as a surrogate indicator of dietary protein intake according to the equation proposed by the Kidney Disease Outcomes Quality Initiative clinical practice guidelines<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">18</span></a> was calculated as follows:<elsevierMultimedia ident="eq0005"></elsevierMultimedia></p><p id="par0035" class="elsevierStylePara elsevierViewall">The sample was classified into three nPna groups (G<span class="elsevierStyleInf"><span class="elsevierStyleItalic">n</span></span>) according the daily mean of the protein intake (to mean of daily protein intake): (G<span class="elsevierStyleInf">1</span>): nPna<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.8<span class="elsevierStyleHsp" style=""></span>g/kg/day; (G<span class="elsevierStyleInf">2</span>): nPna 0.8–1<span class="elsevierStyleHsp" style=""></span>g/kg/day and, (G<span class="elsevierStyleInf">3</span>): nPna<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>1<span class="elsevierStyleHsp" style=""></span>g/kg/day.</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Nutritional assessment</span><p id="par0040" class="elsevierStylePara elsevierViewall">Nutritional status was assessed by the malnutrition-inflammation score (MIS) questionnaire,<a class="elsevierStyleCrossRef" href="#bib0275"><span class="elsevierStyleSup">19</span></a> including six different components: five subjective assessments (concerning the patient's medical history and physical examination), and three objective assessments [s-albumin, total binding iron capacity and body mass index (BMI)]. In agreement with other studies,<a class="elsevierStyleCrossRef" href="#bib0280"><span class="elsevierStyleSup">20</span></a> PEW was defined as a MIS score ≥5.</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Anthropometric measurements</span><p id="par0045" class="elsevierStylePara elsevierViewall">Body weight (BW), BMI, standard body weight (SBW), triceps skinfold thickness (TSF), and mid-arm muscle circumference (MAMC) were recorded as anthropometric measures. The BMI as dry weight in kilograms divided by the square of height in meters was calculated. TSF was measured with a Lange Skin Calipers (Holtain Caliper, Crymch, Dyfed, UK), using standard techniques. MAMC was estimated as follows: MAMC (cm)<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>mid-arm circumference (cm)<span class="elsevierStyleHsp" style=""></span>−<span class="elsevierStyleHsp" style=""></span>0.314<span class="elsevierStyleHsp" style=""></span>×<span class="elsevierStyleHsp" style=""></span>TSF (mm). All anthropometric measurements were done in duplicate by the same investigator, and the mean values were taken for the analysis.</p><p id="par0050" class="elsevierStylePara elsevierViewall">Handgrip strength was performed on the dominant arm or non-fistula side, using a manual dynamometer (Baseline<span class="elsevierStyleSup">®</span> Hydraulic Hand Dynamometer – 12-0240; Irvington, NY, USA) device. All anthropometric measures were repeated three times and the mean value was taken for the analysis.</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Body composition analysis</span><p id="par0055" class="elsevierStylePara elsevierViewall">Monofrequency BIA was determined on the non-dominant side of the body, in the post-absorptive state, injecting 800<span class="elsevierStyleHsp" style=""></span>μA alternating sinusoidal current with a standard tetrapolar technique (BIA 101 Impedance Analyzer; Akern, Firenze, Italy). BIA was performed at fasting state in the supine position<a class="elsevierStyleCrossRefs" href="#bib0285"><span class="elsevierStyleSup">21,22</span></a> with disposable electrodes (BiatrodesTM 100'S; Akern). Body composition analysis by gender, age, BW and height was individually measured at 50<span class="elsevierStyleHsp" style=""></span>kHz, which resistance and reactance were obtained.</p><p id="par0060" class="elsevierStylePara elsevierViewall">The BIA-derived variables [(exchange Na/K, percentage of total body water (TBW%), extracellular body water (ECW%), intracellular body water (ICW%), body cell mass (BCM%), fat mass (FM%), muscle mass (MM%), fat-free mass (FFM%) and values of phase angle (PA)], were estimated by BIA<span class="elsevierStyleSup">®</span> software. This method was previously validated in CKD<a class="elsevierStyleCrossRef" href="#bib0395"><span class="elsevierStyleSup">11</span></a> and dialysis patients.<a class="elsevierStyleCrossRef" href="#bib0295"><span class="elsevierStyleSup">23</span></a></p></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Laboratory parameters</span><p id="par0065" class="elsevierStylePara elsevierViewall">Early morning blood samples were drawn from every patient in a 12-h overnight fasting conditions. Serum albumin (s-albumin) using bromocresol green method was measured using an automated analyzer (Abbot, Aeroset<span class="elsevierStyleSup">®</span>, Diamond Diagnosis, Holliston, MA).<a class="elsevierStyleCrossRef" href="#bib0300"><span class="elsevierStyleSup">24</span></a> Variation coefficients were lower than 2%. CRP (<span class="elsevierStyleItalic">no-high sesnsitivity</span>), was measured by immunoturbidimetry (Roche/Hitachi 904<span class="elsevierStyleSup">®</span>/Model P: ACN 218, Roche Diagnostics, Basel, Switzerland). S-CRP was logarithmically transformed to normality using the natural log (Ln s-CRP).</p></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Statistical analysis</span><p id="par0070" class="elsevierStylePara elsevierViewall">The statistical analyses were carried out using the SPSS v.20 software and the results expressed as the arithmetic mean and standard deviation. Correlation between continuous variables by Pearson test was calculated. The normality and homoscedasticity of the data were verified by the Kolmogorov–Smirnov and Shapiro–Wilk test, respectively. The analysis of variance (ANOVA) followed by the Bonferroni and Tukey <span class="elsevierStyleItalic">post-hoc</span> test was used when the variables showed a normal distribution and Welch and Brown–Forsythe when the variables were non-parametric. Analysis of covariance (ANCOVA) was used to test extent variations of gender as a covariate. Linear regression analysis was used to test the effect of nPna on other variables. The level of significance was set at <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05.</p></span></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Results</span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Demographic characteristics</span><p id="par0075" class="elsevierStylePara elsevierViewall">A total of 134 CKD patients participated in the study. The aged population was 70.9<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>13.11 years, 68.7% were men and the primary etiology of CKD was diabetes mellitus (35.8%) (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>). Most of the patients were in CKD stage 3 (34.5%) and stage 4 (56.5%), with mean nPna values of 0.84<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.21 and 0.93<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.21<span class="elsevierStyleHsp" style=""></span>g/kg/day, respectively (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.033).</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Correlations</span><p id="par0080" class="elsevierStylePara elsevierViewall">nPna was positively and significantly associated with e-GFR (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.19; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05), BCM% (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.32; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.001), MM% (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.42; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.001) and s-albumin (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.26; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.01), whilst inverse correlation was observed between nPna and exchange Na/K (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.18; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05). Not significant correlation between nPna and Ln s-CRP was found.</p></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Patient characteristics according to dietary protein intake</span><p id="par0085" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a> shows laboratory data according to nPna groups of daily protein intake. Of the 134 CKD patients, 43 patients (32.1%) had nPna<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.8<span class="elsevierStyleHsp" style=""></span>g/kg BW/day (G<span class="elsevierStyleInf">1</span>), 53 patients (39.2%) with nPna of 0.8–1<span class="elsevierStyleHsp" style=""></span>g/kg BW/day (G<span class="elsevierStyleInf">2</span>) and 38 patients (28.3%) had a nPna<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>1<span class="elsevierStyleHsp" style=""></span>g/kg BW/day (G<span class="elsevierStyleInf">3</span>). Patients with lower nPna (G<span class="elsevierStyleInf">1</span>), were older and showed also significantly higher proteinuria in comparison with mean values of nPna<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>0.8<span class="elsevierStyleHsp" style=""></span>g/kg BW/day. Mean values of s-albumin showed significantly differences between nPna groups (G<span class="elsevierStyleInf">1</span>, G<span class="elsevierStyleInf">2</span>, G<span class="elsevierStyleInf">3</span>), being highlighted mean values of albumin level >4<span class="elsevierStyleHsp" style=""></span>g/dL in the three groups (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.015). Ln s-CRP tended in a non-significant manner to be higher levels with nPna<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>1<span class="elsevierStyleHsp" style=""></span>g/kg BW/day. The prevalence of PEW was 15% in this study.</p><p id="par0090" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a> shows anthropometric, nutritional and body composition data according to nPna groups of daily protein intake. Anthropometric measures as BW, BMI and TSF were significantly higher within nPna<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>1<span class="elsevierStyleHsp" style=""></span>g/kg/day group. MAMC%, tended significantly to be decreased across nPna groups but, being within normal range. As regards the BIA-derived hydration parameters, patients with low protein intake had higher values of exchange Na/K (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>0.05), and ECW% (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.01), whereas TBW% (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05), ICW% (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.01) and s-albumin (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.015) were also significantly lower with nPna<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.8<span class="elsevierStyleHsp" style=""></span>g/kg BW/day (G<span class="elsevierStyleInf">1</span>). Low protein intake (G<span class="elsevierStyleInf">1</span>) showed significantly lower FFM%, MM% and PA values, but not significant differences with handgrip strength (kg) were found. Interestingly, MM% was higher with nPna values ≥0.8<span class="elsevierStyleHsp" style=""></span>g/kg BW/day.</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0095" class="elsevierStylePara elsevierViewall">In a sub-analysis data, robust test of equal means showed significant differences with BCM%, ECW%, FFM%, MM% and s-albumin in the sample (at least, <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.01). Gender inter-subjects’ analysis showed significant differences with BW, FFM%, TSF and MAMC%.</p></span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Protein intake as a predictor of nutritional and body composition status in chronic kidney disease patients</span><p id="par0100" class="elsevierStylePara elsevierViewall">In the linear regression analysis adjusted by gender, age and BW (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>), parameters as resistance, BCM%, MM%, and s-albumin were significantly predictors of nPna as a surrogate marker of daily protein intake (<span class="elsevierStyleItalic">R</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.51; <span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.29; <span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span> adjusted: 0.23; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.001).</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia></span></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0140">Discussion</span><p id="par0105" class="elsevierStylePara elsevierViewall">The results of this study revealed that low dietary protein intake in CKD patients on stages 3, 4–5, was associated with loss of muscle mass even in patients receiving dietary counseling and nutritional follow-up at the advanced-CKD unit. In this study, older ages and lower e-GFR in CKD patients showed lower protein intake and loss of muscle mass, especially in women.</p><p id="par0110" class="elsevierStylePara elsevierViewall">nPna an indirect measure of protein intake was showed as a strong and independent predictor of morbidity and mortality in CKD patients<a class="elsevierStyleCrossRef" href="#bib0305"><span class="elsevierStyleSup">25</span></a> and dialysis patients.<a class="elsevierStyleCrossRef" href="#bib0415"><span class="elsevierStyleSup">26</span></a> Clinical practice guideline for CKD patients,<a class="elsevierStyleCrossRefs" href="#bib0375"><span class="elsevierStyleSup">4–7</span></a> defined as those with e-GFR<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>30<span class="elsevierStyleHsp" style=""></span>mL/min/1.73<span class="elsevierStyleHsp" style=""></span>m<span class="elsevierStyleSup">2</span>, have recommended reducing dietary protein intake to 0.8<span class="elsevierStyleHsp" style=""></span>g/kg/day in adults both with and without diabetes to slow disease progression, and achieve/maintain adequate s-albumin concentration and nutritional status. In the current study, overall nPna values were slightly increased, but only 57% of the eligible CKD patients correctly achieved the low protein intake reduction. Patients with CKD on stage 3, had mean nPna values closed to current protein intake recommendation, whilst advanced CKD on stages 4–5, showed higher daily protein intake. In this study, diet adherence of usual nutritional recommendation was low, being observed a 67.9% of CKD patients with nPna<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>0.8<span class="elsevierStyleHsp" style=""></span>g/kg BW/day. However, a dietary protein intake <0.8<span class="elsevierStyleHsp" style=""></span>g/kg BW/day (G<span class="elsevierStyleInf">1</span>), showed significantly depletion of MAMC, BCM%, FFM% and PA in a similar way compared with one another nPna categories. These findings are of importance because the loss of muscle mass and wasting has been demonstrated to be associated with poor outcomes in CKD patients.<a class="elsevierStyleCrossRefs" href="#bib0420"><span class="elsevierStyleSup">27,28</span></a></p><p id="par0115" class="elsevierStylePara elsevierViewall">PEW is common in CKD patients and is associated with a subsequent increased risk of mortality.<a class="elsevierStyleCrossRef" href="#bib0370"><span class="elsevierStyleSup">3</span></a> Dietary protein and energy intake may be masked in patients with advanced CKD due to uremic anorexia, inter-current illness, systemic inflammation, fluid overload and/or excessive dietary protein restriction. S-albumin concentration and BMI are the most often used indicators of nutritional assessment in daily clinical practice<a class="elsevierStyleCrossRefs" href="#bib0325"><span class="elsevierStyleSup">29,30</span></a> However, both are influenced by several non-nutritional factors, including proteinuria, fluid overload and inflammation statuses.<a class="elsevierStyleCrossRefs" href="#bib0335"><span class="elsevierStyleSup">31,32</span></a> In the current study, PEW was assessed by MIS, as a nutritional screening tool previously validated in CKD and dialysis patients together with commonly used nutritional-inflammatory markers. Overall, only 15% of CKD patients were wasted. In accordance with previous studies,<a class="elsevierStyleCrossRefs" href="#bib0430"><span class="elsevierStyleSup">33,34</span></a> the prevalence of PEW in the study was low compared with others.<a class="elsevierStyleCrossRefs" href="#bib0435"><span class="elsevierStyleSup">35,36</span></a> Furthermore, despite of low e-GFR (mean 19.4<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.7<span class="elsevierStyleHsp" style=""></span>mL/min/1.73<span class="elsevierStyleHsp" style=""></span>m<span class="elsevierStyleSup">2</span>), a common used marker of protein turnover such as s-albumin was ≥4<span class="elsevierStyleHsp" style=""></span>g/dL in all nPna groups. Therefore, a routine nutritional screening (i.e. MIS) could decreased the contribution of each indicator by combining s-albumin and BMI. In fact, this study found significantly positive correlation between nPna with e-GFR, BCM%, MM% and s-albumin, but not Ln s-CRP and BMI. These findings suggest that a multifactorial approach in CKD patients is mandatory.</p><p id="par0120" class="elsevierStylePara elsevierViewall">Additional methods such as BIA and anthropometric measures may be also clinically useful to assess nutritional status. Body composition analysis in patients with CKD are characterized by high content of ECW associated with sodium retention and a decreased of BCM, both related with well-known causes as inflammation, fluid overload and wasting.<a class="elsevierStyleCrossRefs" href="#bib0290"><span class="elsevierStyleSup">22,31,32</span></a> In this study, exchange Na/K and ECW% were significantly higher as protein intake was <0.8<span class="elsevierStyleHsp" style=""></span>g of protein/kg BW/day. Additionally, BIA-derived parameters such as FFM% and MM% were also diminished. Linear regression analysis showed that BIA-measures as resistance, MM% and s-albumin were independent predictors of nPna in the study population, but an inverse relation was found with BCM%. These findings suggest that a high protein intake could worsen renal function and, consequently the homeostasis of internal environment. Nevertheless, parameters such as exchange Na/K, FFM% and FM% were not found significant predictors of nPna in the linear regression analysis. Thus, in addition to common used nutritional markers, data suggest that body composition parameters should be taken into account in the nutritional monitoring, in patients with CKD. In this clinical setting, a “tailored diet prescription” considering gender-aged and body composition differences is required.</p><p id="par0125" class="elsevierStylePara elsevierViewall">Prescription of a KA/EAA supplemented VLPD may be considered in well-nourished not-inflamed CKD patients aimed to preserve the renal function and metabolic disturbances related to uremic milieu. However, in wasted patients with alterations of fluid status and body composition parameters may be further considered dietary protein intake definition. There are potential limitations to be taking into account in this study. The sample size of this study due to its nature as a single-center cross-sectional study may reduce the generalizability of the findings. First, there are fluctuations in nPna from day to day caused by changes in daily protein intake or endogenous protein catabolism related with e-GFR value in CKD patients. Monitoring sequentially the body composition measures (i.e. muscle mass), could provide early nutritional interventions. Second, for nPna to accurately estimate protein intake, the patient's protein metabolism should be at equilibrium or nearly so at the time of measurement. This condition is not always met, particularly in CKD patients with many comorbidities, inflammation or acute disease states. In this study, eligible CKD patients were stabilized for at least 3 months before enrolment. Third, nPna could be masked usual dietary protein intake in wasted-inflamed patients. Assessment of nutritional-inflammatory status by validated nutritional tools, could early diagnose inadequate food intake and nutritional related-problems (i.e. PEW) in CKD patients.</p><p id="par0130" class="elsevierStylePara elsevierViewall">In conclusion, controlled protein intake is one of the mainstays of CKD patients. A low protein intake in patients with CKD stages 3, 4–5, was associated with muscle wasting, even in patients receiving dietary advice and nutritional follow-up in the advanced-CKD unit. The loss of muscle mass appears as an early indicator of being wasting. Factors such as advanced age and loss of eGFR, showed lower protein intake and were associated with muscle loss, especially in women. In addition, of standard medical care, assessment of nutritional status and body composition should be included to prevent, diagnose and/or treat PEW.</p><p id="par0135" class="elsevierStylePara elsevierViewall">Further longitudinal studies are required for evaluating the contribution of different protein intake in uremic symptoms, nutritional status, body composition and CKD progression.</p></span><span id="sec0080" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0145">Authors’ contributions</span><p id="par0140" class="elsevierStylePara elsevierViewall">GB designed the study, collected the data, analyzed and interpreted the results, and drafted the manuscript. AN collected the data and drafted the manuscript. MR, analyzed, interpreted the results, and drafted the manuscript. YC analyzed and interpreted the statistical results. JST analyzed, interpreted the results, and drafted the manuscript. All of the authors read and approved the final version of manuscript.</p></span><span id="sec0085" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0150">Declarations</span><p id="par0145" class="elsevierStylePara elsevierViewall">None.</p></span><span id="sec0090" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0155">Conflict of interests</span><p id="par0150" class="elsevierStylePara elsevierViewall">The authors declare that they have no conflict of interests.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:14 [ 0 => array:3 [ "identificador" => "xres1126794" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Introduction" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Method" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusion" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1060678" "titulo" => "Keywords" ] 2 => array:2 [ "identificador" => "xpalclavsec1060679" "titulo" => "Abbreviations" ] 3 => array:3 [ "identificador" => "xres1126793" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Introducción" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Método" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusión" ] ] ] 4 => array:2 [ "identificador" => "xpalclavsec1060677" "titulo" => "Palabras clave" ] 5 => array:2 [ "identificador" => "sec0005" "titulo" => "Background" ] 6 => array:3 [ "identificador" => "sec0010" "titulo" => "Patients and methods" "secciones" => array:7 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Study design" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Clinical assessment" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "Nutritional assessment" ] 3 => array:2 [ "identificador" => "sec0030" "titulo" => "Anthropometric measurements" ] 4 => array:2 [ "identificador" => "sec0035" "titulo" => "Body composition analysis" ] 5 => array:2 [ "identificador" => "sec0040" "titulo" => "Laboratory parameters" ] 6 => array:2 [ "identificador" => "sec0045" "titulo" => "Statistical analysis" ] ] ] 7 => array:3 [ "identificador" => "sec0050" "titulo" => "Results" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "sec0055" "titulo" => "Demographic characteristics" ] 1 => array:2 [ "identificador" => "sec0060" "titulo" => "Correlations" ] 2 => array:2 [ "identificador" => "sec0065" "titulo" => "Patient characteristics according to dietary protein intake" ] 3 => array:2 [ "identificador" => "sec0070" "titulo" => "Protein intake as a predictor of nutritional and body composition status in chronic kidney disease patients" ] ] ] 8 => array:2 [ "identificador" => "sec0075" "titulo" => "Discussion" ] 9 => array:2 [ "identificador" => "sec0080" "titulo" => "Authors’ contributions" ] 10 => array:2 [ "identificador" => "sec0085" "titulo" => "Declarations" ] 11 => array:2 [ "identificador" => "sec0090" "titulo" => "Conflict of interests" ] 12 => array:2 [ "identificador" => "xack383529" "titulo" => "Acknowledgements" ] 13 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2017-12-23" "fechaAceptado" => "2018-06-07" "PalabrasClave" => array:2 [ "en" => array:2 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1060678" "palabras" => array:7 [ 0 => "Protein intake" 1 => "Normalized protein nitrogen appearance" 2 => "Muscle mass" 3 => "Protein-energy wasting" 4 => "Body composition" 5 => "Bioelectrical impedance" 6 => "Chronic kidney disease" ] ] 1 => array:4 [ "clase" => "abr" "titulo" => "Abbreviations" "identificador" => "xpalclavsec1060679" "palabras" => array:28 [ 0 => "BCM%" 1 => "BIA" 2 => "BIVA" 3 => "BMI" 4 => "BW" 5 => "CKD" 6 => "CRP" 7 => "ECW" 8 => "FFM%" 9 => "FM" 10 => "e-GFR" 11 => "ICW%" 12 => "KA" 13 => "Ln s-CRP" 14 => "LPD" 15 => "MAMC%" 16 => "MIS" 17 => "MM%" 18 => "nPna" 19 => "PA" 20 => "PEW" 21 => "RRT" 22 => "SBW%" 23 => "s-albumin" 24 => "s-CRP" 25 => "TBW%" 26 => "TSF" 27 => "VLPD" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1060677" "palabras" => array:7 [ 0 => "Ingesta de proteínas" 1 => "Aparición de nitrógeno proteico normalizado" 2 => "Masa muscular" 3 => "Pérdida de energía proteica" 4 => "Composición corporal" 5 => "Impedancia bioeléctrica" 6 => "Enfermedad renal crónica" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Introduction</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">A controlled protein intake has shown beneficial effects to preserve renal function and nutritional status in chronic kidney disease (CKD) patients. This study aimed to analyze usual dietary protein intake and its potential contribution to body composition in CKD patients in stages 3–5.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Method</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Cross-sectional study in 134 CKD patients in stages 3–5 (mean e-GFR: 19.4<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.7<span class="elsevierStyleHsp" style=""></span>ml/min/1.73<span class="elsevierStyleHsp" style=""></span>m<span class="elsevierStyleSup">2</span>; males 68.7% and primary CKD etiology was diabetes mellitus, 35.8%). Demographic, clinical and nutritional parameters were evaluated. Normalized protein nitrogen appearance (nPNA), was used as a surrogate marker of dietary protein intake. The sample was classified into three nPNA groups (G<span class="elsevierStyleInf"><span class="elsevierStyleItalic">n</span></span>): G<span class="elsevierStyleInf">1</span>: <0.8<span class="elsevierStyleHsp" style=""></span>g/kg/day; G<span class="elsevierStyleInf">2</span>: 0.8–1<span class="elsevierStyleHsp" style=""></span>g/kg/day and, G<span class="elsevierStyleInf">3</span>: ≥1<span class="elsevierStyleHsp" style=""></span>g/kg/day. Assessment of nutritional status using the malnutrition-inflammation score (MIS), anthropometric measures and laboratory parameters. Analysis of body composition and hydration status by bioelectrical impedance analysis (BIVA-101-RJL system). Statistical analysis by SPSS v.20.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Overall mean nPNA values were 0.91<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.23<span class="elsevierStyleHsp" style=""></span>g of protein/kg BW/day and only 32.1% had a dietary protein intake <0.8<span class="elsevierStyleHsp" style=""></span>g of protein/kg BW/day. Most of the CKD patients (65.5%) were in stages 4 or 5. Prevalence of protein–energy–wasting (PEW) syndrome measured by MIS was 15%. By analyzing differences between nPNA groups, body weight (BW), BMI and triceps-skinfold (TSF) thickness were significantly higher in the group with nPNA ≥1<span class="elsevierStyleHsp" style=""></span>g/kg BW/day (G<span class="elsevierStyleInf">3</span>), whereas a significant inverse relationship was found with the percentages of body cell mass (BCM%), fat-free mass (FFM%), muscle mass (MM%) and phase angle (PA) in the group with the lowest nPNA (G<span class="elsevierStyleInf">1</span>). Analysis of gender among subjects showed significant differences with BW, FFM%, TSF and mid-arm muscle circumference (MAMC%). Linear regression analysis showed that resistance, BCM%, MM%, and serum albumin were significant predictors of nPNA as a surrogate marker of daily protein intake (<span class="elsevierStyleItalic">R</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.51; <span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.29; <span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span> adjusted<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.23; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.001).</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusion</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Controlled protein intake is one of the cornerstones of treatment in CKD patients. A low protein intake in patients with CKD stages 3 and 4–5 was associated with loss of muscle mass in the advanced-CKD unit. The loss of muscle mass appears as an early indicator of nutritional comprised. Factors such, elderly age and loss of eGFR, showed lower protein intake and were associated with muscle loss, especially in women. Further longitudinal studies are required to evaluate the contribution of different protein intakes to uremic symptoms, nutritional status, body composition and CKD progression.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Introduction" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Method" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusion" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Introducción</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">El control de la ingesta proteica ha mostrado efectos beneficiosos preservando la función renal y el estado nutricional en pacientes con enfermedad renal crónica (ERC). El objetivo del estudio fue analizar la ingesta habitual de proteína, y su potencial contribución en la composición corporal en los pacientes con ERC estadios 3-5.</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Método</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Estudio observacional transversal en 134 pacientes con ERC estadios 3-5 (media e-TFG: 19,4<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8,7<span class="elsevierStyleHsp" style=""></span>ml/min/1,73<span class="elsevierStyleHsp" style=""></span>m<span class="elsevierStyleSup">2</span>; varones: 68,7% y etiología primaria de la ERC, diabetes mellitus: 35,8%). Se evaluaron parámetros demográficos, clínicos y nutricionales. La aparición de nitrógeno proteico normalizado (nPNA) se utilizó como marcador sustituto de la ingesta proteica. La muestra fue clasificada según el nPNA en 3 grupos (G<span class="elsevierStyleInf">n</span>): G<span class="elsevierStyleInf">1</span>: < 0,8<span class="elsevierStyleHsp" style=""></span>g/kg/día; G<span class="elsevierStyleInf">2</span>: 0,8-1<span class="elsevierStyleHsp" style=""></span>g/kg/día y G<span class="elsevierStyleInf">3</span>:<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>1<span class="elsevierStyleHsp" style=""></span>g/kg/día. Valoración nutricional por la escala de malnutrición-inflamación (MIS), medidas antropométricas y parámetros de laboratorio. Análisis de composición corporal y del patrón de hidratación mediante bioimpedancia eléctrica (BIVA-101<span class="elsevierStyleSup">®</span>, RJL System). Análisis estadístico por SPSS<span class="elsevierStyleSup">®</span> v.20.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Globalmente los valores medios de nPNA fueron 0,91<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0,23<span class="elsevierStyleHsp" style=""></span>g proteína/kg peso corporal/día, y tan solo el 32,1% tenían una ingesta proteica <<span class="elsevierStyleHsp" style=""></span>0,8<span class="elsevierStyleHsp" style=""></span>g de proteína/kg peso corporal/día. El 65,5% de los pacientes con ERC estaban en estadios 4 y 5. La prevalencia de síndrome de desgaste proteico-energético (SDP) medido por MIS era del 15%. Analizando las diferencias con el nPNA entre los grupos, el peso corporal, el índice de masa corporal y el pliegue tricipital (PCT), eran significativamente mayores en el grupo con nPNA<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>1<span class="elsevierStyleHsp" style=""></span>g/kg peso corporal/día (G<span class="elsevierStyleInf">3</span>), mientras que se encontró relación inversa significativa con los porcentajes de la masa celular (MC%), de la masa magra (MMagra%), de la masa muscular (MM%) y del ángulo de fase (AF) en el grupo con menor nPNA (G<span class="elsevierStyleInf">1</span>). El análisis del género entre los sujetos mostró diferencias significativas con el peso corporal, MMagra%, PCT y la circunferencia muscular del brazo (CMB%). El análisis de regresión lineal demostró que la resistencia MC%, MM% y la albúmina sérica eran predictores significativos del nPNA como marcador de la ingesta proteica habitual (R<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,51; R<span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,29; R<span class="elsevierStyleSup">2</span> ajustado<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0,23; p<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0,001).</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusión</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">El control de la ingesta proteica es uno de los pilares del tratamiento en los pacientes con ERC. La dieta hipoproteica en pacientes con ERC estadios 3-5 se asoció con una pérdida de la masa muscular en la unidad de ERC avanzada. La pérdida de masa muscular aparece como un indicador temprano de compromiso nutricional. La edad avanzada y la pérdida de TFG-e se asociaron con menor ingesta proteica y pérdida de masa muscular asociada, especialmente en mujeres. Nuevos estudios longitudinales, son necesarios para evaluar la contribución de la ingesta de proteínas en los síntomas urémicos, el estado nutricional, la composición corporal y la progresión de la ERC.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Introducción" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Método" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusión" ] ] ] ] "multimedia" => array:4 [ 0 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">e-GFR, estimated glomerular filtration rate measured by CKD-EPI equation; Ln s-CRP, natural logarithmic of C-reactive protein; nPna, normalized protein nitrogen appearance. PEW, protein-energy wasting.</p><p id="spar0100" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleSup">*</span><span class="elsevierStyleItalic">p</span>-values are based on Chi-square tests or ANOVA-tests according to cut-off points of normalized protein nitrogen appearance (nPna).</p><p id="spar0055" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleSup">#</span>Daily protein intake measured by nPna were defined in different groups as follows: G1: nPna<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.8<span class="elsevierStyleHsp" style=""></span>g/kg BW/day; G2: nPna 0.8–1<span class="elsevierStyleHsp" style=""></span>g/kg<span class="elsevierStyleHsp" style=""></span>BW/day and; G3: nPna<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>1<span class="elsevierStyleHsp" style=""></span>g/kg BW/day. <span class="elsevierStyleSup">a,b,c</span><span class="elsevierStyleItalic">p</span>-values within the means of nPna bearing different letters were significantly different; <span class="elsevierStyleSup">a</span><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05, <span class="elsevierStyleSup">b</span><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.01, <span class="elsevierStyleSup">c</span><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.001 (Brown–Forsythe test for equal means).</p><p id="spar0060" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleSup">†</span>PEW was defined by MIS score ≥5 points.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Variables \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Global \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">G<span class="elsevierStyleInf">1</span>: nPna<br><0.8<span class="elsevierStyleHsp" style=""></span>g/kg/day \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">G<span class="elsevierStyleInf">2</span>: nPna 0.8–1<span class="elsevierStyleHsp" style=""></span>g/kg/day \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">G<span class="elsevierStyleInf">3</span>: nPna<br>≥1<span class="elsevierStyleHsp" style=""></span>g/kg/day \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">p</span>-value<span class="elsevierStyleSup">*</span> \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">n</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">134 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">43 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">53 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">38 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">nPna (g/kg BW/day) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.91<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.23 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.65<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.08 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.89<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.21 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.16<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.16 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Age (years) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">71<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>13.11 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">73.58<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>12.58 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">70.22<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>12.27 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">69.21<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>14.79 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.29 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Men, <span class="elsevierStyleItalic">n</span> (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">92 (68.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">25 (17.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">40 (29.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">27 (20.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Diabetes, <span class="elsevierStyleItalic">n</span> (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">48 (36.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">24 (17.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">28 (20.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3 (12.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.73 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">e-GFR (mL/min) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">19.4<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">16.34<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.95 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">17.43<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>5.73 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">17.73<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>5.53 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.16 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Hemoglobin (g/L) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">12.25<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">11.86<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.14 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">12.19<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.28 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">12.50<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.25 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.076 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">s-Albumin (g/dL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">4.18<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.42 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">4.04<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.46 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">4.20<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.44 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">4.11<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.42 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.015<span class="elsevierStyleSup">b</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Total Lymphocytes count (×10<span class="elsevierStyleSup">3</span>/mm<span class="elsevierStyleSup">3</span>) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2026.4<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1133.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1897.5<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>881.19 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2142<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1529 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2016.87<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>744.23 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.44 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">s-Creatinine (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3.27<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.21 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3.39<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.08 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3.54<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.17 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3.42<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.16 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.94 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Ln s-CRP \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.84<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.13 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.75<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.09 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.87<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.99 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−1.1<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.38 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Proteinuria (mg/dL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">58.4<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>69.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">82.34<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>72.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">49.5<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>63.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">44.70<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>70.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.032 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">PEW,<span class="elsevierStyleSup">†</span><span class="elsevierStyleItalic">n</span> (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">20 (15) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">7 (5.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">8 (6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">5 (3.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.33 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1920594.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Demographic and laboratory data in 134 CKD patients stages, 3–5 according to daily dietary protein intake.#.</p>" ] ] 1 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at2" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">BMI, body mass index; ECW, extracellular water; FM, fat mass; FFM, fat free mass; ICW, intracellular water; MAMC, middle-arm muscle circumference; MIS, Malnutrition-Inflammation Score; TBW, total body water; TSF, triceps skinfold thickness.</p><p id="spar0105" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleSup">*</span>p-values are based on Chi-square tests or ANOVA-tests according to cut-off points of normalized protein nitrogen appearance (nPna).</p><p id="spar0080" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleSup">#</span>Daily protein intake measured by nPna were defined in different groups as follows: G<span class="elsevierStyleInf">1</span>: nPna < 0. 8<span class="elsevierStyleHsp" style=""></span>g/kg BW/day; G<span class="elsevierStyleInf">2</span>: nPna 0.8–1<span class="elsevierStyleHsp" style=""></span>g/kg BW/day and; G<span class="elsevierStyleInf">3</span>: nPna ≥ 1<span class="elsevierStyleHsp" style=""></span>g/kg BW/day. <span class="elsevierStyleSup">a,b,c</span><span class="elsevierStyleItalic">p</span>-values within the means of nPna bearing different letters were significantly different; <span class="elsevierStyleSup">a</span><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05, <span class="elsevierStyleSup">b</span><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.01, <span class="elsevierStyleSup">c</span><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.001 (Brown–Forsythe test for equal means).</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Variables \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Global \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">G<span class="elsevierStyleInf">1</span>: nPna<br><0.8<span class="elsevierStyleHsp" style=""></span>g/kg/day \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">G<span class="elsevierStyleInf">2</span>: nPna<br>0.8–1<span class="elsevierStyleHsp" style=""></span>g/kg/day \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">G<span class="elsevierStyleInf">3</span>: nPna<br>≥1<span class="elsevierStyleHsp" style=""></span>g/kg/day \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">p</span>-value<span class="elsevierStyleSup">*</span> \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Body weight (kg) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">74.41<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>15.13 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">77.78<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>15.06 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">76.32<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>13.99 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">69.32<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>15.96 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.037<span class="elsevierStyleSup">a</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Standard Body Weight (kg) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">68.08<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.26 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">67.77<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>7.28 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">70.01<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.24 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">68.62<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>10.18 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.301 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">BMI (kg/m<span class="elsevierStyleSup">2</span>) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">27.19<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.99 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">28.42<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>5.23 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">27.40<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.28 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">25.56<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.67 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.012<span class="elsevierStyleSup">b</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">TSF (mm) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">17.84<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>9.35 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">20.02<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>11.14 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">16.79<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>7.81 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14.75<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>7.09 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.016<span class="elsevierStyleSup">b</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">MAMC (cm) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">27.9<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">28.96<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.86 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">28.14<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>3.62 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">26.58<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.09 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.041<span class="elsevierStyleSup">a</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">MAMC (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">130.2<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>22.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">136.1<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>27.44 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">130.97<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>18.49 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">122.59<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>18.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.024<span class="elsevierStyleSup">a</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Handgrip strength right (kg) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">25.4<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>9.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">24.1<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>9.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">26.9<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>9.35 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">25.1<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>9.58 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.34 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Handgrip strength left (kg) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">23.8<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>9.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">22.3<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.69 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">24.8<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>9.32 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">24.2<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>9.19 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.41 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Exchange Na/K \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.46<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.53 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.58<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.66 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.47<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.52 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.45<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.42 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.463 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Body cell mas (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">37.3<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>9.34 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">34.1<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.17 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">37.7<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>9.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">40.5<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.45 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.008<span class="elsevierStyleSup">b</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Total body water (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">54.4<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>7.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">52.90<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.58 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">55.77<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">55.63<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.91 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.037 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">ECW (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">56.45<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.72 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">59.86<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.57 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">55.99<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.57 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">55.10<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.51 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.007<span class="elsevierStyleSup">b</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">ICW (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">43.51<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.73 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">40.13<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.57 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">44<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.57 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">44.79<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.008<span class="elsevierStyleSup">b</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Fat mass (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">31<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>9.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">33.46<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>10.91 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">29.50<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.96 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">28.80<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>7.89 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.012 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Fat-free mass (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">68.9<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>9.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">66.31<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>11.03 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">70.49<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.96 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">71.19<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.009<span class="elsevierStyleSup">b</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Muscle mass (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">33.78<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>7.71 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">29.68<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>5.06 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">34.82<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>8.29 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">55.77<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001<span class="elsevierStyleSup">c</span> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Phase angle (°) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.17<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.23 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.77<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.14 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.26<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.25 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.27<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.24 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.033 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1920593.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">Anthropometric, nutritional and body composition data in 134 CKD patients stages, 3–5 according to daily dietary protein intake.<span class="elsevierStyleSup">#</span>.</p>" ] ] 2 => array:8 [ "identificador" => "tbl0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at3" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0095" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleSup">#</span>Normalized nitrogen protein appearance as a dependent variable in a linear regression model adjusted by gender, age and body weight. 95%CI, confidence interval. <span class="elsevierStyleItalic">R</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.53; <span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.29; <span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span> adjusted<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.23.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Variable \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Coefficient \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">95%CI \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">p</span>-value \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Resistance \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.276 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.00 to 0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.01 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Exchange Na/K \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.445 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.136 to 0.522 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.24 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Body cell mass (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−1.996 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.008 to −0.092 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.019 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Fat-free mass (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.574 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.026 to 0.054 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.485 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Muscle mass (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.724 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.028 to 0.139 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.004 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Fat mass (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.161 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.000 to 0.107 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.050 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">s-Albumin (g/dL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.203 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.012 to 0.209 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.028 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Constant \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−8.63 to 0.97 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.117 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1920592.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0090" class="elsevierStyleSimplePara elsevierViewall">Normalized nitrogen protein appearance in a linear regression analysis as likely predictor in CKD stages 3–5 patients.<span class="elsevierStyleSup">#</span>.</p>" ] ] 3 => array:5 [ "identificador" => "eq0005" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "nPna=(diuresis×urine   urea/2.03)+(body   weight×0.031)×6.25body   weight" "Fichero" => "STRIPIN_si1.jpeg" "Tamanyo" => 4015 "Alto" => 29 "Ancho" => 376 ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0015" "bibliografiaReferencia" => array:36 [ 0 => array:3 [ "identificador" => "bib0185" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "The effect of dietary protein restriction on the progression of diabetic and nondiabetic renal diseases: a meta-analysis" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:5 [ 0 => "M.T. 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año/Mes | Html | Total | |
---|---|---|---|
2024 Noviembre | 17 | 14 | 31 |
2024 Octubre | 75 | 55 | 130 |
2024 Septiembre | 38 | 45 | 83 |
2024 Agosto | 57 | 86 | 143 |
2024 Julio | 50 | 34 | 84 |
2024 Junio | 78 | 56 | 134 |
2024 Mayo | 70 | 35 | 105 |
2024 Abril | 64 | 52 | 116 |
2024 Marzo | 63 | 45 | 108 |
2024 Febrero | 49 | 52 | 101 |
2024 Enero | 41 | 28 | 69 |
2023 Diciembre | 33 | 42 | 75 |
2023 Noviembre | 58 | 56 | 114 |
2023 Octubre | 92 | 55 | 147 |
2023 Septiembre | 294 | 37 | 331 |
2023 Agosto | 220 | 30 | 250 |
2023 Julio | 74 | 30 | 104 |
2023 Junio | 85 | 34 | 119 |
2023 Mayo | 94 | 43 | 137 |
2023 Abril | 52 | 34 | 86 |
2023 Marzo | 99 | 33 | 132 |
2023 Febrero | 54 | 36 | 90 |
2023 Enero | 47 | 43 | 90 |
2022 Diciembre | 85 | 46 | 131 |
2022 Noviembre | 63 | 66 | 129 |
2022 Octubre | 100 | 64 | 164 |
2022 Septiembre | 53 | 46 | 99 |
2022 Agosto | 44 | 55 | 99 |
2022 Julio | 51 | 67 | 118 |
2022 Junio | 53 | 69 | 122 |
2022 Mayo | 37 | 50 | 87 |
2022 Abril | 54 | 60 | 114 |
2022 Marzo | 48 | 61 | 109 |
2022 Febrero | 38 | 62 | 100 |
2022 Enero | 45 | 58 | 103 |
2021 Diciembre | 55 | 63 | 118 |
2021 Noviembre | 49 | 43 | 92 |
2021 Octubre | 58 | 59 | 117 |
2021 Septiembre | 45 | 51 | 96 |
2021 Agosto | 30 | 52 | 82 |
2021 Julio | 45 | 60 | 105 |
2021 Junio | 36 | 56 | 92 |
2021 Mayo | 52 | 69 | 121 |
2021 Abril | 95 | 120 | 215 |
2021 Marzo | 70 | 86 | 156 |
2021 Febrero | 70 | 56 | 126 |
2021 Enero | 46 | 62 | 108 |
2020 Diciembre | 37 | 31 | 68 |
2020 Noviembre | 26 | 33 | 59 |
2020 Octubre | 41 | 39 | 80 |
2020 Septiembre | 56 | 41 | 97 |
2020 Agosto | 62 | 38 | 100 |
2020 Julio | 57 | 43 | 100 |
2020 Junio | 48 | 47 | 95 |
2020 Mayo | 77 | 39 | 116 |
2020 Abril | 51 | 47 | 98 |
2020 Marzo | 57 | 38 | 95 |
2020 Febrero | 72 | 50 | 122 |
2020 Enero | 88 | 45 | 133 |
2019 Diciembre | 64 | 25 | 89 |
2019 Noviembre | 72 | 60 | 132 |
2019 Octubre | 85 | 53 | 138 |
2019 Septiembre | 56 | 38 | 94 |
2019 Agosto | 42 | 30 | 72 |
2019 Julio | 70 | 41 | 111 |
2019 Junio | 59 | 66 | 125 |
2019 Mayo | 48 | 42 | 90 |
2019 Abril | 75 | 65 | 140 |
2019 Marzo | 50 | 47 | 97 |
2019 Febrero | 43 | 64 | 107 |
2019 Enero | 60 | 66 | 126 |
2018 Diciembre | 163 | 74 | 237 |
2018 Noviembre | 225 | 37 | 262 |
2018 Octubre | 97 | 20 | 117 |