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Differential metabolic profile associated with the condition of normoalbuminuria in the hypertensive population
Perfil metabolómico diferenciador asociado a la condición de normoalbuminuria en la población hipertensa
Aranzazu Santiago-Hernandeza, Paula J. Martineza, Marta Martin-Lorenzoa, Gema Ruiz-Hurtadob,c, María G. Barderasc, Julian Segurad, Luis M. Ruilopeb,d,e, Gloria Alvarez-Llamasa,f,
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a Laboratorio de Inmunoalergia y Proteómica, Departamento de Inmunología, IIS-Fundación Jiménez Díaz, Universidad Autónoma de Madrid, Madrid, Spain
b Laboratorio Traslacional Cardiorrenal, Instituto de Investigación I+12 Hospital Universitario 12 de Octubre/CIBER-CV, Madrid, Spain
c Departamento de Fisiopatología Vascular, Hospital Nacional de Parapléjicos, SESCAM, Toledo, Spain
d Servicio de Nefrología, Unidad de Hipertensión, Hospital Universitario 12 de Octubre, Madrid, Spain
e Escuela de Estudios de Doctorado e Investigación, Universidad Europea de Madrid, Madrid, Spain
f REDINREN, Spain
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ACHN and Caki-1 cells were analyzed 24 or 72<span class="elsevierStyleHsp" style=""></span>h post-transfection with miR-9-5p mimic as compared with control miR. (A) miR-9-5p expression in ACHN and Caki-1 cells 72<span class="elsevierStyleHsp" style=""></span>h post-transfection. (B, C) Quantification of cell proliferation in ACHN and Caki-1 cells 72<span class="elsevierStyleHsp" style=""></span>h post-transfection. (D) Quantification of clone formation in ACHN and Caki-1 cells 72<span class="elsevierStyleHsp" style=""></span>h post-transfection. (E) Quantification of migratory and invasive ability in ACHN and Caki-1 cells 72<span class="elsevierStyleHsp" style=""></span>h post-transfection. (F, G) Annexin V-FITC/7AAD FACS quantification of early apoptotic cells (lower right quadrant) in ACHN and Caki-1 cells 24<span class="elsevierStyleHsp" style=""></span>h post-transfection. 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Martinez, Marta Martin-Lorenzo, Gema Ruiz-Hurtado, María G. Barderas, Julian Segura, Luis M. Ruilope, Gloria Alvarez-Llamas" "autores" => array:8 [ 0 => array:3 [ "nombre" => "Aranzazu" "apellidos" => "Santiago-Hernandez" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 1 => array:3 [ "nombre" => "Paula J." "apellidos" => "Martinez" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 2 => array:3 [ "nombre" => "Marta" "apellidos" => "Martin-Lorenzo" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 3 => array:3 [ "nombre" => "Gema" "apellidos" => "Ruiz-Hurtado" "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">c</span>" "identificador" => "aff0015" ] ] ] 4 => array:3 [ "nombre" => "María G." "apellidos" => "Barderas" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">c</span>" "identificador" => "aff0015" ] ] ] 5 => array:3 [ "nombre" => "Julian" "apellidos" => "Segura" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">d</span>" "identificador" => "aff0020" ] ] ] 6 => array:3 [ "nombre" => "Luis M." "apellidos" => "Ruilope" "referencia" => array:3 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">d</span>" "identificador" => "aff0020" ] 2 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">e</span>" "identificador" => "aff0025" ] ] ] 7 => array:4 [ "nombre" => "Gloria" "apellidos" => "Alvarez-Llamas" "email" => array:1 [ 0 => "galvarez@fjd.es" ] "referencia" => array:3 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">f</span>" "identificador" => "aff0030" ] 2 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">*</span>" "identificador" => "cor0005" ] ] ] ] "afiliaciones" => array:6 [ 0 => array:3 [ "entidad" => "Laboratorio de Inmunoalergia y Proteómica, Departamento de Inmunología, IIS-Fundación Jiménez Díaz, Universidad Autónoma de Madrid, Madrid, Spain" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Laboratorio Traslacional Cardiorrenal, Instituto de Investigación I+12 Hospital Universitario 12 de Octubre/CIBER-CV, Madrid, Spain" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Departamento de Fisiopatología Vascular, Hospital Nacional de Parapléjicos, SESCAM, Toledo, Spain" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Servicio de Nefrología, Unidad de Hipertensión, Hospital Universitario 12 de Octubre, Madrid, Spain" "etiqueta" => "d" "identificador" => "aff0020" ] 4 => array:3 [ "entidad" => "Escuela de Estudios de Doctorado e Investigación, Universidad Europea de Madrid, Madrid, Spain" "etiqueta" => "e" "identificador" => "aff0025" ] 5 => array:3 [ "entidad" => "REDINREN, Spain" "etiqueta" => "f" "identificador" => "aff0030" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "<span class="elsevierStyleItalic">Corresponding author</span>." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Perfil metabolómico diferenciador asociado a la condición de normoalbuminuria en la población hipertensa" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:8 [ "identificador" => "fig0010" "etiqueta" => "Fig. 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 787 "Ancho" => 3136 "Tamanyo" => 171236 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0010" "detalle" => "Fig. " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Observed correlations between the metabolites identified in urine and the ACR level. Spearman's correlation. a.u.: arbitrary units.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Hypertension is one of the diseases with the highest prevalence worldwide.<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a> A 30–40 % of the adult population is hypertensive. One of the first-line of treatment for its control is the chronic inhibition of the renin angiotensin system (RAS inhibition) as monotherapy or in combination with other antihypertensive drugs, with proven efficacy in reducing blood pressure. However, a remarkable percentage of controlled hypertensive patients develop albuminuria (16.1% at 3-year follow-up).<a class="elsevierStyleCrossRef" href="#bib0010"><span class="elsevierStyleSup">2</span></a> Albuminuria is the clinical expression of a complex and multifactorial pathophysiological process which is associated with increased cardiovascular risk.<a class="elsevierStyleCrossRefs" href="#bib0015"><span class="elsevierStyleSup">3,4</span></a> Although the only presence of albuminuria may not be predictive of chronic kidney disease progression,<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a> there is evidence of an association between changes in albuminuria levels and the development or aggravation of kidney disease.<a class="elsevierStyleCrossRefs" href="#bib0030"><span class="elsevierStyleSup">6–8</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">Albuminuria indicates that there is a subclinical organ damage. The development of albuminuria is a continuous process and as such its consequences on cardiovascular risk and kidney damage must be considered.<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">9</span></a> Previous studies have shown that the association between the development of albuminuria and cardiovascular events begins at urine Albumin/creatinine ratio (ACR) level within the normal range of albuminuria, with values as low as 4.4 mg /g<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">10</span></a>; 6.6 mg/g<a class="elsevierStyleCrossRef" href="#bib0055"><span class="elsevierStyleSup">11</span></a> or, in any case with values below 10 mg/g.<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">12</span></a> Particularly, the risk of developing cardiovascular disease in diabetics increases by a factor of 10 if albuminuria increases from 10 to 30 mg/d<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a> and, in the general population, an increase of 5−10 mg / L is associated with a 29% higher risk of mortality from cardiovascular disease.<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">14</span></a> In the same line, it predicts the development of hypertension in the high-normal range (<30 mg / g)<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a> and chronic kidney disease in non-diabetics.<a class="elsevierStyleCrossRefs" href="#bib0035"><span class="elsevierStyleSup">7,8</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">The greatest difficulty in the application of prevention strategies is that it is not possible to anticipate which subjects will develop albuminuria. One of the main reasons is that the underlying molecular mechanisms are not fully understood. The value of urine analysis in the study of cardiovascular disease has been widely demonstrated.<a class="elsevierStyleCrossRefs" href="#bib0080"><span class="elsevierStyleSup">16–19</span></a> Specifically, in previous studies we have identified urine molecular markers associated with the condition of albuminuria that point to alterations in the immune response, coagulation system, inflammatory response, vascular remodeling and oxidative stress as the main biological processes involved in the development of albuminuria.<a class="elsevierStyleCrossRefs" href="#bib0100"><span class="elsevierStyleSup">20–22</span></a> In this work we explore the existence of a differential metabolomic profile in subjects classified according to their ACR level in: a) <10 mg / g (normal); b) 10−30 mg / g in men or 20−40 mg / g in women (normal-high); c) 30−200 mg / g or 40−300 mg / g, in men and women respectively (micro). Thus, patients can be separated into those that are not expected to develop albuminuria (normal) and those who are likely to develop albuminuria (normal-high). We analyzed the previously identified metabolic footprint to investigate whether there is metabolic variation associated with an early or incipient albuminuria condition in order to stratify cardiorenal risk at the molecular level and thus better adapt the therapeutic strategy in these patients.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Material and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Selection of patients</span><p id="par0020" class="elsevierStylePara elsevierViewall">Patients were recruited from the Hypertension Unit of the Hospital 12 de Octubre in Madrid. A total of 48 hypertensive patients with blood pressure controlled with chronic suppression of the RAS for a minimum of 2 years were selected. Those patients with secondary hypertension were excluded from the study. Patients with and without diabetes mellitus between 45 and 70 years of age were included. The study was performed according to the recommendations of the Declaration of Helsinki and was approved by the Ethics Committee of the Hospital 12 de Octubre, with the prior signed informed consent of the patients.</p><p id="par0025" class="elsevierStylePara elsevierViewall">Subjects were classified according to the ACR value into 3 groups: normal (N), individuals with ACR < 10 mg / g, of whom, according to the ROADMAP study, it is known that they will not develop albuminuria<a class="elsevierStyleCrossRef" href="#bib0115"><span class="elsevierStyleSup">23</span></a>; normal-high (NA), individuals with ACR = 10−30 mg / g (men) or 20−40 mg / g (women) and microalbuminuria (M), individuals with ACR = 30−200 mg / g or 40–300 mg / g, in men and women respectively. The clinical guidelines use a cut-off point of ACR =30 mg / g between albuminuria and moderately elevated albuminuria as a general classification criterion.<a class="elsevierStyleCrossRef" href="#bib0120"><span class="elsevierStyleSup">24</span></a> For women, the cutoff point has been slightly increased to 40 mg/g,<a class="elsevierStyleCrossRef" href="#bib0125"><span class="elsevierStyleSup">25</span></a> considering that the urinary excretion of creatinine is influenced by muscle mass. <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a> collects the clinical characteristics of the subjects included in the study.</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Metabolomic analysis of urine by directed mass spectrometry</span><p id="par0030" class="elsevierStylePara elsevierViewall">The first morning urine was collected, centrifuged to remove cell debris, and stored at −80 °C until analysis. Quantitative analysis of metabolites was performed using liquid chromatography coupled to mass <span class="elsevierStyleItalic">reaction</span> spectrometry in <span class="elsevierStyleItalic">selected reaction monitoring</span> mode (SRM-LC-MS / MS). This methodology was selected as “method of the year” by the journal <span class="elsevierStyleItalic">Nature Methods</span> 2012.<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">26</span></a> Based on previous studies in our laboratory, metabolites were extracted from the urine after elimination of the protein fraction by organic precipitation.<a class="elsevierStyleCrossRefs" href="#bib0135"><span class="elsevierStyleSup">27,28</span></a> The supernatant was filtered and analyzed on a QQQ6460 Triple Quadrupole Mass Spectrometer (Agilent Technologies) coupled to a liquid chromatography binary system (1200 series, Agilent Technologies) controlled by the Mass Hunter program (v4.0 Agilent Technologies).</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Statistical analysis</span><p id="par0035" class="elsevierStylePara elsevierViewall">The signal corresponding to each metabolite was integrated using the Mass Hunter Acquisition Data Qualitative Analysis B.04.00 program ( Agilent Technologies), and the peak area was obtained. A non-parametric Mann-Whitney statistical analysis was performed, with a 95% confidence level and previous detection of <span class="elsevierStyleItalic">outliers</span> using the ROUT method (Q value = 5%). For the analysis of correlations, a non-parametric Spearman correlation test was used, all using the GraphPad Prism program (version 6.01).</p></span></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Results and discussion</span><p id="par0040" class="elsevierStylePara elsevierViewall">Oxalacetate, guanidoacetate and 3-ureidopropionate show lower levels in the group of individuals with microalbuminuria (M) than in those with normoalbuminuria (N). However, Malate levels are higher in M ​​than in N (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>). These data confirm previous observations in patients with albuminuria developed during the 3-year follow-up prior to sampling (albuminuria <span class="elsevierStyleItalic">de novo</span>) or already present previously (maintained albuminuria).<a class="elsevierStyleCrossRef" href="#bib0110"><span class="elsevierStyleSup">22</span></a> It should be noted that these 4 metabolites are capable of differentiating between N patients and those in the NA albuminuria range, and therefore allow for earlier molecular stratification of patients.</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0045" class="elsevierStylePara elsevierViewall">The correlation between the urine metabolites levels and the ACR values ​​for each patient was performed. There was a statistically significant correlation in all cases (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>).</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia><p id="par0050" class="elsevierStylePara elsevierViewall">Albuminuria has been associated with an increase in oxidative stress.<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">29</span></a> Oxidative stress is caused by a dysregulation in the production and metabolism of reactive oxygen species; the cycle of tricarboxylic acid participates in this regulation. The changes observed in the levels of oxalacetate and malate in patients with albuminuria in the high-normal range and microalbuminuria again point to energy metabolism as a key element in the management of hypertensive patients.<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">30</span></a> The guanidoacetate is an intermediate in the metabolism of proline and arginine and creatine precursor, a substrate of creatine kinase. This enzyme has been linked to a failure of antihypertensive treatment, without knowing in detail what are the mechanisms that may mediate this effect.<a class="elsevierStyleCrossRef" href="#bib0155"><span class="elsevierStyleSup">31</span></a> In addition guanidoacetate has been proposed as a marker of kidney injury since it is reduced in the urine of transplant patients with normal kidney function.<a class="elsevierStyleCrossRef" href="#bib0160"><span class="elsevierStyleSup">32</span></a> Therefore, the alterations of these metabolic processes, indicate an early dysregulation of energy metabolism and the metabolism of arginine and proline in patients with albuminuria in the normal-high range.</p><p id="par0055" class="elsevierStylePara elsevierViewall">A limitation of the present study is the difference in some of the baseline characteristics of the clinical groups, particularly in regard with the percentage of diabetic individuals. Although a greater presence of diabetes mellitus is expected in the group of subjects with microalbuminuria, it would be of interest to evaluate in a larger cohort of only non-diabetic subjects the observed metabolic variations to determine with more precision the degree of contribution of diabetes.</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Conclusions</span><p id="par0060" class="elsevierStylePara elsevierViewall">In this study we have confirmed the association of the levels of the metabolites 3-ureidopropionate, oxalacetate, malate and guanidoacetate with different degrees of albuminuria. For the first time, a molecular fingerprint (metabolic panel) capable of showing variation within the normoalbuminuria condition has been identified being able to distinguish subjects with ACR < 10 mg / g or higher. This fact is noteworthy in that it represents a tool with enormous potential in the therapeutic management of hypertensive patients with ACR levels considered "non-pathological" and who therefore do not receive special medical care. However, these are the patients who would benefit most from early intervention, as they are at increased risk of cardiovascular or kidney disease.</p></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Financing</span><p id="par0065" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleGrantSponsor" id="gs0005">Carlos III Health Institute-FEDER Funds</span> (<span class="elsevierStyleGrantNumber" refid="gs0005">PI16/01334</span>, <span class="elsevierStyleGrantNumber" refid="gs0005">PI13/01873</span>, <span class="elsevierStyleGrantNumber" refid="gs0005">PI17/01193</span>, <span class="elsevierStyleGrantNumber" refid="gs0005">PI17/01093</span>, <span class="elsevierStyleGrantNumber" refid="gs0005">IF08/3667-1</span>, <span class="elsevierStyleGrantNumber" refid="gs0005">CPII15/00027</span>, <span class="elsevierStyleGrantNumber" refid="gs0005">CP15/00129</span>, <span class="elsevierStyleGrantNumber" refid="gs0005">PT13/0001/0013</span>, <span class="elsevierStyleGrantSponsor" id="gs0010">PRB3</span> (<span class="elsevierStyleGrantNumber" refid="gs0010">IPT17/0019</span> ISCIIIS-GEFI/ERDF), <span class="elsevierStyleGrantSponsor" id="gs0015">REDinREN</span> (<span class="elsevierStyleGrantNumber" refid="gs0015">RD16/0009</span>)), Research Aid from the <span class="elsevierStyleGrantSponsor" id="gs0020">SENEFRO Foundation</span> and the <span class="elsevierStyleGrantSponsor" id="gs0025">Conchita Rábago Foundation</span> from Jiménez Díaz.</p></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Conflict of interests</span><p id="par0070" class="elsevierStylePara elsevierViewall">The authors declare that they have no conflict of interest.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:12 [ 0 => array:3 [ "identificador" => "xres1407259" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Background and aim" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Patients, materials and methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1287485" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1407258" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Antecedentes y objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Pacientes, materiales y métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusiones" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1287486" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Material and methods" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Selection of patients" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Metabolomic analysis of urine by directed mass spectrometry" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "Statistical analysis" ] ] ] 6 => array:2 [ "identificador" => "sec0030" "titulo" => "Results and discussion" ] 7 => array:2 [ "identificador" => "sec0035" "titulo" => "Conclusions" ] 8 => array:2 [ "identificador" => "sec0040" "titulo" => "Financing" ] 9 => array:2 [ "identificador" => "sec0045" "titulo" => "Conflict of interests" ] 10 => array:2 [ "identificador" => "xack489711" "titulo" => "Acknowledgments" ] 11 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2019-06-21" "fechaAceptado" => "2019-10-24" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1287485" "palabras" => array:7 [ 0 => "Albuminuria" 1 => "Cardiovascular risk" 2 => "Hypertension" 3 => "Renin-angiotensin system" 4 => "Metabolomics" 5 => "Biomarkers" 6 => "Metabolites" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1287486" "palabras" => array:7 [ 0 => "Albuminuria" 1 => "Riesgo cardiovascular" 2 => "Hipertensión" 3 => "Sistema renina-angiotensina" 4 => "Metabolómica" 5 => "Biomarcadores" 6 => "Metabolitos" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Background and aim</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Albuminuria is an indicator of sub-clinical organ damage and a marker of cardiovascular risk and renal disease. A percentage of hypertensive patients develop albuminuria despite being under chronic suppression of the renin-angiotensin system (RAS). We previously identified urinary metabolites associated with the development of albuminuria. In this study, we searched for metabolic alterations which reflect different levels within the condition of normoalbuminuria.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Patients, materials and methods</span><p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Urine from 48 hypertensive patients under chronic RAS suppression was analyzed. They were classified according to the albumin / creatinine ratio (ACR) into 3 groups: Normoalbuminuria (<10 mg / g); Normal-high (10–30 mg / g in men, or 20−40 mg / g in women); and moderately high albuminuria (microalbuminuria, 30−200 mg / g or 40−300 mg / g, respectively). The metabolome was analyzed by mass spectrometry and a correlation analysis was performed between altered metabolite levels and ACR.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Oxaloacetate, 3-ureidopropionate, guanidoacetate and malate show significant variation between the normo and micro groups. Additionally, these metabolites are able to differentiate between patients in the normo and high-normal range. A significant correlation between metabolites and ACR was found. Observed variations point to alterations in the energy metabolism already in patients with albuminuria in the high-normal range.</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">The association between the molecular panel consisting of 3-ureidopropionate, oxaloacetate, malate and guanidoacetate and different levels of albuminuria is confirmed. A metabolic fingerprint was also identified showing variations within the condition of normoalbuminuria allowing an earlier molecular stratification of patients.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Background and aim" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Patients, materials and methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Antecedentes y objetivo</span><p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">La albuminuria es un indicador de daño orgánico subclínico y un marcador de riesgo cardiovascular y de enfermedad renal. Un porcentaje de pacientes hipertensos desarrollan albuminuria a pesar de estar bajo supresión crónica del sistema renina-angiotensina (SRA). Previamente identificamos metabolitos en orina asociados al desarrollo de albuminuria. En este estudio, investigamos alteraciones metabólicas que reflejen distintos niveles dentro de la condición de normoalbuminuria.</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Pacientes, materiales y métodos</span><p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Se analizó la orina de 48 pacientes hipertensos con supresión crónica del SRA. Se clasificaron según el cociente albúmina/creatinina (ACR) en 3 grupos: normoalbuminuria (<10 mg/g); normal-alta (10−30 mg/g en varones, o 20−40 mg/g en mujeres) y albuminuria moderadamente elevada (microalbuminuria: 30−200 mg/g o 40−300 mg/g, respectivamente). El metaboloma se analizó mediante espectrometría de masas y se realizó un análisis de correlaciones entre los niveles de los metabolitos alterados y ACR.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">Oxalacetato, 3-ureidopropionato, guanidoacetato y malato muestran una variación significativa entre los grupos normo y micro. Además, estos metabolitos son capaces de diferenciar entre los pacientes normo y normal-alta. Igualmente se observó correlación significativa entre el nivel de los metabolitos identificados con el nivel de ACR. Las variaciones observadas señalan una alteración del metabolismo energético ya en pacientes con albuminuria en el rango normal-alta.</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusiones</span><p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">Se confirma la asociación del panel molecular constituido por 3-ureidopropionato, oxalacetato, malato y guanidoacetato con distintos niveles de albuminuria. Así mismo, se ha identificado una huella metabólica capaz de mostrar variación dentro de la condición de normoalbuminuria, lo que permite una estratificación molecular más temprana de los pacientes.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Antecedentes y objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Pacientes, materiales y métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusiones" ] ] ] ] "NotaPie" => array:1 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Please cite this article as: Santiago-Hernandez A, Martinez PJ, Martin-Lorenzo M, Ruiz-Hurtado G, Barderas MG, Segura J, et al. Perfil metabolómico diferenciador asociado a la condición de normoalbuminuria en la población hipertensa. Nefrologia. 2020;40:439–445.</p>" ] ] "multimedia" => array:3 [ 0 => array:8 [ "identificador" => "fig0005" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 761 "Ancho" => 2981 "Tamanyo" => 138570 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0005" "detalle" => "Fig. " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Metabolic footprint in urine associated with the development of albuminuria.</p> <p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">M: microalbuminuria ; N: norm; NA: normal-high; AU : arbitrary units.</p> <p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">* <span class="elsevierStyleItalic">p</span> < 0.05. ** <span class="elsevierStyleItalic">p</span> < 0.01. *** <span class="elsevierStyleItalic">p</span> < 0.001. **** <span class="elsevierStyleItalic">p</span> < 0.0001.</p>" ] ] 1 => array:8 [ "identificador" => "fig0010" "etiqueta" => "Fig. 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 787 "Ancho" => 3136 "Tamanyo" => 171236 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0010" "detalle" => "Fig. " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Observed correlations between the metabolites identified in urine and the ACR level. Spearman's correlation. a.u.: arbitrary units.</p>" ] ] 2 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0015" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">ACR is expressed as median (interquartile range). The rest of the variables are expressed as frequencies or as mean ± standard deviation.</p><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">ACR: albumin / creatinine ratio; ARA: angiotensin receptor antagonist; eGFR: estimated glomerular filtration rate; ACEI: angiotensin- converting enzyme inhibitors; PAD: diastolic blood pressure; PAS: systolic blood pressure.</p>" "tablatextoimagen" => array:2 [ 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="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Normal (n = 22) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Normal-high (n = 17) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Microalbuminuria (n = 9) \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Age (years) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">57 ± 9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">64 ± 5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">65 ± 3 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Gender (% male) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">59 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">76 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">66 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Cholesterol (mg/dl) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">179 ± 38 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">166 ± 29 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">154 ± 29 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Triglycerides (mg/dl) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">110 ± 33 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">125 ± 59 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">122 ± 32 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">HDL cholesterol (mg/dl) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">54 ± 16 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">53 ± 16 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">50 ± 7 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">LDL cholesterol (mg/dl) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">102 ± 31 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">88 ± 30 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">91 ± 26 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Uric acid (mg/dl) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5 ± 1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6 ± 2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 ± 2 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">eGFR (ml/min/1.73 m <span class="elsevierStyleSup">2</span> ) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">86 ± 16 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">85 ± 20 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">93 ± 22 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">ACR (mg/g) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 (3−6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">22 (18−31) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">85 (44−99) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Type II diabetes mellitus (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">18 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">24 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">67 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">SBP (mmHg) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">140 ± 14 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">144 ± 14 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">141 ± 19 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">DBP (mmHg) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">85 ± 8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">83 ± 8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">79 ± 5 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2413385.png" ] ] 1 => 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="\n \t\t\t\t\ttable-head\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Antihypertensive treatment (%)</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">ACEI \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">18 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">18 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">67 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">ARA \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">41 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">65 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">33 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Diuretics \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Four. Five \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">47 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">22 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">α-blockers \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">18 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">22 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">β-blockers \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">32 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">29 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">33 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Calcium channel blockers \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">41 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">71 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">78 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2413386.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Clinical characteristics of the patients included in the study.</p>" ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:32 [ 0 => array:3 [ "identificador" => "bib0005" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "2018 ESC / ESH Guidelines for the management of arterial hypertension" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "B. 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| Year/Month | Html | Total | |
|---|---|---|---|
| 2024 November | 1 | 4 | 5 |
| 2024 October | 44 | 68 | 112 |
| 2024 September | 54 | 48 | 102 |
| 2024 August | 72 | 88 | 160 |
| 2024 July | 32 | 47 | 79 |
| 2024 June | 66 | 63 | 129 |
| 2024 May | 60 | 70 | 130 |
| 2024 April | 44 | 51 | 95 |
| 2024 March | 53 | 64 | 117 |
| 2024 February | 54 | 70 | 124 |
| 2024 January | 44 | 45 | 89 |
| 2023 December | 47 | 37 | 84 |
| 2023 November | 88 | 79 | 167 |
| 2023 October | 78 | 47 | 125 |
| 2023 September | 56 | 45 | 101 |
| 2023 August | 37 | 39 | 76 |
| 2023 July | 42 | 57 | 99 |
| 2023 June | 43 | 77 | 120 |
| 2023 May | 50 | 62 | 112 |
| 2023 April | 34 | 26 | 60 |
| 2023 March | 56 | 35 | 91 |
| 2023 February | 43 | 36 | 79 |
| 2023 January | 34 | 33 | 67 |
| 2022 December | 61 | 42 | 103 |
| 2022 November | 74 | 40 | 114 |
| 2022 October | 62 | 55 | 117 |
| 2022 September | 44 | 35 | 79 |
| 2022 August | 41 | 47 | 88 |
| 2022 July | 37 | 64 | 101 |
| 2022 June | 38 | 48 | 86 |
| 2022 May | 54 | 39 | 93 |
| 2022 April | 58 | 71 | 129 |
| 2022 March | 51 | 66 | 117 |
| 2022 February | 63 | 55 | 118 |
| 2022 January | 69 | 59 | 128 |
| 2021 December | 46 | 45 | 91 |
| 2021 November | 36 | 36 | 72 |
| 2021 October | 55 | 64 | 119 |
| 2021 September | 34 | 34 | 68 |
| 2021 August | 50 | 50 | 100 |
| 2021 July | 33 | 36 | 69 |
| 2021 June | 21 | 17 | 38 |
| 2021 May | 37 | 44 | 81 |
| 2021 April | 86 | 82 | 168 |
| 2021 March | 60 | 42 | 102 |
| 2021 February | 66 | 51 | 117 |
| 2021 January | 34 | 26 | 60 |
| 2020 December | 27 | 17 | 44 |
| 2020 November | 50 | 25 | 75 |
| 2020 October | 53 | 28 | 81 |
| 2020 September | 15 | 9 | 24 |
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