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"aff0005" ] 1 => array:3 [ "entidad" => "Unidad de Gastroenterología y Nutrición Pediátrica, Hospital Universitario Miguel Servet, Zaragoza, Spain" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Unidad de Neuropediatría, Hospital Universitario Miguel Servet, Zaragoza, Spain" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Universidad de Zaragoza, Instituto de Investigación Sanitaria Aragón, Red de Salud Materno Infantil y del Desarrollo (SAMID), RETICS ISCIII, Zaragoza, Spain" "etiqueta" => "d" "identificador" => "aff0020" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Situación nutricional en una población con parálisis cerebral moderada-grave: más allá del peso" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:8 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1177 "Ancho" => 2139 "Tamanyo" => 69521 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0005" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Percentage of lean mass relative to the ideal mass by GMFCS level.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Cerebral palsy (CP) is the most frequent cause of motor impairment in the paediatric age group and the third leading cause of neurodevelopmental disorders following intellectual disability and autism spectrum disorders. The term CP refers to motor sequelae that may be accompanied by other disorders and does not carry any aetiological implications or an association with a specific past medical history or adverse events.</p><p id="par0010" class="elsevierStylePara elsevierViewall">The collaborative project known as Surveillance of Cerebral Palsy in Europe<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a> has reported an incidence of CP of 2–3 cases per 1000 live births. This group recommends a minimum age of 3 years for diagnosis of CP and considers age 5 years optimal.</p><p id="par0015" class="elsevierStylePara elsevierViewall">Feeding problems are frequent in children with CP, although nutritional and feeding problems are more frequent and severe in those with more severe neurologic impairment.<a class="elsevierStyleCrossRefs" href="#bib0010"><span class="elsevierStyleSup">2,3</span></a> The reported prevalence of malnutrition varies widely between case series, ranging between 19% and 50.9%.<a class="elsevierStyleCrossRefs" href="#bib0020"><span class="elsevierStyleSup">4,5</span></a></p><p id="par0020" class="elsevierStylePara elsevierViewall">Nutritional management aims at ensuring optimal growth, preventing malnutrition and disorders related to nutritional deficiencies, and at establishing healthy dietary habits to prevent the development of diseases associated with poor nutrition.<a class="elsevierStyleCrossRef" href="#bib0030"><span class="elsevierStyleSup">6</span></a> An adequate nutritional status improves outcomes in motor skills, cognitive stills, communication and social interaction, and therefore overall neurodevelopmental outcomes.<a class="elsevierStyleCrossRefs" href="#bib0035"><span class="elsevierStyleSup">7,8</span></a></p><p id="par0025" class="elsevierStylePara elsevierViewall">Nutritional and dietary measures must be safe and effective, allowing to the extent possible the enjoyment of food. All of the above requires continuous, comprehensive, coordinated and close monitoring based on a multidisciplinary approach, with participation of paediatric neurologists, gastroenterologists, nutritionists/dietitians, nursing staff, speech therapists and rehabilitation specialists.<a class="elsevierStyleCrossRefs" href="#bib0030"><span class="elsevierStyleSup">6,9</span></a></p><p id="par0030" class="elsevierStylePara elsevierViewall">The aim of our study was to assess the nutritional status of patients with predominantly spastic CP and the degree of nutritional compromise based on the severity of CP.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Materials and methods</span><p id="par0035" class="elsevierStylePara elsevierViewall">We conducted a cross-sectional, observational, descriptive and inferential study. The study universe consisted of the patients aged 4–15 years with moderate to severe predominantly spastic CP managed in the paediatric neurology unit of a referral hospital.</p><p id="par0040" class="elsevierStylePara elsevierViewall">We included patients at levels III, IV or IV of the Gross Motor Function Classification System (GMFCS) developed by Palisano et al.<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">10</span></a> and modified according to the International Classification of Functioning, Disability and Health (ICF) of the World Health Organization (WHO), which categorises patients based on the degree of motor impairment.</p><p id="par0045" class="elsevierStylePara elsevierViewall">We excluded patients who refused or whose parents refused to participate in the study, those outside the age range under study, and those that did not meet the diagnostic criteria for CP.</p><p id="par0050" class="elsevierStylePara elsevierViewall">The study was approved by the Regional Ethics Committee (CEICA; PI16/039). All participating patients and/or their guardians signed an informed consent form.</p><p id="par0055" class="elsevierStylePara elsevierViewall">After ascertaining that patients met the inclusion criteria, we contacted the patient or the guardians to schedule an office visit during which we carried out a clinical interview to collect data on variables related to the patient’s clinical condition, anthropometric values and dietary habits.</p><p id="par0060" class="elsevierStylePara elsevierViewall">For the anthropometric assessment, we used the height calculated by means of the knee-height (KH) stature estimate equation developed by Stevenson<a class="elsevierStyleCrossRef" href="#bib0055"><span class="elsevierStyleSup">11</span></a>: height<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>KH<span class="elsevierStyleHsp" style=""></span>×<span class="elsevierStyleHsp" style=""></span>2.69<span class="elsevierStyleHsp" style=""></span>+<span class="elsevierStyleHsp" style=""></span>24.2<span class="elsevierStyleHsp" style=""></span>cm. The other anthropometric measurements taken were the weight, arm circumference (AC), subcutaneous skinfolds (biceps, triceps [TSF], subscapular, suprailiac). These measurements were made with measuring tape (perimeter and segmental height measures), Holtain® skinfold callipers (subcutaneous folds), scale (weight) and callipers (knee height). We used the Siri equation to estimate body composition.</p><p id="par0065" class="elsevierStylePara elsevierViewall">We calculated the <span class="elsevierStyleItalic">z</span>-scores for the obtained anthropometric values using the growth tables of Carrascosa et al. (2010) as Ref.<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">12</span></a> in adherence to the recommendation made in 2017 by the European Society for Paediatric Gastroenterology, Hepatology and Nutrition (ESPGHAN) of using a standardised reference population. We calculated the body mass index (BMI) and the weight-for-height (WFH) to categorise the nutritional status of the patient based on weight: WFH<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>patient weight/expected weight for height (50th percentile)<span class="elsevierStyleHsp" style=""></span>×<span class="elsevierStyleHsp" style=""></span>100.</p><p id="par0070" class="elsevierStylePara elsevierViewall">We evaluated the body composition of the patients using bioelectrical impedance analysis (BIA) with an Akern BIA-101 Anniversary bio-impedance analyser. This method allowed us to obtain values for the total body water (extracellular and intracellular e intracellular), fat body mass, body cell mass (total mass of living, functioning and metabolically active cells) and lean body mass (muscle mass and bone mass).<a class="elsevierStyleCrossRefs" href="#bib0065"><span class="elsevierStyleSup">13,14</span></a> Measurements are obtained by adhering electrodes to the skin to generate a small alternating current in a single or multiple frequencies, recording the resistance (opposition to the passage of the electric current) and the reactance (the delay in conduction caused by cellular membranes, tissue interfaces and non-ionic tissues).<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a></p><p id="par0075" class="elsevierStylePara elsevierViewall">Patients underwent BIA following a fast of at least 4<span class="elsevierStyleHsp" style=""></span>h, after avoiding physical activity for at least the last 12<span class="elsevierStyleHsp" style=""></span>h and in a state of absolute rest. The measurements were made with the patient lying in the supine position with the arms abducted at 20°–30° and the legs at 45° from the trunk. The 2 current-introducing electrodes were placed in the midlines of the wrist and the ankle of the unclothed patient lying on a cot made of non-conductive material, and the voltage-sensing electrodes 4–5<span class="elsevierStyleHsp" style=""></span>cm away from the source along the metacarpal and the metatarsal phalangeal lines, respectively; always homolaterally (hemibody).</p><p id="par0080" class="elsevierStylePara elsevierViewall">In order to accurately assess lean body mass and eliminate the potential bias associated with low weight in these patients, we calculated the expected percentage of lean mass for their height. To do so, after obtaining the expected weight for their height (using the median in the growth charts of Carrascosa et al., 2010), we calculated the expected kilograms of lean mass (using the references published by Fomon<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a> and Haschke<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">16</span></a>) and, lastly, divided the lean body mass of the patient by the expected lean body mass (both in kg).</p><p id="par0085" class="elsevierStylePara elsevierViewall">To classify lean body mass values, we applied the cutoffs proposed by Lohman and Going<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a>: underfat (<10% in boys and <15% in girls), normal (11–25% in boys and 16–30% in girls) and excess fat (>25% in boys and >30% in girls).</p><p id="par0090" class="elsevierStylePara elsevierViewall">Our statistical analysis was performed with the software SPSS Statistics version 21.0. We did a descriptive analysis, summarising the results as mean<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>standard deviation (SD) with the 95% confidence interval (quantitative variables) or as frequencies (qualitative variables). We tested for normality with the Kolmogorov-Smirnov and Shapiro-Wilk tests. Afterward, we performed hypothesis testing with different methods: chi square test and Fisher exact test (qualitative variables), Student <span class="elsevierStyleItalic">t</span> test (parametric data, quantitative and dichotomous variables), Mann-Whitney <span class="elsevierStyleItalic">U</span> test (nonparametric data, quantitative and dichotomous variables), analysis of variance (ANOVA) with the Bonferroni correction (parametric data, quantitative and dichotomous variables) and Kruskal-Wallis test (nonparametric data, quantitative and non-dichotomous qualitative).</p></span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Results</span><p id="par0095" class="elsevierStylePara elsevierViewall">A total of 82 patients met the inclusion criteria, but we were unable to locate or obtain content for participation from 13, so the final sample included 69 patients (recruitment of 84.2%). Of this total, 50.7% (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">=</span><span class="elsevierStyleHsp" style=""></span>35) were female. The distribution of patients by level of functioning based on the GMFCS was as follows: level III, 36.2% (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">=</span><span class="elsevierStyleHsp" style=""></span>25); level IV, 29.0% (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">=</span><span class="elsevierStyleHsp" style=""></span>20); level V, 34.8% (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">=</span><span class="elsevierStyleHsp" style=""></span>24). The mean age was 10.46<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.4 years (level III, 10.83<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.7 years; level IV, 10.89<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.8 years; level V, 9.73<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.7 years; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>.380).</p><p id="par0100" class="elsevierStylePara elsevierViewall">The distribution by form of CP based on the predominant clinical pattern was: spastic, 75.4% (<span class="elsevierStyleItalic">n =</span> 52); mixed, 17.4% (<span class="elsevierStyleItalic">n =</span> 12); and dystonic, 7.2% (<span class="elsevierStyleItalic">n =</span> 5), although all patients exhibited spasticity (100%). The extension of paresis was: tetraparesis (59.4%; (<span class="elsevierStyleItalic">n =</span> 41), triparesis 21.7% (<span class="elsevierStyleItalic">n =</span> 15), diparesis 18.9% (<span class="elsevierStyleItalic">n =</span> 13). Of all patients, 73.9% (<span class="elsevierStyleItalic">n =</span> 51) received regular doses of botulinum toxin, with no differences in frequency between groups.</p><p id="par0105" class="elsevierStylePara elsevierViewall">The distribution of patients by feeding modality was: exclusively oral, 87% (<span class="elsevierStyleItalic">n =</span> 60); exclusively enteral, 10.1% (<span class="elsevierStyleItalic">n =</span> 7); mixed, 2.9% (<span class="elsevierStyleItalic">n =</span> 2). Thirteen percent of patients in the sample (<span class="elsevierStyleItalic">n =</span> 9) had a gastrostomy, all of them classified as level V.</p><p id="par0110" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a> presents information on the use of supplements and nutritional support in the sample, evincing that the use of polymeric formulas and thickening agents increased with the level of neurologic impairment.</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0115" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a> presents anthropometric data and body composition values calculated using anthropometric measures. We found a higher frequency of anthropometric <span class="elsevierStyleItalic">z</span>-scores in the abnormal range in patients with more severe motor impairment, which was particularly marked in the variables most relevant for assessment of nutritional status in patients with CP: BMI, AC, TSF, WFH.</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0120" class="elsevierStylePara elsevierViewall">The tibial length and knee height could not be assessed in one patient that had undergone a bilateral bone surgery, so this patient underwent segmental measurements.</p><p id="par0125" class="elsevierStylePara elsevierViewall">We did not find differences in weight, height or BMI based on sex.</p><p id="par0130" class="elsevierStylePara elsevierViewall">When we classified the patients based on the WFH, we found that most cases of moderate to severe undernutrition occurred in the level V group, while most cases of overweight/obesity occurred in groups III and IV III–IV (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>).</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><p id="par0135" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a> presents the body composition data obtained by BIA. We found a significant decrease in the cellular mass in the Level V group compared to the rest of the sample. We also found a decrease in the lean body mass, muscle mass and fat mass in these patients, but only in terms of absolute amounts as opposed to the percentages of the total body mass.</p><elsevierMultimedia ident="tbl0020"></elsevierMultimedia><p id="par0140" class="elsevierStylePara elsevierViewall">In this sample, 14.5% of patients (<span class="elsevierStyleItalic">n =</span> 10) were underfat based on the findings of BIA, while 50.7% (<span class="elsevierStyleItalic">n =</span> 35) had a normal fat mas and 34.8% (<span class="elsevierStyleItalic">n =</span> 24) excess fat. The distribution by GMFCS level was as follows (<span class="elsevierStyleItalic">P</span> = .104):<ul class="elsevierStyleList" id="lis0005"><li class="elsevierStyleListItem" id="lsti0005"><span class="elsevierStyleLabel">•</span><p id="par0145" class="elsevierStylePara elsevierViewall">III: 0% (<span class="elsevierStyleItalic">n =</span> 0) underfat, 64% (<span class="elsevierStyleItalic">n =</span> 16) normal fat and 36% (<span class="elsevierStyleItalic">n =</span> 9) excess fat.</p></li><li class="elsevierStyleListItem" id="lsti0010"><span class="elsevierStyleLabel">•</span><p id="par0150" class="elsevierStylePara elsevierViewall">IV: 20% (<span class="elsevierStyleItalic">n =</span> 4) underfat, normal 40% (<span class="elsevierStyleItalic">n =</span> 8) normal fat, 40% (<span class="elsevierStyleItalic">n =</span> 8) excess fat.</p></li><li class="elsevierStyleListItem" id="lsti0015"><span class="elsevierStyleLabel">•</span><p id="par0155" class="elsevierStylePara elsevierViewall">V: 25% (<span class="elsevierStyleItalic">n =</span> 6) underfat, 50% (<span class="elsevierStyleItalic">n =</span> 12) normal fat, 25% (<span class="elsevierStyleItalic">n =</span> 6) excess fat.</p></li></ul></p><p id="par0160" class="elsevierStylePara elsevierViewall">The distribution of male patients by body fat was: 11.8% underfat (<10%), 41.2% normal fat (11–25%), 47% excess fat (>25%). The distribution of male patients by body fat was: 17.1% underfat (<15%), 60% normal fat (16–30%), 22.9% excess fat (>30%). We did not find an association between sex and the prevalence of underfat/normal fat/excess fat established using BIA.</p><p id="par0165" class="elsevierStylePara elsevierViewall">In the overall sample, the lean body mass was 88.7% of the lean body mass expected for height. This percentage was higher in the level III group (88.93 ± 3.5%) and the level IV group (98.31 ± 5.7%), and lower in the level V group (80.66 ± 2.8%) (<span class="elsevierStyleItalic">P</span> = .012). <a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a> shows the distribution of the percentage of lean body mass relative to the expected lean body mass by group.</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0170" class="elsevierStylePara elsevierViewall">In the level V group (<span class="elsevierStyleItalic">n =</span> 24), 33.3% (<span class="elsevierStyleItalic">n =</span> 8) of patients had a gastrostomy. The mean age of patients with a gastrostomy was 9.73 ± 3.3 years (no difference between patients with and without a gastrostomy), and 50% were girls. The mean time elapsed between the placement of the gastrostomy tube and the time of the study was 43.89 ± 8.5 months. <a class="elsevierStyleCrossRef" href="#tbl0025">Table 5</a> compares the body composition and nutritional status markers in patients with and without a gastrostomy, revealing that patients with gastrostomy had lower body muscle and body cell masses.</p><elsevierMultimedia ident="tbl0025"></elsevierMultimedia></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Discussion</span><p id="par0175" class="elsevierStylePara elsevierViewall">Maintaining an adequate nutrition in patients with CP requires periodical and routine monitoring of nutritional status to detect actual malnutrition or its risk early on.<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a> However, less than half of the patients in our study were in follow-up with regular evaluations by a nutrition specialist.</p><p id="par0180" class="elsevierStylePara elsevierViewall">Due to their accessibility, anthropometric methods are most commonly used to assess nutritional outcomes, and the weight, height, TSF and AC are the most widely recommended values for monitoring of patients with CP.<a class="elsevierStyleCrossRefs" href="#bib0020"><span class="elsevierStyleSup">4,5,18,19</span></a></p><p id="par0185" class="elsevierStylePara elsevierViewall">When it came to stature, we found that the degree of abnormality was directly proportional to the severity of CP. This was to be expected, as the growth and body composition patterns in patients with CP differ from those of the reference population for age and sex.<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">20</span></a> As occurred in our study, stunting tends to be more severe the more severe the neurologic impairment and the feeding difficulties.<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">21</span></a> Measuring the height of patients at levels III to V is usually challenging due to the presence of scoliosis, spasticity and postural abnormalities. For this reason, it is recommended that height be assessed by taking segmental measurements and using an equation to estimate the stature,<a class="elsevierStyleCrossRefs" href="#bib0040"><span class="elsevierStyleSup">8,22</span></a> for which the knee height seems to be the measure least likely to be affected by least technical errors and associated with the lowest intrarater and interrater variability.<a class="elsevierStyleCrossRefs" href="#bib0095"><span class="elsevierStyleSup">19,23</span></a></p><p id="par0190" class="elsevierStylePara elsevierViewall">It is advisable that weight assessments take into account height by using the BMI and/or the WFH. In our study, categorization based on WFH resulted in a higher proportion of patients with undernutrition in the GMFCS level V group. In contrast, we found a high prevalence of overweight/obesity with an excess of body fat in patients with GMFCS levels III to IV. Such excess weight is relatively frequent in patients at levels III to IV that have no feeding problems depending on the level of impairment of motor skills or walking.<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">20</span></a></p><p id="par0195" class="elsevierStylePara elsevierViewall">In 2007, Day et al. published specific weight, height and BMI tables for children with CP<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">21</span></a> based on the level of motor impairment.<a class="elsevierStyleCrossRef" href="#bib0020"><span class="elsevierStyleSup">4</span></a> These tables are only descriptive and have not been standardised, as there were many factors at play in the study, such as a high prevalence of malnutrition, that could affect anthropometric variables, and therefore the tables do not reflect optimal growth patterns. For this reason, the ESPGHAN recommends against the routine use of these tables to assess for nutritional problems in children with CP, and instead proposes using standardised reference population data.<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a></p><p id="par0200" class="elsevierStylePara elsevierViewall">In addition to the weight, the height and their relationships, the ESPGHAN recommends routine measurement of subcutaneous skinfolds (especially the TSF) and of the AC to monitor nutritional status.<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> In our sample, patients with severe neurologic impairment had the lowest TSF and AC values. The evidence on this aspect is contradictory, as some studies have found similar trends while others have found no association between the level of neurologic impairment and the variability in skinfold and circumference measures,<a class="elsevierStyleCrossRefs" href="#bib0100"><span class="elsevierStyleSup">20,24</span></a> and therefore further research is required to corroborate our findings.</p><p id="par0205" class="elsevierStylePara elsevierViewall">In addition to calculating the <span class="elsevierStyleItalic">z-</span>scores corresponding to the anthropometric measures, it is also important to determine how the weight of the patient is distributed according to body composition. This can be achieved with equations that use skinfold measures, although these equations may not be very accurate in children with CP.<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> Other methods are available to assess body composition, and BIA is an essential tool in clinical practice for this purpose.<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> It is a safe, reliable, painless and quick method for assessment of body composition that is more accurate and with a lesser interrater and intrarater variability compared to other methods.<a class="elsevierStyleCrossRefs" href="#bib0100"><span class="elsevierStyleSup">20,25</span></a></p><p id="par0210" class="elsevierStylePara elsevierViewall">In our study, BIA found a lower muscle mass, lean body mass and fat mass (in kg) in patients with greater impairment based on the GMFCS. This was consistent with the previous literature, in which greater neurologic impairment is associate with decreased body weight, growth and lean body mass.<a class="elsevierStyleCrossRef" href="#bib0020"><span class="elsevierStyleSup">4</span></a></p><p id="par0215" class="elsevierStylePara elsevierViewall">When it came to the percentage of lean body mass, we found that it was greater in patients at level V in absolute terms, but when we adjusted the lean mass for height, we found a greater decrease in this group. This is why it is important to evaluate the obtained measures relative to the age, height and sex of the patient. We found it interesting that the lean mass was greater in patients at level IV compared to patients at level III. A possible explanation is that 40% of patients in the level IV group were in follow-up by the nutrition unit, compared to 16% of patients in the level III group. Other authors have reported these positive changes in body composition once regular nutritional follow-up is initiated,<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">26</span></a> so the ESPGHAN recommends performance of growth assessments in patients with CP every 1–3 months.<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a></p><p id="par0220" class="elsevierStylePara elsevierViewall">Another parameter that can be measured by BIA is the cell mass, which is considered a good marker of nutritional status.<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">14</span></a> As occurred in our sample, a study published in 2017 by Sung et al.<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">27</span></a> in a series of 146 patients found a decrease in cell mass in patients with more severe neurologic impairment, especially those with level V functioning. When it comes to the fat compartment, a study published by Kuperminc et al.<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">20</span></a> in 2008 analysed the normal percentage of body fat in patients at levels III to V, and found lower percentages of body fat compared to the percentages found in all groups.</p><p id="par0225" class="elsevierStylePara elsevierViewall">Compared to BIA, anthropometric methods underestimate the fat body mass and overestimates the lean body mass. It has been estimated that anthropometric measures led to a systematic error of approximately 1.3<span class="elsevierStyleHsp" style=""></span>kg in calculating the fat body mass,<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">20</span></a> an error similar to the error found in our study. One possible reason is that a decrease in peripheral cutaneous skinfold measures may not necessarily indicate a decrease in adiposity, as fat tends to be stored in the abdominal region in children with CP.<a class="elsevierStyleCrossRefs" href="#bib0095"><span class="elsevierStyleSup">19,28</span></a></p><p id="par0230" class="elsevierStylePara elsevierViewall">Gastrostomy tube feeding can be used in case oral intake does not contribute adequate amounts of nutrients, causes discomfort or is unsafe.<a class="elsevierStyleCrossRefs" href="#bib0015"><span class="elsevierStyleSup">3,19</span></a> The proportion of patients that required a gastrostomy in our sample was consistent with the 10–33% range reported in other case series.<a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">7</span></a> When comparing nutritional status in patients with and without a gastrostomy, previous studies have concluded that patients with gastrostomies have better nutritional outcomes, especially in terms of weight, BMI, fat body mass and lean body mass.<a class="elsevierStyleCrossRefs" href="#bib0010"><span class="elsevierStyleSup">2,21</span></a> However, in our sample patients with gastrostomies only exhibited an improvement in weight, with an increase in fat body mass but no increase in the lean body mass. This could be due to a greater degree of neurologic impairment in patients requiring enteral feeding, or to the higher intake of fat associated with gastrostomy tube feeding.<a class="elsevierStyleCrossRef" href="#bib0010"><span class="elsevierStyleSup">2</span></a></p><p id="par0235" class="elsevierStylePara elsevierViewall">The main limitation of our study was the small sample size, which was compounded by the division of the sample into groups, although the sample was representative of the catchment population of a regional referral hospital, of considerable size, and the results were statistically significant. Nevertheless, it would be interesting to expand the scope of this investigation with additional studies allowing a comparison of nutritional status with its actual impact on quality of life.</p><p id="par0240" class="elsevierStylePara elsevierViewall">To conclude, a higher proportion of patients with CP and more severe neurologic impairment are more likely to experience undernutrition, whereas one third of patients with less severe forms of CP exhibited overweight or obesity. Although anthropometry is a widely accessible and very useful tool for nutritional assessment, BIA can be a helpful addition for the non-invasive monitoring of body composition, as traditional anthropometric methods underestimate fat body mass and overestimate lean body mass. When we adjusted the lean body mass for height, we found greater deficits in patients at level V, so it would be relevant to analyse obtained results in relation to age, height and sex. Due to all of the above, performance of both routine and individualised evaluations in patients with CP are needed to ensure adequate nutritional management and to improve the health, quality of life and developmental outcomes in these patients.</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Conflicts of interest</span><p id="par0245" class="elsevierStylePara elsevierViewall">The authors have no conflicts of interest to declare.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:11 [ 0 => array:3 [ "identificador" => "xres1336766" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Introduction" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Material and methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1230928" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1336767" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Introducción" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Material y métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusiones" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1230927" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:2 [ "identificador" => "sec0010" "titulo" => "Materials and methods" ] 6 => array:2 [ "identificador" => "sec0015" "titulo" => "Results" ] 7 => array:2 [ "identificador" => "sec0020" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0025" "titulo" => "Conflicts of interest" ] 9 => array:2 [ "identificador" => "xack462240" "titulo" => "Acknowledgments" ] 10 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2019-02-11" "fechaAceptado" => "2019-06-12" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1230928" "palabras" => array:6 [ 0 => "Cerebral palsy" 1 => "Nutrition" 2 => "Bioimpedance" 3 => "Anthropometry" 4 => "Overweight" 5 => "Obesity" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1230927" "palabras" => array:6 [ 0 => "Parálisis cerebral" 1 => "Nutrición" 2 => "Bioimpedanciometría" 3 => "Antropometría" 4 => "Sobrepeso" 5 => "Obesidad" ] ] ] ] "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="spar0050" class="elsevierStyleSimplePara elsevierViewall">Cerebral palsy (CP) is the most frequent cause of motor disability in the paediatric age. The aim of this article is the study of the nutritional status of patients with CP followed-up in a reference hospital, as well as the relationship between neurological and nutritional state.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Material and methods</span><p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">A cross-sectional, observational, descriptive and analytical study was conducted on a sample consisting of 4–15 year old patients with CP with Gross Motor Function Classification System (GMFCS) grades III–IV–V, from a specialised paediatric hospital reference area. An interview (collection of general data, medications and nutritional habits), anthropometric study and bioimpedance (BIA) measurements were carried out.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">The study included 69 patients (recruitment 84.15%), with a mean age of 10.46<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.43 years, and 50.7% females. The distribution according to GMFCS scale was: grade III (36.2%), grade IV (29%), and grade V (34.8%). According to weight for height: moderate malnutrition 21.8% (grade V: 33.3%), severe malnutrition 5.8% (grade V: 12.6%), overweight/obesity 23.2% (grade III: 24%, grade IV: 35%). Adequate level of lean mass for height: grade III (36%), grade IV (55%), and grade V (16.7%). Fat excess: grade III (36%), grade IV (40%), and grade V (29.2%). Fat mass comparison: BIA 6.89<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.64<span class="elsevierStyleHsp" style=""></span>kg versus anthropometry 5.56<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.43<span class="elsevierStyleHsp" style=""></span>kg.</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">In CP grade GMFCS V, the weight deficit associated with a decrease in lean body mass is common. Patients with CP grades GMFCS III–IV have a significant prevalence of overweight/obesity. Anthropometry is a useful tool for nutritional assessment in children with CP, although fat levels could be underestimated.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Introduction" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Material 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">Introducción</span><p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">La parálisis cerebral (PC) es la causa más frecuente de discapacidad motora en edad pediátrica. El objetivo es estudiar la situación nutricional de los pacientes con PC controlados en una unidad de referencia, así como la relación entre la afectación neurológica y nutricional.</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Material y métodos</span><p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">Estudio transversal, observacional, descriptivo y analítico en el que se han incluido pacientes con PC con grados III–IV–V (GMFCS) procedentes del área de influencia de un hospital pediátrico de referencia, con edades de 4–15 años. Se ha realizado: encuesta (con recogida de datos generales, medicaciones y hábitos nutricionales), estudio antropométrico y bioimpedanciometría (BIA).</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">N<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>69 pacientes (reclutamiento 84,15%). Edad media 10,46<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0.43 años, el 50,7% mujeres. Distribución según GMFCS: grado III (36,2%), grado IV (29%), grado V (34,8%). Según el peso para la talla: desnutrición moderada el 21,8% (grado V: 33,3%), desnutrición grave el 5,8% (grado V: 12.6%), sobrepeso/obesidad el 23,2% (grado III: 24%; grado IV: 35%). Nivel adecuado de masa magra para su talla: grado III (36%), grado IV (55%), grado V (16,7%). Exceso de grasa: grado III (36%), grado IV (40%), grado V (29,2%). Comparación de masa grasa: BIA 6,89<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>0,64<span class="elsevierStyleHsp" style=""></span>kg Vs antropometría 5,56<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4,43<span class="elsevierStyleHsp" style=""></span>kg.</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusiones</span><p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">En PC grado GMFCS V es frecuente el déficit de peso asociado a disminución de masa magra para su talla. Los pacientes con PC grados GMFCS III-IV presentan una prevalencia llamativa de sobrepeso/obesidad. La antropometría es una herramienta útil para la valoración nutricional en niños con PC, aunque los niveles de grasa tienden a infravalorarse.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Introducción" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Material 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: Fernández JMMdZ, Arnal IR, Segura JLP, Romero RG, Martínez GR. Situación nutricional en una población con parálisis cerebral moderada-grave: más allá del peso. An Pediatr (Barc). 2020;92:192–199.</p>" ] ] "multimedia" => array:6 [ 0 => array:8 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1177 "Ancho" => 2139 "Tamanyo" => 69521 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0005" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Percentage of lean mass relative to the ideal mass by GMFCS level.</p>" ] ] 1 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0010" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:1 [ "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="\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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Total sample (<span class="elsevierStyleItalic">n<span class="elsevierStyleHsp" style=""></span>=</span><span class="elsevierStyleHsp" style=""></span>69) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Level III \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Level IV \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Level V \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">p \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">Follow-up in nutrition clinic \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">42% (<span class="elsevierStyleItalic">n =</span> 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">16% (<span class="elsevierStyleItalic">n =</span> 4) \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">40% (<span class="elsevierStyleItalic">n =</span> 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">70.8% (<span class="elsevierStyleItalic">n =</span> 17) \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">.001 \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">Require supplementation with polymeric formula \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">34.8% (<span class="elsevierStyleItalic">n =</span> 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">8% (<span class="elsevierStyleItalic">n =</span> 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">35% (<span class="elsevierStyleItalic">n =</span> 7) \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">62.5% (<span class="elsevierStyleItalic">n =</span> 15) \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">.001 \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">Dosage (kcal/day) \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">561 ± 64 \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">225 ± 75 \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">492 ± 85 \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">638 ± 87 \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">.100 \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">Require thickening agents \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">18.8% (<span class="elsevierStyleItalic">n =</span> 13) \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% (<span class="elsevierStyleItalic">n =</span> 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">20% (<span class="elsevierStyleItalic">n =</span> 4) \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">33.3% (<span class="elsevierStyleItalic">n =</span> 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">.032 \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">Gastrostomy \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">13% (<span class="elsevierStyleItalic">n =</span> 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">0% (<span class="elsevierStyleItalic">n =</span> 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">5% (<span class="elsevierStyleItalic">n =</span> 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">33.3% (<span class="elsevierStyleItalic">n =</span> 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">.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2291927.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Frequency of follow-up in specialty nutrition clinic and of use of nutritional supplementation by GMFCS level.</p>" ] ] 2 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0015" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">AC, arm circumference; BMI, body mass index; BSF, biceps skin fold; CI, confidence interval; H, height; SD, standard deviation; SISF, suprailiac skinfold; SSSF, subscapular skinfold; TSF, triceps skinfold; W, weight; WFH, weight for height.</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="\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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Total sample \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Level III \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Level IV \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Level V \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">P</span> \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 " colspan="6" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Anthropometric measures, mean (95% CI)</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">H (<span class="elsevierStyleItalic">z</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">−2.98 (−3.32; −2.64) \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">−2.42 (−2.92; −1.93) \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">−3.29 (−4.04; −2.54) \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">−3.3 (−3.85; −2.75) \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">.045 \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">W (<span class="elsevierStyleItalic">z</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">−1.60 (−1.85; −1.35) \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">−1.13 (−1.59; −0.67) \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">−1.55 (−1.96; −1.13) \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">−2.15 (−2.50; −1.80) \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">.002 \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">IMC (<span class="elsevierStyleItalic">z</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">−0.61 (−0.92; −0.30) \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">−0.19 (−0.75;0.38) \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">−0.38 (−0.96;0.21) \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">−1.25 (−1.69; −0.80) \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">.007 \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">AC (<span class="elsevierStyleItalic">z</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">−0.79 (−1.14; −0.43) \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">−0.33 (−0.85;0.19) \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">−0.47 (−1.17;0.23) \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">−1.52 (−2.12; −0.93) \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">.007 \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">TSF (<span class="elsevierStyleItalic">z</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">−1.11 (−1.44; −0.78) \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">−0.61 (−1.08; −0.14) \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">−0.97 (−1.76; −0.17) \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">−1.75 (−2.19; −1.31) \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">.002 \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">BSF (<span class="elsevierStyleItalic">z</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">−1.27 (−1.59; −0.95) \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">−0.98 (−1.50; −0.46) \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">−1.17 (−1.94; −0.41) \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">−1.64 (−2.09; −1.21) \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">.201 \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">SSSF (<span class="elsevierStyleItalic">z</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">−1.07 (−1.41; −0.73) \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">−0.54 (−1.26;0.18) \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">−1.18 (−1.76; −0.59) \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">−1.54 (−1.96; −1.13) \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">.060 \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">SISF (<span class="elsevierStyleItalic">z</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">−0.63 (−0.90; −0.35) \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">−0.23 (−072;0.26) \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">−0.85 (−1.32; −0.38) \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">−0.85 (−1.34; −0.37) \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">.096 \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 " colspan="6" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Weight for height and body composition, mean<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>SD</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">WFH (%) \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">97.0 ± 24.7 \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">101.5 ± 4.9 \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">105.1 ± 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">85.52 ± 3.7 \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">.007 \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">Fat mass, % \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">18.2 ± 7.2 \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">20.5 ± 1.4 \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">18.2 ± 1.6 \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">16.0 ± 1.3 \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">.123 \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">Fat mass, kg \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">5.6 ± 4.4 \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">7.4 ± 1.1 \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">5.9 ± 1.0 \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">3.5 ± 0.4 \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">.029 \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">Lean mass, kg \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">21.4 ± 9.1 \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">25.1 ± 2.2 \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">22.6 ± 2.0 \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">16.6 ± 0.8 \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">.003 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2291928.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Anthropometric and body composition measures (calculated based on anthropometric measures) by GMFCS level.</p>" ] ] 3 => array:8 [ "identificador" => "tbl0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0020" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">WFH, weight-for-height.</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="\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">CP level \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Total sample (<span class="elsevierStyleItalic">n<span class="elsevierStyleHsp" style=""></span>=</span><span class="elsevierStyleHsp" style=""></span>69) \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Level III \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Level IV \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Level V \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">Overweight/obesity: WFH<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>110% \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">23.2% (<span class="elsevierStyleItalic">n =</span> 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">24% (<span class="elsevierStyleItalic">n =</span> 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">35% (<span class="elsevierStyleItalic">n =</span> 7) \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">12.5%(<span class="elsevierStyleItalic">n =</span> 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">Normal: WFH 90–110% \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">33.3% (<span class="elsevierStyleItalic">n =</span> 23) \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">48% (<span class="elsevierStyleItalic">n =</span> 12) \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">30% (<span class="elsevierStyleItalic">n =</span> 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">20.8% (<span class="elsevierStyleItalic">n =</span> 5) \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">Mild underweight: WFH 80–90% \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">15.9% (<span class="elsevierStyleItalic">n =</span> 11) \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">8% (<span class="elsevierStyleItalic">n =</span> 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">20% (<span class="elsevierStyleItalic">n =</span> 4) \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">20.8% (<span class="elsevierStyleItalic">n =</span> 5) \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">Moderate underweight: WFH 70–79% \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">21.8% (<span class="elsevierStyleItalic">n =</span> 15) \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">16% (<span class="elsevierStyleItalic">n =</span> 4) \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">15% (<span class="elsevierStyleItalic">n =</span> 3) \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">33.3% (<span class="elsevierStyleItalic">n =</span> 8) \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">Severe underweight: WFH<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>70% \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">5.8% (<span class="elsevierStyleItalic">n =</span> 4) \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% (<span class="elsevierStyleItalic">n =</span> 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">0% (<span class="elsevierStyleItalic">n =</span> 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">12.6% (<span class="elsevierStyleItalic">n =</span> 3) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2291926.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Nutritional status of patients by GMFCS level.</p>" ] ] 4 => array:8 [ "identificador" => "tbl0020" "etiqueta" => "Table 4" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0025" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:1 [ "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="\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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Total sample \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Level III \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Level IV \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Level V \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">P</span> \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">Total water, % \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">64.1 ± 1.3 \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">60.4 ± 1.3 \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">63.8 ± 2.5 \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">68.3 ± 2.7 \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">.043 \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">Extracellular water, % \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">42.7 ± 1.1 \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">42.2 ± 1.5 \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">42.3 ± 1.7 \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">43.5 ± 2.3 \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">.996 \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">Intracellular water, % \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">57.4 ± 1.1 \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">57.9 ± 1.5 \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">57.7 ± 1.7 \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">56.5 ± 2.3 \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">.994 \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">Lean mass, kg \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">20.0 ± 1.1 \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">23.5 ± 2.1 \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">21.3 ± 1.8 \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">15.2 ± 1.0 \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">.017 \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">Lean mass, % \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">76.9 ± 1.2 \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">73.5 ± 1.3 \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">78.0 ± 2.4 \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">79.4 ± 2.4 \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">.095 \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">Muscle mass, kg \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">12.0 ± 0.7 \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">14.3 ± 1.4 \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">13.2 ± 1.3 \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">8.5 ± 0.5 \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">.004 \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">Muscle mass, % \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">44.9 ± 1.0 \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">44.0 ± 1.1 \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">47.6 ± 1.8 \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">43.5 ± 2.0 \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">.161 \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">Cell mass, kg \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">9.6 ± 0.6 \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">11.5 ± 1.2 \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">10.7 ± 1.1 \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">6.5 ± 0.4 \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">.003 \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">Cell mass, % \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">46.6 ± 0.8 \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">48.12 ± 1.0 \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">49.1 ± 1.4 \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">43.0 ± 1.2 \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">.001 \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">Fat mass, kg \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">6.9 ± 0.6 \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">9.0 ± 1.1 \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">7.2 ± 1.4 \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">4.5 ± 0.6 \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">.011 \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">Fat mass, % \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">23.7 ± 2.1 \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">26.5 ± 1.3 \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">23.8 ± 2.4 \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">20.6 ± 2.4 \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">.111 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2291930.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Body composition calculated by bioelectrical impedance analysis (BIA) by GMFCS level.</p>" ] ] 5 => array:8 [ "identificador" => "tbl0025" "etiqueta" => "Table 5" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0030" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">BMI, body mass index; CI, confidence interval; SD, standard deviation.</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="\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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">No gastrostomy \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Gastrostomy \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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">P</span> \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 " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Anthropometric measures, mean (95% CI)</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">Height (<span class="elsevierStyleItalic">z</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">−3.24 (−3.88;−2.59) \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">−3.43 (−4.72; −2.14) \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">.745 \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">Weight (<span class="elsevierStyleItalic">z</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">−2.1 (−2.47; −1.74) \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">−2.24 (−3.17; −1.31) \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">.710 \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">BMI (<span class="elsevierStyleItalic">z</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">−1.31 (−1.76; −0.85) \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">−1.13 (−2.33;0.07) \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">.706 \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">Weight for height, % \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">89.0 ± 3.5 \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">90.6 ± 8.9 \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">.341 \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 " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">BIA, mean<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>SD</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">Total water, % \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">71.6 ± 2.9 \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">61.7 ± 5.3 \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">.088 \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">Extracellular water, % \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">42.8 ± 2.6 \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">44.9 ± 4.9 \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">.689 \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">Intracellular water, % \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">57.2 ± 2.6 \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">55.1 ± 4.9 \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">.677 \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">Lean mass, kg \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">15.9 ± 0.9 \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">13.8 ± 2.4 \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">.328 \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">Lean mass, % \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">81.8 ± 2.1 \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">74.8 ± 5.8 \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">.171 \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">Muscle mass, kg \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">9.0 ± 0.6 \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">7.7 ± 1.0 \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">.227 \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">Muscle mass, % \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">46.2 ± 2.1 \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">38.3 ± 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">.055 \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">Cell mass, kg \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">7.1 ± 0.5 \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">6.0 ± 0.8 \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">.093 \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">Cell mass, % \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">44.7 ± 1.4 \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">39.8 ± 1.9 \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">.061 \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">Fat mass, kg \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">3.8 ± 0.6 \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">5.7 ± 1.4 \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">.150 \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">Fat mass, % \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">18.3 ± 2.1 \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">25.3 ± 5.8 \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">.171 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2291929.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Anthropometric and body composition assessment by bioelectrical impedance analysis (BIA) in patients at GMFCS level V with and without a gastrostomy.</p>" ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:28 [ 0 => array:3 [ "identificador" => "bib0005" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Surveillance of cerebral palsy in Europe: a collaboration of cerebral palsy surveys and registers" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:1 [ 0 => "C. 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Year/Month | Html | Total | |
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2024 November | 4 | 5 | 9 |
2024 October | 75 | 40 | 115 |
2024 September | 66 | 60 | 126 |
2024 August | 64 | 70 | 134 |
2024 July | 51 | 47 | 98 |
2024 June | 47 | 46 | 93 |
2024 May | 44 | 29 | 73 |
2024 April | 41 | 41 | 82 |
2024 March | 55 | 33 | 88 |
2024 February | 54 | 36 | 90 |
2024 January | 43 | 24 | 67 |
2023 December | 61 | 32 | 93 |
2023 November | 53 | 30 | 83 |
2023 October | 44 | 32 | 76 |
2023 September | 35 | 24 | 59 |
2023 August | 29 | 23 | 52 |
2023 July | 29 | 25 | 54 |
2023 June | 39 | 24 | 63 |
2023 May | 34 | 31 | 65 |
2023 April | 34 | 13 | 47 |
2023 March | 57 | 33 | 90 |
2023 February | 27 | 17 | 44 |
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2022 December | 77 | 21 | 98 |
2022 November | 50 | 22 | 72 |
2022 October | 78 | 40 | 118 |
2022 September | 31 | 25 | 56 |
2022 August | 39 | 45 | 84 |
2022 July | 52 | 43 | 95 |
2022 June | 44 | 29 | 73 |
2022 May | 64 | 46 | 110 |
2022 April | 42 | 37 | 79 |
2022 March | 66 | 56 | 122 |
2022 February | 58 | 27 | 85 |
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2021 December | 55 | 47 | 102 |
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2021 August | 47 | 48 | 95 |
2021 July | 45 | 33 | 78 |
2021 June | 47 | 45 | 92 |
2021 May | 65 | 36 | 101 |
2021 April | 178 | 78 | 256 |
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2020 December | 80 | 24 | 104 |
2020 November | 58 | 18 | 76 |
2020 October | 42 | 16 | 58 |
2020 September | 134 | 30 | 164 |
2020 August | 85 | 18 | 103 |
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