Research letter
Comparison of predictive equations of resting energy expenditure in older adults with chronic obstructive pulmonary disease
F.M.M. Ramosa, L.T. Rossatob, B.R. Ramiresc, G.D. Pimenteld, L.S. Venâncioe, F.L. Orsattif, E.P. de Oliveirab,
Corresponding author
a Department of Public Health, Nutrition and Metabolism Center (CeMENutri), São Paulo State University (UNESP), Botucatu, São Paulo, Brazil
b School of Medicine, Federal University of Uberlandia (UFU), Uberlandia, Minas Gerais, Brazil
c Methodist University of Piracicaba (UNIMEP), Lins, São Paulo, Brazil
d Clinical and Sports Nutrition Research Laboratory (Labince), Federal University of Goias (UFG), Faculty of Nutrition, Goiania, Goias, Brazil
e Paulista University (UNIP), Bauru, São Paulo, Brazil
f Exercise Biology Laboratory (BioEx), Institute of Health Sciences, Federal University of Triangulo Mineiro (UFTM), Uberaba, Minas Gerais, Brazil
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"tienePdf" => "en" "tieneTextoCompleto" => "en" "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "43" "paginaFinal" => "45" ] ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 2079 "Ancho" => 2666 "Tamanyo" => 436921 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">(A and B) Chest tomography in the patient no. 1. (A) Image at diagnosis revealed left lower lobe atelectasis (blue arrow). (B) Image after treatment with laser photocoagulation revealing no abnormalities. (C and D) Chest tomography in the patient no. 2 (C) Image at diagnosis showed a lesion in the posterior-lateral wall of the trachea (blue arrow). (D) Image after endoscopic treatment with no abnormalities.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "M.T. Redondo, E. Padrão, S. Guimarães, G. Fernandes, A. Magalhães" "autores" => array:5 [ 0 => array:2 [ "nombre" => "M.T." "apellidos" => "Redondo" ] 1 => array:2 [ "nombre" => "E." "apellidos" => "Padrão" ] 2 => array:2 [ "nombre" => "S." "apellidos" => "Guimarães" ] 3 => array:2 [ "nombre" => "G." "apellidos" => "Fernandes" ] 4 => array:2 [ "nombre" => "A." "apellidos" => "Magalhães" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2173511516300926?idApp=UINPBA00004E" "url" => "/21735115/0000002300000001/v1_201701210027/S2173511516300926/v1_201701210027/en/main.assets" ] "itemAnterior" => array:19 [ "pii" => "S2173511516301105" "issn" => "21735115" "doi" => "10.1016/j.rppnen.2016.08.003" "estado" => "S300" "fechaPublicacion" => "2017-01-01" "aid" => "1194" "copyright" => "Sociedade Portuguesa de Pneumologia" "documento" => "simple-article" "crossmark" => 1 "licencia" => "http://creativecommons.org/licenses/by-nc-nd/4.0/" "subdocumento" => "cor" "cita" => "Rev Port Pneumol. 2017;23:39-40" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:2 [ "total" => 2319 "formatos" => array:3 [ "EPUB" => 230 "HTML" => 1220 "PDF" => 869 ] ] "en" => array:10 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Research letter</span>" "titulo" => "Peak cough flow measurement with a pneumotacograph and a portable peak flow meter in patients with neuromuscular diseases" "tienePdf" => "en" "tieneTextoCompleto" => "en" "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "39" "paginaFinal" => "40" ] ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1277 "Ancho" => 1650 "Tamanyo" => 83074 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Coughs by patient: Bland–Altman plot of the agreement in measuring peak cough flow (L/min) between the pneumotochograph measurement system and the peak flow meter. The difference between two measurements (pneumotachograph-peak flow meter) is plotted against the mean of two measurements. Solid line indicates the line of equality (no difference between measurements). Three dashed lines indicate the difference between measurements (bias) and the upper and lower 95% limits of agreement (bias<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>1.96SD). The bias (95% limits of agreement) was 87.11<span class="elsevierStyleHsp" style=""></span>L/min (−82.29 to 256.50<span class="elsevierStyleHsp" style=""></span>L/min).</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "P.R. Rodrigues, P.U. Brito, L. Fernandes, C. Rodrigues, A. Reis, J. Moita" "autores" => array:6 [ 0 => array:2 [ "nombre" => "P.R." "apellidos" => "Rodrigues" ] 1 => array:2 [ "nombre" => "P.U." "apellidos" => "Brito" ] 2 => array:2 [ "nombre" => "L." "apellidos" => "Fernandes" ] 3 => array:2 [ "nombre" => "C." "apellidos" => "Rodrigues" ] 4 => array:2 [ "nombre" => "A." "apellidos" => "Reis" ] 5 => array:2 [ "nombre" => "J." "apellidos" => "Moita" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2173511516301105?idApp=UINPBA00004E" "url" => "/21735115/0000002300000001/v1_201701210027/S2173511516301105/v1_201701210027/en/main.assets" ] "en" => array:15 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Research letter</span>" "titulo" => "Comparison of predictive equations of resting energy expenditure in older adults with chronic obstructive pulmonary disease" "tieneTextoCompleto" => true "saludo" => "Dear Editor," "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "40" "paginaFinal" => "42" ] ] "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "F.M.M. Ramos, L.T. Rossato, B.R. Ramires, G.D. Pimentel, L.S. Venâncio, F.L. Orsatti, E.P. de Oliveira" "autores" => array:7 [ 0 => array:3 [ "nombre" => "F.M.M." "apellidos" => "Ramos" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 1 => array:3 [ "nombre" => "L.T." "apellidos" => "Rossato" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] 2 => array:3 [ "nombre" => "B.R." "apellidos" => "Ramires" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">c</span>" "identificador" => "aff0015" ] ] ] 3 => array:3 [ "nombre" => "G.D." "apellidos" => "Pimentel" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">d</span>" "identificador" => "aff0020" ] ] ] 4 => array:3 [ "nombre" => "L.S." "apellidos" => "Venâncio" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">e</span>" "identificador" => "aff0025" ] ] ] 5 => array:3 [ "nombre" => "F.L." "apellidos" => "Orsatti" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">f</span>" "identificador" => "aff0030" ] ] ] 6 => array:4 [ "nombre" => "E.P." "apellidos" => "de Oliveira" "email" => array:1 [ 0 => "erick_po@yahoo.com.br" ] "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">*</span>" "identificador" => "cor0005" ] ] ] ] "afiliaciones" => array:6 [ 0 => array:3 [ "entidad" => "Department of Public Health, Nutrition and Metabolism Center (CeMENutri), São Paulo State University (UNESP), Botucatu, São Paulo, Brazil" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "School of Medicine, Federal University of Uberlandia (UFU), Uberlandia, Minas Gerais, Brazil" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Methodist University of Piracicaba (UNIMEP), Lins, São Paulo, Brazil" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Clinical and Sports Nutrition Research Laboratory (Labince), Federal University of Goias (UFG), Faculty of Nutrition, Goiania, Goias, Brazil" "etiqueta" => "d" "identificador" => "aff0020" ] 4 => array:3 [ "entidad" => "Paulista University (UNIP), Bauru, São Paulo, Brazil" "etiqueta" => "e" "identificador" => "aff0025" ] 5 => array:3 [ "entidad" => "Exercise Biology Laboratory (BioEx), Institute of Health Sciences, Federal University of Triangulo Mineiro (UFTM), Uberaba, Minas Gerais, Brazil" "etiqueta" => "f" "identificador" => "aff0030" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1029 "Ancho" => 1598 "Tamanyo" => 76571 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Comparison of REE values (mean<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>SD) of predictive equations and indirect calorimetry. (a) not significantly different from values measured by indirect calorimetry; (b) significantly different from values measured by indirect calorimetry. <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><p id="par0005" class="elsevierStylePara elsevierViewall">Chronic obstructive pulmonary disease (COPD) increases resting energy expenditure (REE)<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">1</span></a> due to chronic inflammation and greater effort for breathing.<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">2</span></a> REE is the major component of total energy expenditure and the correct measurement of REE is essential to offer a proper nutritional management and consequently prevent or treat malnutrition. Up till now, there has been no consensus about which REE equation is the best to use in clinical practice to match the energy intake of older adults with COPD. Therefore, we aimed to compare predictive equations of REE with indirect calorimetry (IC) in older adults with COPD.</p><p id="par0010" class="elsevierStylePara elsevierViewall">We evaluated 20 older adults with COPD (16 men and 4 women) and all subjects were selected from a pulmonary rehabilitation program of a private health service. The details of sample selection and recruitment have been previously described.<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">1</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">Demographic and anthropometric data were used to calculate the REE using gender-specific predictive equations<a class="elsevierStyleCrossRef" href="#bib0055"><span class="elsevierStyleSup">3</span></a>: Mifflin St. Jeor equation, Harris & Benedict, World Health Organization (WHO)1, WHO2, Owen et al., and de Oliveira et al.</p><p id="par0020" class="elsevierStylePara elsevierViewall">Indirect calorimetry (Metalyzer 3B – R2 (Cortex), breath by breath) was used for determining REE after calibration of barometric pressure (960<span class="elsevierStyleHsp" style=""></span>mbar) and room air (O<span class="elsevierStyleInf">2</span>: 20.93/CO<span class="elsevierStyleInf">2</span>: 0.03<span class="elsevierStyleHsp" style=""></span>vol%) using a known gas mixture (White Martins, O<span class="elsevierStyleInf">2</span>: 15.94/CO<span class="elsevierStyleInf">2</span>: 5.01<span class="elsevierStyleHsp" style=""></span>vol%) and volume (3-L Hans Rudolph syringe, <span class="elsevierStyleItalic">V</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>3.0<span class="elsevierStyleHsp" style=""></span>L). REE was determined by Weir<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">4</span></a> equation after measurement of oxygen consumption (VO<span class="elsevierStyleInf">2</span>) and production of carbon dioxide (VCO<span class="elsevierStyleInf">2</span>). The participants were asked to use a mask and remain silent until the steady state condition was reached over a 5-min period and 20% variation of VO<span class="elsevierStyleInf">2</span>, 12% variation of VCO<span class="elsevierStyleInf">2</span> and 10% variation of RQ. Both room temperature (25.0<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>2.0<span class="elsevierStyleHsp" style=""></span>°C) and relative humidity (47.0<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>4.5%) were controlled. None of the individuals presented flu, cold or cough during the assessment and all individuals were asked to avoid exercise and caffeinated or alcoholic beverages consumption during the 48<span class="elsevierStyleHsp" style=""></span>h that preceded the assessment. The REE evaluation was performed after an overnight fast and all individuals came to the lab in the morning.</p><p id="par0025" class="elsevierStylePara elsevierViewall">Weight (kg) and height (cm) were measured for determining body mass index (BMI). Waist circumference (WC), absolute fat, fat-free mass (FFM), and muscle mass were also measured, as described previously.<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">1</span></a></p><p id="par0030" class="elsevierStylePara elsevierViewall">In statistical analyses, data were presented as mean<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>standard derivation and percentage. ANOVA one-way was used to compare the differences between REE values from equations and indirect calorimetry, then Scheffe <span class="elsevierStyleItalic">post hoc</span> test was used to identify which equation value was equal to the REE value measured by IC. Intraclass correlation coefficient and Bland–Altman were applied to compare the differences between REE values from IC and tested equations. The software STATISTICA 6.0 was used for the statistical analyses and significance level was at <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05.</p><p id="par0035" class="elsevierStylePara elsevierViewall">Regarding sociodemographic characteristics, the sample consisted of older adults, white (85%), not workers and mostly male gender (80%). The anthropometric data showed high adiposity with suboptimal muscle mass, as described previously.<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">1</span></a></p><p id="par0040" class="elsevierStylePara elsevierViewall">All equations, except de Oliveira et al., underestimated the values of REE measured by indirect calorimetry (indirect calorimetry<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1643<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>383<span class="elsevierStyleHsp" style=""></span>kcal/day, Mifflin St. Jeor equation<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1243<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>197<span class="elsevierStyleHsp" style=""></span>kcal/day (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05), Harris and Benedict<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1237.3<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>161<span class="elsevierStyleHsp" style=""></span>kcal/day (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05), WHO1<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1300<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>144<span class="elsevierStyleHsp" style=""></span>kcal/day (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05), WHO2<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1322<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>131<span class="elsevierStyleHsp" style=""></span>kcal/day (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05), Owen<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1453<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>171<span class="elsevierStyleHsp" style=""></span>kcal/day (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05) and de Oliveira<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1572.2<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>213<span class="elsevierStyleHsp" style=""></span>kcal/day (<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>0.05)) (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>).</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0045" class="elsevierStylePara elsevierViewall">Furthermore, after Bland and Altman analysis, Owen and de Oliveira equations were significantly associated with indirect calorimetry, whereas Owen et al. underestimated the REE in −190.2 (−343; −37.5)<span class="elsevierStyleHsp" style=""></span>kcal/day or −9.9 (−20.1; 0.2)% and de Oliveira overestimated the REE in 302.3 (198.5; 406.3)<span class="elsevierStyleHsp" style=""></span>kcal/day or 19.6 (12.4; 26.7)% (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>).</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0050" class="elsevierStylePara elsevierViewall">Although de Oliveira equation showed similar mean values compared to IC, and an association was found between IC and de Oliveira and Owen equation, we noted high intervals of agreements between these equations and IC. For example, de Oliveira overestimated the REE in 302<span class="elsevierStyleHsp" style=""></span>kcal and Owen underestimated in 190<span class="elsevierStyleHsp" style=""></span>kcal, which can result in high or low energy intake, respectively. Hence, we suggest that none of the equations tested in the present study should be used in clinical practice for older adults with COPD because it is equally undesirable to overestimate energy expenditure as to underestimate it. Both extremes are counterproductive and might have consequences for the patient because overfeeding leads to higher carbon dioxide production which increases the work of breathing<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">5</span></a>; and low energy and protein intake can result in muscle mass loss<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">6</span></a> that is associated with higher mortality in older adults<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">7</span></a> and in COPD patients.<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">8</span></a> Thus, none of the equations was ideal for estimating REE in older adults with COPD and there is a need to create new equations for this specific population.</p><p id="par0055" class="elsevierStylePara elsevierViewall">The main limitation of the present study was that the small sample size constituted mainly by male patients does not permit speculation about these results in general COPD population and more studies evaluating higher number of older adults with COPD are needed.</p><p id="par0060" class="elsevierStylePara elsevierViewall">Therefore, we concluded that the majority of equations underestimated the REE and all equations showed low association with IC. Therefore, we suggest that the REE equations used at present study should not be used in older adults with COPD.</p><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0005">Conflicts of interest</span><p id="par0065" class="elsevierStylePara elsevierViewall">The authors have no conflicts of interest to declare.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:3 [ 0 => array:2 [ "identificador" => "sec0005" "titulo" => "Conflicts of interest" ] 1 => array:2 [ "identificador" => "xack265529" "titulo" => "Acknowledgments" ] 2 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "multimedia" => array:2 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1029 "Ancho" => 1598 "Tamanyo" => 76571 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Comparison of REE values (mean<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>SD) of predictive equations and indirect calorimetry. (a) not significantly different from values measured by indirect calorimetry; (b) significantly different from values measured by indirect calorimetry. <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05.</p>" ] ] 1 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:3 [ "leyenda" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">ICC<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>intra-class correlation coefficient; ICC CI 95%<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>confidence intervals for ICC; <span class="elsevierStyleItalic">d</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>mean difference; CI 95%/<span class="elsevierStyleItalic">d</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>confidence intervals for mean difference; SD<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>standard derivation; CL 95%<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>concordance limits for the mean difference; <span class="elsevierStyleItalic">d</span>% percentage difference.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Equations \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">ICC \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">ICC CI 95% \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">d</span> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">CI 95%/<span class="elsevierStyleItalic">d</span> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">DP/<span class="elsevierStyleItalic">d</span> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">CL 95% \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">d</span>% \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">CI 95%/<span class="elsevierStyleItalic">d</span>% \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">SD/<span class="elsevierStyleItalic">d</span>% \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">CL 95%/<span class="elsevierStyleItalic">d</span>% \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Mifflin \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.18 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.28; 0.58 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−401.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−552.9; −249.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">324.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−1036.6; 234.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−25.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−35.3; −16.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">19.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−65.1; 13.2 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Harris \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.01 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.44; 0.45 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−404.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−568.2; −242.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">347.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−1086.7; 275.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−25.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−36.2; −15.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">22.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−69.7; 18.2 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">WHO \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.07 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.39; 0.50 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−342.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−502.8; −181.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">343.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−1114.7; 330.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−20.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−31.4; −10.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">22.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−65.6; −46.9 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">WHO2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.13 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.34; 0.54 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−321.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−481.6; −160.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">342.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−993.2; 350.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−19.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−29.4; −8.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">22.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−62.3; 24.3 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Owen \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.37<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">*</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−0.08; 0.70 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−190.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−343.0; −37.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">326.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−829.9; 449.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−9.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−20.1; 0.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">21.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−52.5; 32.5 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">de Oliveira \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.47<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">*</span></a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.04; 0.76 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">302.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">198.5; 406.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">222.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">−132.8; 737.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">19.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">12.4; 26.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">15.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−10.2; 49.4 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1325792.png" ] ] ] "notaPie" => array:1 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "*" "nota" => "<p class="elsevierStyleNotepara" id="npar0005"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05 – significant association with indirect calorimetry.</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Coefficient analysis of intra-class correlation coefficient (ICC) and Bland and Altman of to estimate REE.</p>" ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:8 [ 0 => array:3 [ "identificador" => "bib0045" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Resting energy expenditure and carbohydrate oxidation are higher in elderly patients with COPD: a case control study" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "B.R. 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| Year/Month | Html | Total | |
|---|---|---|---|
| 2024 November | 14 | 10 | 24 |
| 2024 October | 70 | 43 | 113 |
| 2024 September | 64 | 33 | 97 |
| 2024 August | 86 | 41 | 127 |
| 2024 July | 63 | 30 | 93 |
| 2024 June | 77 | 26 | 103 |
| 2024 May | 46 | 37 | 83 |
| 2024 April | 43 | 27 | 70 |
| 2024 March | 52 | 19 | 71 |
| 2024 February | 79 | 35 | 114 |
| 2024 January | 49 | 24 | 73 |
| 2023 December | 38 | 28 | 66 |
| 2023 November | 38 | 65 | 103 |
| 2023 October | 31 | 35 | 66 |
| 2023 September | 27 | 39 | 66 |
| 2023 August | 20 | 12 | 32 |
| 2023 July | 24 | 33 | 57 |
| 2023 June | 34 | 17 | 51 |
| 2023 May | 35 | 27 | 62 |
| 2023 April | 37 | 16 | 53 |
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