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GOLD Staging System is Appropriate to Predict Mortality in Older People With Chronic Obstructive Pulmonary Disease
El sistema de estadificación GOLD es adecuado para predecir la mortalidad en personas de edad avanzada con enfermedad pulmonar obstructiva crónica
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Staging System is Appropriate to Predict Mortality in Older People With Chronic Obstructive Pulmonary Disease" "tieneTextoCompleto" => true "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "365" "paginaFinal" => "370" ] ] "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "Claudio Pedone, Renato Giua, Nicola Scichilone, Vincenzo Bellia, Raffaele Antonelli-Incalzi" "autores" => array:5 [ 0 => array:3 [ "nombre" => "Claudio" "apellidos" => "Pedone" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 1 => array:4 [ "nombre" => "Renato" "apellidos" => "Giua" "email" => array:1 [ 0 => "renatogiua@alice.it" ] "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">*</span>" "identificador" => "cor0005" ] ] ] 2 => array:3 [ "nombre" => "Nicola" "apellidos" => "Scichilone" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] 3 => array:3 [ "nombre" => "Vincenzo" "apellidos" => "Bellia" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] ] ] 4 => array:3 [ "nombre" => "Raffaele" "apellidos" => "Antonelli-Incalzi" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] ] "afiliaciones" => array:2 [ 0 => array:3 [ "entidad" => "Area di Geriatria, Università Campus Bio-Medico di Roma, Rome, Italy" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Dipartimento Biomedico di Medicina Interna e Specialistica (Di.Bi.MIS), Università di Palermo, Palermo, Italy" "etiqueta" => "b" "identificador" => "aff0010" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "El sistema de estadificación GOLD es adecuado para predecir la mortalidad en personas de edad avanzada con enfermedad pulmonar obstructiva crónica" ] ] "resumenGrafico" => array:2 [ "original" => 1 "multimedia" => array:5 [ "identificador" => "fig0015" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => false "mostrarDisplay" => true "figura" => array:1 [ 0 => array:4 [ "imagen" => "fx1.jpeg" "Alto" => 807 "Ancho" => 1333 "Tamanyo" => 74559 ] ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">For several years, the grading of chronic obstructive pulmonary disease (COPD) severity proposed by the Global Initiative for Obstructive Lung Disease (GOLD) has been based on Forced Expiratory Volume in 1 second (FEV1) only. This classification could not adequately predict clinical outcomes<a class="elsevierStyleCrossRefs" href="#bib0125"><span class="elsevierStyleSup">1,2</span></a> and therefore other prognostic indices, such as the BODE index<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">3</span></a> have been proposed to stratify the severity of COPD. In 2011, the GOLD proposed a new classification of COPD severity that in addition to the level of FEV1 reduction also took into account severity of symptoms and frequency of exacerbations,<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">4</span></a> thus generating a panel of four different stages of disease severity (A through D). This new classification, however, does not seem to have better prognostic capacity,<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">5</span></a> and the GOLD group has recently proposed a new classification that merges the GOLD 2007 and GOLD 2011 classes.<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">6</span></a> In this document, the severity of obstruction expressed as reduction of FEV1 is still considered a very important prognostic factor at the population level.</p><p id="par0010" class="elsevierStylePara elsevierViewall">One potential issue with the GOLD classification is that FEV1 is expressed as the percent of the value predicted by estimating equations (FEV1PP). This approach may introduce bias, and it has been shown that GOLD classification can lead to misclassification of older patients.<a class="elsevierStyleCrossRefs" href="#bib0155"><span class="elsevierStyleSup">7,8</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">Due to these limitation, alternative ways of standardizing FEV1 have been proposed, such as FEV1 standardized residuals, FEV1 divided by height squared or cubed (FEV1/Ht<span class="elsevierStyleSup">3</span>) or expressed as a function of the sex-specific first percentile.<a class="elsevierStyleCrossRef" href="#bib0165"><span class="elsevierStyleSup">9</span></a> FEV1/Ht<span class="elsevierStyleSup">3</span> may be more informative than FEV1PP to predict clinical outcomes even in elderly patients.<a class="elsevierStyleCrossRefs" href="#bib0165"><span class="elsevierStyleSup">9–11</span></a> Our hypothesis is that part of the suboptimal prognostic capacity of the GOLD stratification comes from the use of equations developed in population that are different from the one that gives raise to the COPD cases. In this study, we evaluated how well the GOLD classification stratifies the mortality risk when FEV1 is expressed as percentage of the value predicted by an equation developed in the same population that gave rise to cases, externally developed equations, or as FEV1/Ht<span class="elsevierStyleSup">3</span>.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Study population</span><p id="par0020" class="elsevierStylePara elsevierViewall">Between January 1996 and July 1999 a total of 1970 participants were recruited within the context of the SaRA (Salute Respiratoria nell’Anziano – Respiratory Health in the Elderly) study. Details on the SaRA project are available elsewhere.<a class="elsevierStyleCrossRef" href="#bib0180"><span class="elsevierStyleSup">12</span></a> This is a multi-center Italian project investigating various aspects of chronic airway diseases in people ≥65 years of age attending pulmonary or geriatric outpatient clinics for any reason. Participants were in stable conditions when the spirometry was performed. Enrollment was on a consecutive basis. The study design was approved by the Ethical Committee of the coordinating center (#276/2012). From this dataset, we selected 1296 participants with post-bronchodilator (postBD) spirometry. We then excluded people with a history of asthma (<span class="elsevierStyleItalic">N</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>224). Of the remaining participants, information on vital status as of December 2010 was available for 882; these patients had clinical and spirometric characteristics comparable to those of subjects lost to follow-up. Causes of death were derived from death certificates, and were available for 74% of participants.</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Pulmonary function tests</span><p id="par0025" class="elsevierStylePara elsevierViewall">All the centers were equipped with an identical fully computerized water-sealed Stead-Wells spirometer (Baires System; Biomedin; Padua, Italy) that met the standards of the American Thoracic Society recommendations for diagnostic spirometry.<a class="elsevierStyleCrossRef" href="#bib0185"><span class="elsevierStyleSup">13</span></a> At baseline, tests were performed with a standardized technique in all centers and a quality control process was successfully implemented: all the centers achieved a high quality performance in spirometry.<a class="elsevierStyleCrossRef" href="#bib0180"><span class="elsevierStyleSup">12</span></a> Obstruction was defined using a fixed cut-off of 0.7 for FEV1/forced vital capacity (FVC) considering the postBD spirometry. Predicted values of FEV1 were derived from equations based on the same sample of the cases included in this study (FEV1-SARA)<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">14</span></a> and the European Respiratory Society (FEV1-ERS).<a class="elsevierStyleCrossRef" href="#bib0195"><span class="elsevierStyleSup">15</span></a> FEV1PP was categorized according to the classes proposed by the GOLD guidelines to stratify severity of obstruction (FEV1PP<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>80%, 80%<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>FEV1PP<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>50%, 50%<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>FEV1PP<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>30%, and FEV1PP<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>30%). Severity of bronchial obstruction was also classified according to quartiles of FEV1/Ht<span class="elsevierStyleSup">3</span>.</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Analytic approach</span><p id="par0030" class="elsevierStylePara elsevierViewall">The demographic and clinical characteristics were compared across COPD severity groups defined using FEV1-SARA. We included in this analysis the distance walked in 6<span class="elsevierStyleHsp" style=""></span>min, expressed as percent predicted,<a class="elsevierStyleCrossRef" href="#bib0200"><span class="elsevierStyleSup">16</span></a> and comorbid diseases such as ischemic heart disease, heart failure, and stroke. Smoking was analyzed as cumulative exposure (pack-years). The multi-dimensional BODE index was also included, as it is able to predict mortality in older people.<a class="elsevierStyleCrossRef" href="#bib0205"><span class="elsevierStyleSup">17</span></a> The SaRA questionnaire did not include a specific item on exacerbations, therefore we combined two of the Saint George Respiratory Questionnaire (SGRQ) items (“During the past 3 months how many severe or very unpleasant attacks of chest trouble have you had?” and “How long did the worst attack of chest trouble last?”) to define exacerbations as an attack that lasted for at least 3 days. The risk of dying was estimated using the Kaplan–Meier method, differences in the survival risk was evaluated using the log-rank test. The relative hazard of dying was estimated using a Cox proportional hazard model. The assumptions of such a model were checked by inspecting the distribution of the Schoenfeld residuals over time.</p><p id="par0035" class="elsevierStylePara elsevierViewall">To estimate the discriminative capacity of each risk stratification tool, we estimated the relative increase in risk of each stratum compared to the preceding stratum, i.e. GOLD I vs. not obstructed, GOLD II vs. GOLD I and so on. The goodness of fit of these models was evaluated using the likelihood ratio test, and the overall diagnostic performance of these models was evaluated using the <span class="elsevierStyleItalic">C</span>-statistic. The analyses were performed for both medium-term (5 years) and very long-term (15 years) mortality.</p></span></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Results</span><p id="par0040" class="elsevierStylePara elsevierViewall">The mean age of our sample was 73.2 (SD: 6), men were 57.8%. Characteristics of the population according to GOLD stages determined using the FEV1-SARA are reported in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>. Participants with bronchial obstruction were predominantly males, especially in classes III and IV. Beside having a higher BODE index, participants in these classes tended to have lower body mass index, higher exposure to cigarette smoking, and higher prevalence of cerebro-vascular disease. We did not observe a linear relationship between GOLD stages and prevalence of comorbidities; for example the prevalence of ischemic heart disease, heart failure, and stroke was higher in GOLD class III than in GOLD class IV.</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0045" class="elsevierStylePara elsevierViewall">The FEV1 predicted by the ERS equation was on average 150<span class="elsevierStyleHsp" style=""></span>ml smaller compared to the SARA equation. Consequently, 21 patients classified in class I, 8 patients classified in class II, and 3 patients classified in class III using the ERS equation were classified in class II, III, and IV, respectively, according to the SARA equation. This notwithstanding, the general pattern across GOLD classes based on FEV1-ERS was not different from that observed using FEV1-SARA. Likewise, no clear specific relationships in clinical characteristics were found after stratification by quartiles of FEV1/Ht<span class="elsevierStyleSup">3</span> (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>).</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0050" class="elsevierStylePara elsevierViewall">In participants with COPD, the average distance walked in 6′ was 67.6<span class="elsevierStyleHsp" style=""></span>m. In the same group, 15% reported at least one exacerbation in the preceding 3 months, and 24.5% had a modified Medical Research Council dyspnea index<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>2. The global SGRQ score was 39. We found no differences in the capacity of the different severity grading methods to stratify exercise capacity expressed by the distance walked in 6′ (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>, panel A). We found that the other important clinical outcomes (exacerbations, dyspnea, and quality of life) differed only across the first three GOLD classes, while participants in class IV did not differ from patients in class III. Using quartiles of FEV1/Ht<span class="elsevierStyleSup">3</span>, instead, the linear association was evident across all categories (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>, panels B–D).</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0055" class="elsevierStylePara elsevierViewall">Data on vital status were gathered after a median of 13 years (range: 0.5–15). The risk for mortality was 19.5% at 5 years and 53,7% at the end of follow-up. <a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a> shows the Kaplan–Meier curves for 15-year mortality risk stratified by stages. Considering the 5-years mortality, all the classification systems showed a fairly linear relationship with mortality. Nonetheless, as reported in <a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>, the incremental changes in risk associated with each class were not statistically significant, except for the increase in risk from stage II to stage III of both GOLD classifications. The goodness of fit of the quartiles of FEV1/Ht<span class="elsevierStyleSup">3</span> was somewhat worse compared to the GOLD classifications, but the overall discriminative capacity expressed by the c statistics was 0.6 for all models. When the models were adjusted for age and sex, the incremental association between the GOLD stages defined using the SARA predicting equation was only marginally affected, while for GOLD stages defined using the ERS predicting equation the linear association was more evident, with significant increases of hazard ratio in group II vs. I, group III vs. II and group IV vs. III. No significant incremental risk was observed for quartiles of FEV1/Ht<span class="elsevierStyleSup">3</span>.</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><p id="par0060" class="elsevierStylePara elsevierViewall">Considering the 15-years mortality risk (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>), the linear association across severity stages is more evident for the two GOLD classifications, as also confirmed by the significant increments in the hazard ratio, shown in <a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>. Although the linear association was evident also for quartiles of FEV1/Ht<span class="elsevierStyleSup">3</span>, the increment in the hazard ratio was significant only for stage III compared to stage II. The goodness of fitness of the models obtained with the GOLD classification system was marginally better compared to that of the model including quartiles of FEV1/Ht<span class="elsevierStyleSup">3</span>, but the overall discriminative capacity did not change between the three classification systems. After correction for age and sex, no substantial changes were observed.</p><p id="par0065" class="elsevierStylePara elsevierViewall">Finally, when only deaths from respiratory causes were taken into account, the overall pattern did not change, although the estimates were more unstable due to the relatively low number of events (46 overall, 28 in the first 5 years).</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Discussion</span><p id="par0070" class="elsevierStylePara elsevierViewall">Our data indicate that the GOLD classification system is superior to a stratification based on quartiles of FEV1 standardized by height in predicting mortality in older persons with COPD. This finding is partly in contrast with other reports<a class="elsevierStyleCrossRefs" href="#bib0165"><span class="elsevierStyleSup">9–11</span></a> showing that FEV1/Ht<span class="elsevierStyleSup">3</span> is superior to FEV1PP in stratifying the mortality risk. One possible explanation for this discrepancy is that previous studies on this issue have compared groups of FEV1PP and FEV1/Ht<span class="elsevierStyleSup">3</span> based on percentiles, and not GOLD classes vs. percentiles of FEV1/Ht<span class="elsevierStyleSup">3</span>. One exception is a study by Miller et al.<a class="elsevierStyleCrossRef" href="#bib0210"><span class="elsevierStyleSup">18</span></a> that compared GOLD classes vs. arbitrarily defined groups of FEV1 divided by height squared (FEV1/Ht<span class="elsevierStyleSup">2</span>), in which the authors found that FEV1/Ht<span class="elsevierStyleSup">2</span> could better stratify mean survival compared to GOLD classes. In this study, however, the cut-off to define bronchial obstruction was set at FEV1/FVC<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.89, and the authors did not provide information on the mortality risk across groups.</p><p id="par0075" class="elsevierStylePara elsevierViewall">A possible explanation of our findings is that the GOLD classification uses pragmatic cut-off of FEV1PP based on consensus, clinical experience, and previous epidemiological data,<a class="elsevierStyleCrossRef" href="#bib0215"><span class="elsevierStyleSup">19</span></a> and in this study we compared it with a distribution-based classification. The use of arbitrary cut-off (as in the GOLD classification) may better fit the risk of mortality compared to distribution-based cut-off (i.e. quartiles) if the relationship between FEV1 and risk was not linear, while the opposite would be true if the relationship was linear. An alternative explanation is that FEV1PP, on which the GOLD classification is based, better captures the underlying pathophysiologic changes compared to FEV1/Ht<span class="elsevierStyleSup">3</span>. Several studies, however, starting from the seminal observation by Fletcher and Peto,<a class="elsevierStyleCrossRef" href="#bib0220"><span class="elsevierStyleSup">20</span></a> indicate that FEV1 standardized using height is a good indicator of reduction of pulmonary function with respect to the mortality risk. Further studies investigating different cut-off for FEV1/Ht<span class="elsevierStyleSup">3</span> are needed to better explore this issue.</p><p id="par0080" class="elsevierStylePara elsevierViewall">To our knowledge, this is the first study comparing the discriminative capacity of GOLD classification and quartiles of FEV1/Ht<span class="elsevierStyleSup">3</span> with respect to walking speed, dyspnea, rate of exacerbations, and disease-specific quality of life in COPD. In contrast to what we observed for mortality, quartiles of FEV1/Ht<span class="elsevierStyleSup">3</span> could better stratify more specific clinical indicators (dyspnea, exacerbations, disease-specific quality of life) compared to the GOLD classification, while no grading system could stratify an overall indicator of exercise capacity such as the distance walked in 6′. The same observation made above about mortality risk may apply for these findings: the distribution-based classification may have a better fit because the relationship is linear. Furthermore, these outcomes were evaluated at the same time of the spirometry, therefore the discriminative capacity of the classification systems are relevant to the actual clinical conditions, not to a future outcome such as mortality. Based on these data, the GOLD classification seems better suited to identify people at generic risk for mortality, but not patients with worse health status related to pulmonary problems. In keeping with this hypothesis, the discriminative capacity of GOLD stages is better for very long-term compared to medium-term survival, and there was no difference in the discriminative capacity for mortality from any cause or mortality from pulmonary causes.</p><p id="par0085" class="elsevierStylePara elsevierViewall">Results obtained using predicting equations developed in the same population that gave rise to the cases differed marginally from those obtained using equation developed in a different population. Thus, although guidelines recommend the use of internally developed standards,<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">21</span></a> the use of externally developed standards seem to be acceptable. Indeed, we found a relatively small discrepancy between GOLD classes assigned by FEV1-SARA or FEV1-ERS.</p><p id="par0090" class="elsevierStylePara elsevierViewall">Limitations of this study deserve consideration. An important limitation is that we do not have follow-up data on pulmonary and physical function and symptoms, therefore we cannot evaluate which classification system better identifies people with worse prognosis in terms of clinical course of disease. At the same time we cannot discriminate if some subjects has changed GOLD class during the follow-up. We used measured height, and this could introduce a bias as vertebral fractures are frequent in the older population (especially women) and COPD.<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">22</span></a> Due to this problem, people with vertebral fractures might have been misclassified as having a FEV1/ht3 higher than the real. Since vertebral fractures are a risk factor for adverse outcomes in COPD,<a class="elsevierStyleCrossRef" href="#bib0235"><span class="elsevierStyleSup">23</span></a> this bias may have caused a reduction in the discriminative capacity of FEV1/ht3. Furthermore, even if a classification basing on quartiles of FEV1/Ht<span class="elsevierStyleSup">3</span> is statistically logical considering the absence of indications from epidemiological studies, it may occur than this would not be the best method.</p><p id="par0095" class="elsevierStylePara elsevierViewall">The observed frequency of exacerbation refers to the last 3 months period and, thus, cannot be compared to that reported in other studies. for example by Hurst et al.<a class="elsevierStyleCrossRef" href="#bib0240"><span class="elsevierStyleSup">24</span></a> Indeed, we based our definition on two SGRQ items that have a time frame of only 3 months; therefore our data are not directly comparable to those reporting yearly exacerbation rates. Finally, the loss of many patients to follow-up may have biased our results on mortality. However, patients followed up and patients lost to follow up had comparable clinical characteristics.</p></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Conclusion</span><p id="par0100" class="elsevierStylePara elsevierViewall">In conclusion, our study indicates that the severity of bronchial obstruction according to GOLD classes may stratify mortality risk better than quartiles of FEV1/Ht<span class="elsevierStyleSup">3</span>, whereas the second seems to be more suited to stratify clinical outcomes, such as dyspnea, walking speed and quality of life. Concerns about the appropriateness of using externally developed reference values to calculate FEV1PP do not seem to be confirmed, at least for GOLD classification.</p></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Authors’ contribution</span><p id="par0105" class="elsevierStylePara elsevierViewall">Each have substantially contributed to data collection, manuscript drafting and revision. All authors read the final manuscript and approved it for publication.</p></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Conflict of interest</span><p id="par0110" class="elsevierStylePara elsevierViewall">The authors declare they have no conflict of interest.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:13 [ 0 => array:3 [ "identificador" => "xres1049986" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0010" "titulo" => "Introduction" ] 1 => array:2 [ "identificador" => "abst0015" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0020" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0025" "titulo" => "Conclusion" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1001008" "titulo" => "Keywords" ] 2 => array:2 [ "identificador" => "xpalclavsec1001009" "titulo" => "Abbreviations" ] 3 => array:3 [ "identificador" => "xres1049985" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0030" "titulo" => "Introducción" ] 1 => array:2 [ "identificador" => "abst0035" "titulo" => "Métodos" ] 2 => array:2 [ "identificador" => "abst0040" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0045" "titulo" => "Conclusión" ] ] ] 4 => array:2 [ "identificador" => "xpalclavsec1001010" "titulo" => "Palabras clave" ] 5 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 6 => array:3 [ "identificador" => "sec0010" "titulo" => "Methods" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Study population" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Pulmonary function tests" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "Analytic approach" ] ] ] 7 => array:2 [ "identificador" => "sec0030" "titulo" => "Results" ] 8 => array:2 [ "identificador" => "sec0035" "titulo" => "Discussion" ] 9 => array:2 [ "identificador" => "sec0040" "titulo" => "Conclusion" ] 10 => array:2 [ "identificador" => "sec0045" "titulo" => "Authors’ contribution" ] 11 => array:2 [ "identificador" => "sec0050" "titulo" => "Conflict of interest" ] 12 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2017-09-20" "fechaAceptado" => "2018-01-15" "PalabrasClave" => array:2 [ "en" => array:2 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1001008" "palabras" => array:4 [ 0 => "GOLD" 1 => "Chronic obstructive pulmonary disease" 2 => "Elderly" 3 => "FEV1" ] ] 1 => array:4 [ "clase" => "abr" "titulo" => "Abbreviations" "identificador" => "xpalclavsec1001009" "palabras" => array:15 [ 0 => "BODE index" 1 => "COPD" 2 => "ERS" 3 => "FEV1" 4 => "FEV1/Ht<span class="elsevierStyleSup">2</span>" 5 => "FEV1/Ht<span class="elsevierStyleSup">3</span>" 6 => "FEV1PP" 7 => "FEV1-ERS" 8 => "FEV1-SARA" 9 => "FVC" 10 => "FVCPP" 11 => "GOLD" 12 => "postBD" 13 => "SaRA" 14 => "SGRQ" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1001010" "palabras" => array:4 [ 0 => "GOLD" 1 => "Enfermedad pulmonar obstructiva crónica" 2 => "Ancianos" 3 => "FEV<span class="elsevierStyleInf">1</span>" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "resumen" => "<span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Introduction</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">In the new GOLD classification the reduction of FEV1, expressed as percentage of predicted value (FEV1PP), is considered an important prognostic factor. However, the use of FEV1PP may introduce bias, especially if based on equations derived from populations different from the one under study. We evaluated how well the GOLD classification stratifies the mortality risk when FEV1PP is based on an equation developed in the same population that gave rise to cases, externally developed equations, or as FEV1 divided by cubed height (FEV1/Ht<span class="elsevierStyleSup">3</span>).</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">We studied 882 participants aged ≥65 years. Bronchial obstruction was defined using a fixed cut-off of 0.7 for FEV1/FVC. Predicted values of FEV1 were derived from equations based on the same sample of the cases included in this study and from the European Respiratory Society equations. Severity of bronchial obstruction was also classified according to quartiles of FEV1/Ht<span class="elsevierStyleSup">3</span>.</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">All the classification systems showed a non-statistically significant linear tendency with 5-years mortality risk. For the 15-years mortality, the linear trend across severity stages is more evident for GOLD classifications, with significant increments in the hazard ratio. Stratification by FEV1/Ht<span class="elsevierStyleSup">3</span> could better discriminate the functional status of participants.</p></span> <span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0030">Conclusion</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">The severity of bronchial obstruction according to GOLD classes may stratify mortality risk better than quartiles of FEV1/Ht<span class="elsevierStyleSup">3</span>, whereas the second seems to be more suited to stratify the risk of clinical outcomes. Concerns about the use of externally developed reference values to calculate FEV1PP do not seem confirmed, at least for GOLD classification.</p></span>" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Graphical abstract" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Introduction" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Methods" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Results" ] 4 => array:2 [ "identificador" => "abst0025" "titulo" => "Conclusion" ] ] "titulo" => "Abstract" ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "<span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Introducción</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">En la nueva clasificación GOLD, la reducción del FEV<span class="elsevierStyleInf">1</span> expresada como porcentaje del valor predicho (FEV<span class="elsevierStyleInf">1</span>PP) se considera un factor pronóstico importante. Sin embargo, usar el FEV<span class="elsevierStyleInf">1</span>PP puede introducir sesgos, especialmente si se basa en ecuaciones derivadas de poblaciones diferentes de la que se estudia. Se ha evaluado cómo de adecuadamente estratifica GOLD el riesgo de mortalidad cuando el FEV<span class="elsevierStyleInf">1</span>PP se basa en una ecuación desarrollada con la misma población en la que se dieron los casos, usando ecuaciones desarrolladas externamente, o con el FEV<span class="elsevierStyleInf">1</span> dividido por la altura al cubo (FEV<span class="elsevierStyleInf">1</span>/A<span class="elsevierStyleSup">3</span>).</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Métodos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Estudiamos a 882 participantes de edad ≥<span class="elsevierStyleHsp" style=""></span>65 años. La obstrucción bronquial se definió utilizando un punto de corte fijo de 0,7 para FEV<span class="elsevierStyleInf">1</span>/FVC. Los valores pronosticados de FEV<span class="elsevierStyleInf">1</span> se derivaron de ecuaciones basadas en la misma muestra de los casos incluidos en este estudio y de las ecuaciones de la <span class="elsevierStyleItalic">European Respiratory Society</span>. La gravedad de la obstrucción bronquial también se clasificó de acuerdo con los cuartiles de FEV<span class="elsevierStyleInf">1</span>/A<span class="elsevierStyleSup">3</span>.</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Todos los sistemas de clasificación mostraron una tendencia lineal estadísticamente no significativa en el riesgo de mortalidad a 5 años. Para la mortalidad a 15 años, la tendencia lineal a través de los diferentes estadios de gravedad es más evidente para los estadios GOLD, con incrementos significativos en la razón de riesgo. La estratificación por FEV<span class="elsevierStyleInf">1</span>/A<span class="elsevierStyleSup">3</span> podría discriminar mejor el estado funcional de los participantes.</p></span> <span id="abst0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0055">Conclusión</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">La gravedad de la obstrucción bronquial según la estadificación GOLD puede estratificar mejor el riesgo de mortalidad que los cuartiles de FEV<span class="elsevierStyleInf">1</span>/A<span class="elsevierStyleSup">3</span>. Sin embargo, lo segundo parece el método más adecuado para estratificar el riesgo de resultados clínicos. Las reticencias respecto al uso de valores de referencia desarrollados externamente para calcular FEV<span class="elsevierStyleInf">1</span>PP no parecen confirmarse, al menos para la clasificación GOLD.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0030" "titulo" => "Introducción" ] 1 => array:2 [ "identificador" => "abst0035" "titulo" => "Métodos" ] 2 => array:2 [ "identificador" => "abst0040" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0045" "titulo" => "Conclusión" ] ] ] ] "multimedia" => array:6 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 2828 "Ancho" => 1488 "Tamanyo" => 229513 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Distribution of walked distance (A), rate of exacerbations (B), dyspnea (C), and St. George Respiratory Questionnaire (D) according to COPD severity rated by GOLD or quartiles of FEV1/Ht<span class="elsevierStyleSup">3</span>.</p>" ] ] 1 => array:7 [ "identificador" => "fig0010" "etiqueta" => "Fig. 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 3087 "Ancho" => 1419 "Tamanyo" => 294478 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Kaplan–Meier curves for 15-years risk of mortality, according to COPD severity rated by GOLD, considering FEV1-SARA (panel A) and FEV1-ERS (panel B), or quartiles of FEV1/Ht<span class="elsevierStyleSup">3</span> (panel C).</p>" ] ] 2 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">FEV1PP postBD: forced expiratory volume in 1 second of post-bronchodilator spirometry; FVCPP postBD: forced vital capacity of post-bronchodilator spirometry; 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="table-head " align="" valign="top" scope="col"> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col">Not obstructed \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col">GOLD 1 \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col">GOLD 2 \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col">GOLD 3 \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col">GOLD 4 \t\t\t\t\t\t\n \t\t\t\t</th></tr><tr title="table-row"><th class="td" title="table-head " align="" valign="top" scope="col" style="border-bottom: 2px solid black"> \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">N</span>: 535 \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">N</span>: 122 \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">N</span>: 139 \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">N</span>: 69 \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">N</span>: 17 \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">Mean age (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">73 (6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">74 (6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">73 (5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">73 (6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">72 (6) \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">Sex (men) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">44 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">78 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">75 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">87 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">94 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Body mass index \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">26.4 (4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">25.7 (3.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">26.2 (4.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">24.9 (4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">23.5 (3.1) \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">FVCPP postBD \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">98.9 (17.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">95.7 (11.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">64.5 (8.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">40.8 (6.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">25.7 (3.4) \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">FEV1PP postBD \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">88.2 (15.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">100.6 (12.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">79.6 (13.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">67.3 (13.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">57.4 (15) \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">BODE index \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1 (1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1 (1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2 (2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5 (2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">7 (2) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Pack/year \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12 (22) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">35 (34) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">38 (37) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">48 (37) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">37 (33) \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">Ischemic heart disease \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">7.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.9 \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">Heart failure \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.8 \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">History of stroke \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">6.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">7.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Diabetes mellitus \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">17.6 \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">Peripheral artery disease \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">6.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.9 \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">Malignancies \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">7.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1784133.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Characteristics of the sample according to GOLD classification (predicted value obtained with SARA equation<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">14</span></a>).</p>" ] ] 3 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at2" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">FEV1PP postBD: forced expiratory volume in 1 second of post-bronchodilator spirometry; FVCPP postBD: forced vital capacity of post-bronchodilator spirometry; 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="table-head " align="" valign="top" scope="col"> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col">Not obstructed \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col">Qtl. I \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col">Qtl. II \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col">Qtl. III \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col">Qtl. IV \t\t\t\t\t\t\n \t\t\t\t</th></tr><tr title="table-row"><th class="td" title="table-head " align="" valign="top" scope="col" style="border-bottom: 2px solid black"> \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">N</span>: 535 \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">N</span>: 89 \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">N</span>: 89 \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">N</span>: 83 \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">N</span>: 86 \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">Mean age (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">73 (6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">73 (6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">74 (5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">73 (6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">74 (6) \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">Sex (men) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">44 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">90 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">75 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">70 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">81 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Body mass index \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">26.4 (4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">26.1 (2.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">25.7 (4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">26.4 (4.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">24.5 (3.8) \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">FVCPP postBD \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">98.9 (17.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">97.6 (11.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">77.6 (9.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">59.9 (12.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">38.6 (9.5) \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">FEV1PP postBD \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">88.2 (15.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">101.1 (12.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">88.5 (12.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">77.2 (16.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">65.8 (15.2) \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">BODE index \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1 (1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1 (1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2 (2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3 (2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5 (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">Pack/year \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12 (22) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">39 (32) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">37 (37) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">37 (39) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">43 (37) \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">Ischemic heart disease \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">15.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.5 \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">Heart failure \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.6 \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">History of stroke \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">6.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.7 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Diabetes mellitus \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.3 \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">Peripheral artery disease \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.5 \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">Malignancies \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.3 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1784132.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Characteristics of the sample according to quartiles of FEV1 divided by squared height.</p>" ] ] 4 => array:8 [ "identificador" => "tbl0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at3" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">FEV1/Ht<span class="elsevierStyleSup">3</span>: forced expiratory volume in 1 second divided by height cubed.</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="" valign="top" scope="col" style="border-bottom: 2px solid black"> \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">GOLD (FEV1-SARA) \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">GOLD (FEV1-ERS) \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">Quartiles of FEV1/Ht<span class="elsevierStyleSup">3</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" title="table-entry " colspan="4" align="left" valign="top"><span class="elsevierStyleItalic">5-years mortality</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Not obstructed \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1 \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"><span class="elsevierStyleHsp" style=""></span>Stage I \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.22 (0.74–1.99) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.25 (0.79–1.98) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.24 (0.71–2.16) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Stage II \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.84 (1.08–3.15) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.88 (1.13–3.13) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.33 (0.68–2.63) \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"><span class="elsevierStyleHsp" style=""></span>Stage III \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.56 (0.96–2.53) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.56 (0.95–2.56) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.61 (0.9–2.88) \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"><span class="elsevierStyleHsp" style=""></span>Stage IV \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.79 (0.87–3.69) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.04 (0.96–4.34) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.38 (0.84–2.27) \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"><span class="elsevierStyleHsp" style=""></span>Log-likelihood \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">49.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">52.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">44.2 \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"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">C</span>-statistic \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.625 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.626 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.623 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="4" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="4" align="left" valign="top"><span class="elsevierStyleItalic">15-years mortality</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Not obstructed \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1 \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"><span class="elsevierStyleHsp" style=""></span>Stage I \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.24 (0.94–1.63) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.31 (1.02–1.69) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.17 (0.85–1.6) \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"><span class="elsevierStyleHsp" style=""></span>Stage II \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.52 (1.11–2.09) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.5 (1.1–2.03) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.29 (0.87–1.93) \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"><span class="elsevierStyleHsp" style=""></span>Stage III \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.61 (1.16–2.25) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.52 (1.07–2.16) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.52 (1.05–2.2) \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"><span class="elsevierStyleHsp" style=""></span>Stage IV \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.89 (1.08–3.29) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.53 (1.4–4.59) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.37 (0.97–1.93) \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"><span class="elsevierStyleHsp" style=""></span>Log-likelihood \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">81.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">82.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">76.5 \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"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">C</span>-statistic \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.598 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.598 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.598 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1784131.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">Hazard ratio for mortality according to GOLD stages and quartiles of FEV1 divided by squared height. Each category is contrasted with the preceding category (e.g. GOLD I vs. not obstructed, GOLD II vs. GOLD I, etc.).</p>" ] ] 5 => array:5 [ "identificador" => "fig0015" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => false "mostrarDisplay" => true "figura" => array:1 [ 0 => array:4 [ "imagen" => "fx1.jpeg" "Alto" => 807 "Ancho" => 1333 "Tamanyo" => 74559 ] ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0015" "bibliografiaReferencia" => array:24 [ 0 => array:3 [ "identificador" => "bib0125" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Global assessment of the COPD patient: time to look beyond FEV1?" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:4 [ 0 => "A.I. Papaioannou" 1 => "S. Loukides" 2 => "K.I. Gourgoulianis" 3 => "K. 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| Year/Month | Html | Total | |
|---|---|---|---|
| 2024 November | 5 | 3 | 8 |
| 2024 October | 41 | 26 | 67 |
| 2024 September | 55 | 31 | 86 |
| 2024 August | 54 | 40 | 94 |
| 2024 July | 103 | 31 | 134 |
| 2024 June | 57 | 29 | 86 |
| 2024 May | 58 | 37 | 95 |
| 2024 April | 43 | 33 | 76 |
| 2024 March | 37 | 36 | 73 |
| 2024 February | 32 | 22 | 54 |
| 2023 March | 15 | 5 | 20 |
| 2023 February | 58 | 33 | 91 |
| 2023 January | 47 | 47 | 94 |
| 2022 December | 71 | 44 | 115 |
| 2022 November | 71 | 38 | 109 |
| 2022 October | 70 | 63 | 133 |
| 2022 September | 86 | 40 | 126 |
| 2022 August | 141 | 61 | 202 |
| 2022 July | 102 | 62 | 164 |
| 2022 June | 46 | 43 | 89 |
| 2022 May | 52 | 39 | 91 |
| 2022 April | 47 | 22 | 69 |
| 2022 March | 56 | 48 | 104 |
| 2022 February | 60 | 28 | 88 |
| 2022 January | 57 | 42 | 99 |
| 2021 December | 74 | 35 | 109 |
| 2021 November | 60 | 39 | 99 |
| 2021 October | 109 | 50 | 159 |
| 2021 September | 76 | 47 | 123 |
| 2021 August | 75 | 38 | 113 |
| 2021 July | 55 | 28 | 83 |
| 2021 June | 96 | 41 | 137 |
| 2021 May | 63 | 41 | 104 |
| 2021 April | 152 | 103 | 255 |
| 2021 March | 45 | 20 | 65 |
| 2021 February | 29 | 29 | 58 |
| 2021 January | 22 | 17 | 39 |
| 2020 December | 35 | 27 | 62 |
| 2020 November | 34 | 24 | 58 |
| 2020 October | 38 | 30 | 68 |
| 2020 September | 32 | 14 | 46 |
| 2020 August | 30 | 16 | 46 |
| 2020 July | 37 | 26 | 63 |
| 2020 March | 23 | 4 | 27 |
| 2020 February | 57 | 15 | 72 |
| 2020 January | 75 | 24 | 99 |
| 2019 December | 84 | 21 | 105 |
| 2019 November | 45 | 15 | 60 |
| 2019 October | 61 | 14 | 75 |
| 2019 September | 83 | 13 | 96 |
| 2019 August | 35 | 16 | 51 |
| 2019 July | 27 | 30 | 57 |
| 2019 June | 27 | 17 | 44 |
| 2019 May | 29 | 18 | 47 |
| 2019 April | 41 | 32 | 73 |
| 2019 March | 52 | 33 | 85 |
| 2019 February | 33 | 19 | 52 |
| 2019 January | 51 | 25 | 76 |
| 2018 December | 3 | 1 | 4 |
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