Original Article
Study of 5 Volatile Organic Compounds in Exhaled Breath in Chronic Obstructive Pulmonary Disease
Estudio de 5 compuestos orgánicos volátiles en aire exhalado en la enfermedad pulmonar obstructiva crónica
José Javier Jareño-Estebana, M. Ángeles Muñoz-Lucasb,
, Óscar Gómez-Martínc, Sergio Utrilla-Trigod, Carlos Gutiérrez-Ortegae, Antonio Aguilar-Rosf, Luis Collado-Yurritag, Luis Miguel Callol-Sánchezh
Corresponding author
a Servicio de Neumología, Hospital Central de la Defensa, Universidad de Alcalá de Henares; IMIDEF, Alcalá de Henares, Madrid, Spain
b Instituto Mixto de Investigación Biosanitaria de la Defensa (IMIDEF), Hospital Central de la Defensa, Madrid, Spain
c Instituto Mixto de Investigación Biosanitaria de la Defensa (IMIDEF), Madrid, Spain
d Universidad Complutense de Madrid, Madrid, Spain
e Unidad de Apoyo a la Investigación, Hospital Central de la Defensa, Madrid, Spain
f Dpto. CC Farmacéuticas, Facultad de Farmacia, Universidad San Pablo CEU, Madrid, Spain
g Dpto. de Medicina, Universidad Complutense de Madrid, Madrid, Spain
h Dpto. de Medicina, Facultad de Medicina, Universidad de Alcalá, Instituto Mixto de Investigación Biosanitaria de la Defensa (IMIDEF), Alcalá de Henares, Madrid, Spain
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CC Farmacéuticas, Facultad de Farmacia, Universidad San Pablo CEU, Madrid, Spain" "etiqueta" => "f" "identificador" => "aff0030" ] 6 => array:3 [ "entidad" => "Dpto. de Medicina, Universidad Complutense de Madrid, Madrid, Spain" "etiqueta" => "g" "identificador" => "aff0035" ] 7 => array:3 [ "entidad" => "Dpto. de Medicina, Facultad de Medicina, Universidad de Alcalá, Instituto Mixto de Investigación Biosanitaria de la Defensa (IMIDEF), Alcalá de Henares, Madrid, Spain" "etiqueta" => "h" "identificador" => "aff0040" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Estudio de 5 compuestos orgánicos volátiles en aire exhalado en la enfermedad pulmonar obstructiva crónica" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0010" "etiqueta" => "Fig. 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1290 "Ancho" => 3125 "Tamanyo" => 281028 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Sample total ion current (TIC) chromatograms from the different study groups. Hexanal can be observed in the TIC of COPD and smoker control groups, but not in the former smoker control group.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Chronic obstructive pulmonary disease (COPD) is defined as a respiratory disease characterized by chronic, progressive airflow limitation that is not fully reversible. The main symptoms are dyspnea and cough, sometimes accompanied by expectoration. COPD patients have exacerbations that vary in severity depending on comorbidities.<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">1</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">Smoking is the most important risk factor in the development of COPD, and evidence shows that the risk is proportional to the accumulated consumption of cigarettes.<a class="elsevierStyleCrossRef" href="#bib0110"><span class="elsevierStyleSup">2</span></a> In Spain, 7.6% of male and 5.5% of female non-smokers have COPD,<a class="elsevierStyleCrossRef" href="#bib0115"><span class="elsevierStyleSup">3</span></a> but this figure rises to 39.9% and 15.4% among men and women, respectively, who have smoked for more than 10 years. Other factors, such as alpha-1 antitrypsin deficiency or pneumonia in childhood, also play a role.<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">1</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">According to the World Health Organization (WHO), 2.9 million individuals a year die from COPD, and it is estimated that by 2030, it will be the third cause of death worldwide.<a class="elsevierStyleCrossRef" href="#bib0120"><span class="elsevierStyleSup">4</span></a></p><p id="par0020" class="elsevierStylePara elsevierViewall">In the EPI-SCAN epidemiological study of COPD in Spain,<a class="elsevierStyleCrossRef" href="#bib0125"><span class="elsevierStyleSup">5</span></a> 73% of confirmed cases did not have a previous diagnosis of COPD, revealing a high degree of underdiagnosis. The standard technique is spirometry, but this method carries a risk of underdiagnosis in the early stages and overdiagnosis in the advanced stages. Other useful methods are available, such as bronchoalveolar lavage or open lung biopsy, but these are too invasive for routine use.<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">6</span></a></p><p id="par0025" class="elsevierStylePara elsevierViewall">Clinicians involved in diagnosing COPD are continually on the look-out for techniques and parameters that will help them in their decision-making. Biomarkers are biological parameters that provide information on the normal or disease status of an individual or a population.<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">7</span></a> The search for biomarkers to characterize COPD is ongoing, and possible candidates have recently been investigated in sputum,<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">8</span></a> bronchoalveolar lavage,<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">9</span></a> and exhaled air.<a class="elsevierStyleCrossRefs" href="#bib0150"><span class="elsevierStyleSup">10–12</span></a></p><p id="par0030" class="elsevierStylePara elsevierViewall">Exhaled air contains a multitude of volatile organic compounds (VOCs), some of which can be identified as biomarkers that may be of use in the characterization of COPD. The analytical procedure is non-invasive and rapid, and could complement spirometry in both diagnosis and follow-up of this entity. However, this technique is susceptible to contamination of samples by multiple environmental compounds, and this needs to be taken into account when interpreting results.</p><p id="par0035" class="elsevierStylePara elsevierViewall">Tobacco smoke contains over 2000 compounds and a great quantity of free radicals and reactive oxygen and nitrogen species, which increase oxidative stress and pulmonary inflammation.<a class="elsevierStyleCrossRef" href="#bib0165"><span class="elsevierStyleSup">13</span></a> Increased oxidative stress causes lipid peroxidation. The damage generated by this chain reaction produces a large amount of VOCs, including alkanes, aldehydes, and carboxylic acids, which may be excreted by the airways. The presence of these compounds in exhaled air may be a sign of oxidative stress in the airways and the lungs. These VOCs meet the definition of inflammatory biomarkers mentioned above.</p><p id="par0040" class="elsevierStylePara elsevierViewall">A series of benchmark studies on VOCs as biomarkers for COPD in COPD patients compared to clinically healthy controls have been published.<a class="elsevierStyleCrossRefs" href="#bib0170"><span class="elsevierStyleSup">14–18</span></a> The studies are similar, but no clear conclusions can be reached as the results vary widely.</p><p id="par0045" class="elsevierStylePara elsevierViewall">The aim of our study was to determine if significant differences really exist between certain VOCs found in the exhaled air of COPD patients compared to healthy controls, and if these substances could be considered as disease biomarkers.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Patients and Methods</span><p id="par0050" class="elsevierStylePara elsevierViewall">This was a case–control study with consecutive non-probability sampling. A total of 157 volunteers were selected among the employees and patients of the Hospital Central de la Defensa “Gomez Ulla” and the General Air Force Headquarters between October 2014 and December 2015. Two study groups were established, one consisting of 57 clinically stable COPD patients, and the other of 100 healthy controls (never smokers, former smokers, and active smokers).</p><p id="par0055" class="elsevierStylePara elsevierViewall">The inclusion criteria for the 2 groups included consent to participate in the study, age over 40 years, and a smoking status of never, former or active (according to WHO criteria). All individuals completed a questionnaire and an additional clinical examination, including a flow-volume loop. Patients in the COPD group underwent standard tests for the diagnosis and follow-up of their disease, including chest radiograph, flow-volume loop, bronchodilator testing, etc. COPD severity was classified according to the GOLD scale.</p><p id="par0060" class="elsevierStylePara elsevierViewall">Exclusion criteria consisted of any other current or previous lung or tumor disease of any organ or system, or refusal to participate in the study. No gender-based restrictions were applied.</p><p id="par0065" class="elsevierStylePara elsevierViewall">None of the participants were exposed to any special occupational environmental conditions.</p><p id="par0070" class="elsevierStylePara elsevierViewall">Subjects were informed about the aims, risks and benefits, and planned tests and techniques used for conducting the study. They were given written information before signing the informed consent form. All study data were handled in accordance with the provisions of Organic Law 15/1999 on the Protection of Personal Data, 13 December 1999, and Act 41/2002, 14 November 2002, regulating the autonomy of patients and their rights and obligations in relation to clinical information and documentation. The study protocol was approved by the Ethics and Clinical Research Committee of Hospital Central de la Defensa “Gómez Ulla”.</p><p id="par0075" class="elsevierStylePara elsevierViewall">This was a targeted chromatographic study with previous selection of the compounds to be studied. VOCs were selected as follows: (1) contaminants derived from the environment or from tobacco smoke were excluded; (2) their metabolic origin had to be known for them to meet criteria for use as biomarkers.</p><p id="par0080" class="elsevierStylePara elsevierViewall">Thus, of more than 250 VOCs in exhaled air described in the consulted literature, only 50 were preselected, on the basis of frequency. Some were endogenous compounds derived from lipid peroxidation. Others were environmental contaminants, and, lastly, another group were compounds of undetermined origin. These latter 2 groups were ruled out, as the origin of the VOCs had to be known in order to select compounds that were of real use as possible biomarkers.</p><p id="par0085" class="elsevierStylePara elsevierViewall">The final selection produced 5 VOCs that met the required criteria: 3 linear, hexanal, hepatanal and nonanal aldehydes (known metabolites of omega 3, omega 6 and omega 9 fatty acid lipid peroxidation); and 2 carboxylic acids, propanoic acid and nonanoic acid (also metabolites of fatty acid lipid peroxidation).<a class="elsevierStyleCrossRefs" href="#bib0155"><span class="elsevierStyleSup">11,12</span></a></p><p id="par0090" class="elsevierStylePara elsevierViewall">After individuals had rested for 1<span class="elsevierStyleHsp" style=""></span>h, with no oral intake or smoking, the exhaled air sample was collected in BioVOC<span class="elsevierStyleSup">®</span> breath samples. These easy-to-manage devices do not generate resistance to the passage of air and can be used for the analysis of a fixed volume. The exhaled air sample was obtained with a forced expiration maneuver. The air corresponding to the anatomical dead space passes through the BioVOC<span class="elsevierStyleSup">®</span> sampler, and the most representative possible fraction of alveolar air is collected in the chamber. The maneuver was repeated 3 times for preconcentration of the compounds. The collected air was transferred to a thermal desorption tube with capacity for absorbing compounds from C2 to C20.</p><p id="par0095" class="elsevierStylePara elsevierViewall">A sample of ambient air was simultaneously obtained from the examination room and processed in the same way as the exhaled air in order to compare VOC levels from ambient and exhaled air, and to determine endogenic or exogenic origin.</p><p id="par0100" class="elsevierStylePara elsevierViewall">All samples were stored at room temperature. The manufacturer states that samples are stable for up to 6 days, but all were analyzed within a maximum of 24<span class="elsevierStyleHsp" style=""></span>h after sampling to minimize any possible cross-reactions between the compounds, given the high concentration of water in the exhaled air.</p><p id="par0105" class="elsevierStylePara elsevierViewall">The sampling method is described in a previous paper published by our group.<a class="elsevierStyleCrossRef" href="#bib0160"><span class="elsevierStyleSup">12</span></a></p><p id="par0110" class="elsevierStylePara elsevierViewall">Two types of results were obtained depending on the limit of detection (LOD): <span class="elsevierStyleItalic">undetected compounds</span>, with a value below the LOD, and <span class="elsevierStyleItalic">detected compounds</span>, with a value above the LOD.</p><p id="par0115" class="elsevierStylePara elsevierViewall">A compound was classified as detected after 3 stages:<ul class="elsevierStyleList" id="lis0005"><li class="elsevierStyleListItem" id="lsti0005"><span class="elsevierStyleLabel">1.</span><p id="par0120" class="elsevierStylePara elsevierViewall">The area of the quantifier ion of the mass spectrum was integrated for each VOC.</p></li><li class="elsevierStyleListItem" id="lsti0010"><span class="elsevierStyleLabel">2.</span><p id="par0125" class="elsevierStylePara elsevierViewall">The area of each compound was normalized according to the area of the 207 ion (corresponding to hexamethylcyclotrisiloxane). Inorganic compound, obtained from the desorption tubes that does not interfere with the VOCs, was used as an internal reference compound.Compounds were normalized by measuring the area under the curve using the following formula:<elsevierMultimedia ident="eq0005"></elsevierMultimedia>where <span class="elsevierStyleItalic">A</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">bc</span></span> is the area under the curve of each compound.</p></li><li class="elsevierStyleListItem" id="lsti0015"><span class="elsevierStyleLabel">3.</span><p id="par0130" class="elsevierStylePara elsevierViewall">A second normalization was conducted between now normalized exhaled air and ambient air. A compound was assumed to be detected when the ratio between the value in exhaled air/ambient air was greater than 1, or when it was detected in exhaled air and not in ambient air.</p></li></ul></p><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Variables</span><p id="par0135" class="elsevierStylePara elsevierViewall">A diagnosis of COPD was taken as an independent variable.</p><p id="par0140" class="elsevierStylePara elsevierViewall">Qualitative dependent variables were the different VOCs, classified as undetected and detected. Demographic variables were sex and age.</p><p id="par0145" class="elsevierStylePara elsevierViewall">VOC distributions were verified using the Kolmogorov–Smirnov test, and median and interquartile range (IQR) were used as measures of central tendency and dispersion. Dependent variables were expressed as relative frequencies.</p><p id="par0150" class="elsevierStylePara elsevierViewall">The association between independent and dependent categorical variables was confirmed by odds ratio, based on logistic regression and the corresponding 95% confidence interval.</p><p id="par0155" class="elsevierStylePara elsevierViewall">The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of VOCs were calculated to evaluate their use as a diagnostic test for COPD.</p><p id="par0160" class="elsevierStylePara elsevierViewall">A <span class="elsevierStyleItalic">P</span>-value of <.05 was considered statistically significant, and the statistical package used was SPSS<span class="elsevierStyleSup">®</span> version 20.</p></span></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Results</span><p id="par0165" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a> summarizes the demographic characteristics of the study population. The control group comprised 100 healthy volunteers, with a mean age of 49 (9) years, and the COPD group comprised 57 patients, mean age 73.6 (9.5) years. Distribution by sex was 49% men and 51% women in the control group, and 89% men and 11% women in the COPD group. Thirty-three percent of the control group were smokers, 28% former smokers, and 39% never smokers, with a mean pack-year index (PYI) of 29 (20). In the COPD group, 14% were smokers, 86% were former smokers, PYI 74.4 (39.2). Fourteen percent of smokers were GOLD 1, 31.6% GOLD 2, 24.6% GOLD 3, and 29.8% GOLD 4.</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0170" class="elsevierStylePara elsevierViewall">The 2 categories differentiated by the values obtained were (a) <span class="elsevierStyleItalic">detected</span> and (b) <span class="elsevierStyleItalic">undetected</span>, according to the criteria defined in the section “Patients and methods”. Frequency distribution, which was non-normal, is shown in percentages in <a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>.</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0175" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleItalic">P</span> values calculated by logistic regression-based odds ratio show statistically significant differences in hexanal levels between patients in the COPD group and healthy controls (<span class="elsevierStyleItalic">P</span>=.023) (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>). The probability of detecting hexanal in the COPD group is 1.97 times higher than in the control group (95% CI: 1.09–3.56) (sensitivity 31.57%, specificity 84%, PPV 52.29% and NPV 68.29%). No statistically significant differences were found for the other VOCs between patients in the COPD group and the control group. No relationship was found between the detection of hexanal and age (<span class="elsevierStyleItalic">P</span>=.114), or sex (<span class="elsevierStyleItalic">P</span>=1.001) (Student's t-test and Fisher's exact test, respectively).</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0180" class="elsevierStylePara elsevierViewall">When the COPD group was compared with the never smoker control subgroup (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>), significant differences were again detected in hexanal (<span class="elsevierStyleItalic">P</span>=.015), with a 3.08-fold probability of detecting this VOC in COPD patients than in never smokers (95% CI: 1.13–8.40) (sensitivity 31.58%, specificity 89.74%, PPV 81.82% and NPV 47.30%). Significant differences in nonanal (<span class="elsevierStyleItalic">P</span>=.008) were also observed between never smoker healthy controls and the COPD group (smokers and former smokers pooled), with a 2.44-fold probability of detecting nonanal in COPD patients (95% CI: 1.17–5.08).</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><p id="par0185" class="elsevierStylePara elsevierViewall">When the COPD group was compared with the active smoker control subgroup (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a> and <a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>), no statistical significance was found in the VOCs under study. However, when the COPD group was compared with the former smoker control subgroup (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>), the presence of hexanal was found to be statistically significant. The probability of detecting hexanal in the COPD group is 4.42 times higher than in the former smoker control subgroup (95% CI: 1.10–17.73) (sensitivity 31.57%, specificity 92.85%, PPV 90% and NPV 40%).</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Discussion</span><p id="par0190" class="elsevierStylePara elsevierViewall">The main aim of this study was to determine differences between the 5 selected VOCs (hexanal, heptanal, nonanal, propanoic acid and nonanoic acid) in a COPD group and a presumably healthy control group.</p><p id="par0195" class="elsevierStylePara elsevierViewall">Statistically significant differences were found for hexanal, with a 1.94-fold probability of detecting this VOC in patients with COPD. This aldehyde is an end metabolite of lipid peroxidation of phospholipids that form the cell membranes.<a class="elsevierStyleCrossRef" href="#bib0195"><span class="elsevierStyleSup">19</span></a> Its detection in COPD patients and not in the control group suggests that oxidative stress is greater in the lower respiratory tract of the COPD patients. For a better understanding of the differences between the control group and COPD group, the controls were subdivided into “never smoker control subgroup”, “former smoker control subgroup”, and “smoker control subgroup”, and each was compared separately with the COPD group.</p><p id="par0200" class="elsevierStylePara elsevierViewall">In the first comparison between the never smoker control subgroup and the COPD group, hexanal concentrations were significantly different, with a 3.08-fold greater probability of detection in the COPD group. Likewise, differences in nonanal levels were also significant (<span class="elsevierStyleItalic">P</span>=.008). This latter finding is in line with results obtained in a previous paper, in which nonanal was associated with smoking.<a class="elsevierStyleCrossRef" href="#bib0160"><span class="elsevierStyleSup">12</span></a></p><p id="par0205" class="elsevierStylePara elsevierViewall">A similar pattern emerged for hexanal when the COPD group was compared with the former smoker control subgroup (<span class="elsevierStyleItalic">P</span>=.013).</p><p id="par0210" class="elsevierStylePara elsevierViewall">In contrast, no significant differences were found between the COPD group and the active smoker control subgroup. Our interpretation is that inflammation due to active smoking might mask COPD-specific inflammation, and that the production of VOCs due to the disease becomes of secondary importance.</p><p id="par0215" class="elsevierStylePara elsevierViewall">For the same reason, it is logical to suppose that the significant differences in hexanal between the COPD group and the former smoker control groups are due, in general, to patients quitting smoking at the time of receiving their COPD diagnosis, with the subsequent resolution of the direct inflammatory effect of tobacco.</p><p id="par0220" class="elsevierStylePara elsevierViewall">This finding confounds the evaluation of hexanal as a discriminant biomarker for COPD and rules out its use in the detection of COPD in asymptomatic smokers, one of the targets of this study. However, the low rate of COPD among active smokers (8 of the 57) means that further, larger studies are needed in this subpopulation.</p><p id="par0225" class="elsevierStylePara elsevierViewall">PPV and specificity of hexanal in the COPD group and the never-smoker and former smoker subgroups are high. In the latter case, this finding may be a useful screening tool in clinical practice, although at present the cost/benefit ratio is high compared to standard spirometry.</p><p id="par0230" class="elsevierStylePara elsevierViewall">The wide variety of analytical methods and instruments available has produced disparate results. Corradi et al.,<a class="elsevierStyleCrossRef" href="#bib0170"><span class="elsevierStyleSup">14</span></a> for example, use high-resolution liquid chromatography and mass spectrometry, while Basanta et al.<a class="elsevierStyleCrossRef" href="#bib0175"><span class="elsevierStyleSup">15</span></a> use gas chromatography and time-of-flight mass spectrometry. Both techniques, though still accepted, have certain features that make them unsuitable in this context. The first requires the gases to be dissolved in a liquid medium, and the cost-effectiveness ratio of the second is very unfavorable. In contrast, our technique – gas chromatography and mass spectrometry (GC/MS) – is used by most authors and offers good, cost-effective results.<a class="elsevierStyleCrossRefs" href="#bib0160"><span class="elsevierStyleSup">12,18,20</span></a></p><p id="par0235" class="elsevierStylePara elsevierViewall">The large range of sampling equipment (BioVOC<span class="elsevierStyleSup">®</span>, SPME, Tedlar bags<span class="elsevierStyleSup">®</span>, desorption tubes, etc.) also leads to widely varying results. In our study, we used a standard method that is useful for detecting a wide range of compounds (from C2 to C20), favoring the sustainability of the study.</p><p id="par0240" class="elsevierStylePara elsevierViewall">Taking these considerations into account, our results would be comparable with those reported by Phillips et al.,<a class="elsevierStyleCrossRef" href="#bib0190"><span class="elsevierStyleSup">18</span></a> who used the same methodology and instrumentation. These authors, however, only found differences in isoprene, a compound associated with the synthesis of cholesterol, which is not a product of lipid peroxidation. It is considered a confounding factor, and for this reason was excluded from our study.</p><p id="par0245" class="elsevierStylePara elsevierViewall">Researchers must be wary when selecting compounds as proposed biomarkers. Van Berkel et al.<a class="elsevierStyleCrossRef" href="#bib0185"><span class="elsevierStyleSup">17</span></a> found differences between COPD patients and healthy controls in a panel of 13 VOCs, and when results were restricted to 6 of these, sensitivity of 100% and specificity of 81% was achieved. In our opinion, branched hydrocarbons, which are all of uncertain origin, together with environmental contaminants and contaminants originating in tobacco smoke are unsuitable candidates for evaluation as biomarkers. Kischkel et al.,<a class="elsevierStyleCrossRef" href="#bib0200"><span class="elsevierStyleSup">20</span></a> like us, found that the origin of VOCs used in predictive models must be clearly defined. The fact that the presence of a compound is statistically significant does not make it suitable for inclusion as a biomarker. The identification of biomarkers must be well founded if data normalization and processing are to provide valuable clinical data.</p><p id="par0250" class="elsevierStylePara elsevierViewall">Most COPD studies use mathematical models with several compounds, but we only obtained 1 biomarker that could differentiate between COPD patients and healthy non-active smoker subcontrols. In contrast, the model proposed by Basanta et al.<a class="elsevierStyleCrossRef" href="#bib0175"><span class="elsevierStyleSup">15</span></a> notably increases sensitivity (90%) when only active smokers, whether COPD or control, are selected from the study groups. This increased sensitivity occurs because the statistical power is reduced when the population size is considerably reduced, i.e., from 39 to 20 active smokers with COPD, and from 32 control group smokers to only 6. These results, which at first sight appear interesting, have a significant statistical bias in terms of sample size and subgroup division.</p><p id="par0255" class="elsevierStylePara elsevierViewall">To sum up, hexanal discriminates between COPD patients and healthy never smoker and former smoker controls. Nonanal discriminates between smokers and former smokers (with or without COPD) and never smoker controls. It is essential to reach a consensus on the methodology and selection of compounds proposed as biomarkers.</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Funding</span><p id="par0260" class="elsevierStylePara elsevierViewall">This study was funded by the <span class="elsevierStyleGrantSponsor" id="gs1">Instituto de Salud Carlos III</span> (<span class="elsevierStyleGrantNumber" refid="gs1">PI07/1116</span>), SEPAR 2013 (Registry no. 135).</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Conflict of Interests</span><p id="par0265" class="elsevierStylePara elsevierViewall">The authors state they have no potential conflict of interests with any of the companies whose products or services may have been discussed in this article.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:11 [ 0 => array:3 [ "identificador" => "xres834120" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Introduction" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Method" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec830158" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres834121" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Introducción" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Método" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusiones" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec830159" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Patients and Methods" "secciones" => array:1 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Variables" ] ] ] 6 => array:2 [ "identificador" => "sec0020" "titulo" => "Results" ] 7 => array:2 [ "identificador" => "sec0025" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0030" "titulo" => "Funding" ] 9 => array:2 [ "identificador" => "sec0035" "titulo" => "Conflict of Interests" ] 10 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2016-03-07" "fechaAceptado" => "2016-09-07" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec830158" "palabras" => array:4 [ 0 => "Chronic obstructive pulmonary disease" 1 => "Volatile organic compounds" 2 => "Exhaled breath" 3 => "Oxidative stress" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec830159" "palabras" => array:4 [ 0 => "Enfermedad pulmonar obstructiva crónica" 1 => "Compuestos orgánicos volátiles" 2 => "Aire exhalado" 3 => "Estrés oxidativo" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Introduction</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">A major risk factor for chronic obstructive pulmonary disease (COPD) is tobacco smoke, which generates oxidative stress in airways, resulting in the production of volatile organic compounds (VOCs). The purpose of this study was to identify VOCs in exhaled breath and to determine their possible use as disease biomarkers.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Method</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Exhaled breath from 100 healthy volunteers, divided into 3 groups (never smokers, former smokers and active smokers) and exhaled breath from 57 COPD patients were analyzed. Samples were collected using BioVOC<span class="elsevierStyleSup">®</span> devices and transferred to universal desorption tubes. Compounds were analyzed by thermal desorption, gas chromatography and mass spectrometry. VOCs analyzed were linear aldehydes and carboxylic acids.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">The COPD group and healthy controls (never smokers and former smokers) showed statistically significant differences in hexanal concentrations, and never smokers and the COPD group showed statistically significant differences in nonanal concentrations.</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Hexanal discriminates between COPD patients and healthy non-smoking controls. Nonanal discriminates between smokers and former smokers (with and without COPD) and never smokers.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Introduction" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Method" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Introducción</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Un factor de riesgo importante para el desarrollo de la enfermedad pulmonar obstructiva crónica (EPOC) es el humo del tabaco, que genera estrés oxidativo en las vías respiratorias, dando lugar a la producción de compuestos orgánicos volátiles (VOC). El objetivo del trabajo es su identificación en el aire exhalado y su posible utilidad como biomarcadores de la enfermedad.</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Método</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Se analizó el aire exhalado de 100 voluntarios sanos, clasificados en 3 grupos (no fumadores, exfumadores y fumadores activos) y un grupo de 57 pacientes con EPOC. La muestra de aire exhalado se recogió mediante BioVOC<span class="elsevierStyleSup">®</span> y se traspasó a tubos de desorción para su posterior análisis por cromatografía de gases y espectrometría de masas. Los VOC analizados fueron aldehídos lineales y ácidos carboxílicos.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Hexanal mostró diferencias estadísticamente significativas entre el grupo EPOC y los controles sanos (no fumadores y exfumadores), y nonanal entre el grupo control no fumador y el grupo EPOC.</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusiones</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Hexanal discrimina entre pacientes con EPOC y controles sanos no fumadores y exfumadores. Nonanal diferencia entre fumadores y exfumadores (con o sin EPOC) frente a controles no fumadores.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Introducción" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Método" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusiones" ] ] ] ] "NotaPie" => array:1 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Please cite this article as: Jareño-Esteban JJ, Muñoz-Lucas MÁ, Gómez-Martín Ó, Utrilla-Trigo S, Gutiérrez-Ortega C, Aguilar-Ros A, et al. Estudio de 5 compuestos orgánicos volátiles en aire exhalado en la enfermedad pulmonar obstructiva crónica. Arch Bronconeumol. 2017;53:251–256.</p>" ] ] "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" => 895 "Ancho" => 1413 "Tamanyo" => 71336 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Detection of study VOCs by frequency.</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" => 1290 "Ancho" => 3125 "Tamanyo" => 281028 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Sample total ion current (TIC) chromatograms from the different study groups. Hexanal can be observed in the TIC of COPD and smoker control groups, but not in the former smoker control group.</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">PYI: pack-year index; 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" 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">Control (<span class="elsevierStyleItalic">n</span>=100) \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">COPD (<span class="elsevierStyleItalic">n</span>=57) \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Age (years), mean (SD)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">48.9 (9.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">73.6 (9.5) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="3" 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="3" align="left" valign="top"><span class="elsevierStyleItalic">Sex</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>Men \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">49 (49%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">51 (89%) \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>Women \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">51 (51%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">6 (11%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="3" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></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="elsevierStyleItalic">Smokers</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">33 (33%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8 (14%) \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="elsevierStyleItalic">Former smokers</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">28 (28%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">49 (86%) \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="elsevierStyleItalic">Never smokers</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">39 (39%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Smoking habit (PYI), mean (SD)</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">29 (20) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">74.4 (39.2) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1406640.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Study Group Demographics.</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">OR and 95% confidence interval based on logistic regression.</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">VOC \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">Control \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">COPD \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">P</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">Hexanal \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">1.97 (1.09–3.56) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.023 \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">Heptanal \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">0.70 (0.39–1.26) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.223 \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">Nonanal \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">1.46 (0.96–2.22) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.08 \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">Propanoic acid \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">1.05 (0.77–1.42) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.773 \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">Nonanoic acid \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">1.42 (0.74–2.75) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.291 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1406638.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Relationship Between the Presence of Markers and the Presence of COPD Compared to the Control Group.</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">OR and 95% confidence interval based on logistic regression.</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">VOC \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">COPD Group vs Never Smokers \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">P</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">COPD Group vs Smokers \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">P</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">COPD Group vs Former Smokers \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">P</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">Hexanal \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.08 (1.13–8.40) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.015 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.04 (0.55–1.98) \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">4.42 (1.10–17.73) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.013 \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">Heptanal \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.82 (0.39–1.71) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.599 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.63 (0.32–1.27) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.198 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.66 (0.314–1.37) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.265 \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">Nonanal \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.44 (1.18–5.08) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.008 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.91 (0.57–1.43) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.671 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.75 (0.866–3.55) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.092 \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">Propanoic acid \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.18 (0.78–1.78) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.428 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.85 (0.60–1.21) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.392 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.17 (0.737–1.86) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.49 \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">Nonanoic acid \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.11 (0.51–2.43) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.789 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.88 (0.67–5.30) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.212 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.60 (0.573–4.45) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.356 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1406639.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">Relationship Between the Presence of Markers and COPD Compared to the Control Subgroups Divided by Smoking Habit.</p>" ] ] 5 => array:5 [ "identificador" => "eq0005" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "(AbcVOC)(AbcSiloxane)×100" "Fichero" => "STRIPIN_si1.jpeg" "Tamanyo" => 2001 "Alto" => 35 "Ancho" => 135 ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:20 [ 0 => array:3 [ "identificador" => "bib0105" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Guía de práctica clínica para el diagnóstico y tratamiento de pacientes con enfermedad pulmonar obstructiva crónica (EPOC) – Guía Española de la EPOC (GesEPOC)" "autores" => array:1 [ 0 => array:2 [ "colaboracion" => "Grupo de trabajo de GesEPOC" "etal" => false ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/S0300-2896(12)70044-3" "Revista" => array:7 [ "tituloSerie" => "Arch Bronconeumol" "fecha" => "2012" "volumen" => "48" "numero" => "Suppl. 1" "paginaInicial" => "2" "paginaFinal" => "58" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/23116901" "web" => "Medline" ] ] ] ] ] ] ] ] 1 => array:3 [ "identificador" => "bib0110" "etiqueta" => "2" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Prevalence of COPD in Spain: impact of undiagnosed COPD on quality of life and daily life activities" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "M. 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| Year/Month | Html | Total | |
|---|---|---|---|
| 2024 November | 9 | 2 | 11 |
| 2024 October | 65 | 33 | 98 |
| 2024 September | 99 | 17 | 116 |
| 2024 August | 105 | 45 | 150 |
| 2024 July | 89 | 39 | 128 |
| 2024 June | 96 | 42 | 138 |
| 2024 May | 148 | 36 | 184 |
| 2024 April | 58 | 39 | 97 |
| 2024 March | 39 | 14 | 53 |
| 2024 February | 43 | 27 | 70 |
| 2023 March | 18 | 2 | 20 |
| 2023 February | 62 | 29 | 91 |
| 2023 January | 42 | 30 | 72 |
| 2022 December | 99 | 35 | 134 |
| 2022 November | 92 | 31 | 123 |
| 2022 October | 72 | 61 | 133 |
| 2022 September | 35 | 34 | 69 |
| 2022 August | 34 | 42 | 76 |
| 2022 July | 34 | 36 | 70 |
| 2022 June | 52 | 47 | 99 |
| 2022 May | 75 | 36 | 111 |
| 2022 April | 78 | 35 | 113 |
| 2022 March | 76 | 56 | 132 |
| 2022 February | 85 | 35 | 120 |
| 2022 January | 87 | 36 | 123 |
| 2021 December | 76 | 56 | 132 |
| 2021 November | 58 | 41 | 99 |
| 2021 October | 102 | 53 | 155 |
| 2021 September | 74 | 45 | 119 |
| 2021 August | 55 | 39 | 94 |
| 2021 July | 55 | 58 | 113 |
| 2021 June | 70 | 63 | 133 |
| 2021 May | 63 | 67 | 130 |
| 2021 April | 156 | 73 | 229 |
| 2021 March | 80 | 22 | 102 |
| 2021 February | 57 | 31 | 88 |
| 2021 January | 96 | 28 | 124 |
| 2020 December | 49 | 37 | 86 |
| 2020 November | 34 | 11 | 45 |
| 2020 October | 72 | 21 | 93 |
| 2020 September | 39 | 16 | 55 |
| 2020 August | 51 | 14 | 65 |
| 2020 July | 72 | 25 | 97 |
| 2020 June | 65 | 10 | 75 |
| 2020 May | 55 | 19 | 74 |
| 2020 April | 41 | 23 | 64 |
| 2020 March | 37 | 15 | 52 |
| 2020 February | 34 | 22 | 56 |
| 2020 January | 39 | 20 | 59 |
| 2019 December | 49 | 23 | 72 |
| 2019 November | 35 | 27 | 62 |
| 2019 October | 40 | 20 | 60 |
| 2019 September | 25 | 15 | 40 |
| 2019 August | 27 | 21 | 48 |
| 2019 July | 32 | 19 | 51 |
| 2019 June | 30 | 19 | 49 |
| 2019 May | 52 | 27 | 79 |
| 2019 April | 54 | 63 | 117 |
| 2019 March | 36 | 19 | 55 |
| 2019 February | 27 | 19 | 46 |
| 2019 January | 60 | 16 | 76 |
| 2018 December | 39 | 17 | 56 |
| 2018 November | 74 | 29 | 103 |
| 2018 October | 105 | 33 | 138 |
| 2018 September | 45 | 10 | 55 |
| 2018 May | 19 | 1 | 20 |
| 2018 April | 31 | 12 | 43 |
| 2018 March | 23 | 7 | 30 |
| 2018 February | 31 | 6 | 37 |
| 2018 January | 19 | 8 | 27 |
| 2017 December | 35 | 8 | 43 |
| 2017 November | 32 | 9 | 41 |
| 2017 October | 31 | 13 | 44 |
| 2017 September | 37 | 7 | 44 |
| 2017 August | 19 | 15 | 34 |
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