Impact of COVID-19 in Patients With Severe Alpha-1 Antitrypsin Deficiency: The IMCA1 Study of the EARCO Clinical Research Collaboration

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As baseline FVC declines, the difference between the relative and absolute percentage value increases. The relative method is more sensitive for detecting decline and this parameter is more marked in patients with reduced baseline FVC values. Absolute FVCdecline=baseline FVC−final FVC; relative decline: (baseline FVC−final FVC)/baseline FVC; FVC: forced vital capacity; L: liters; Δ: Delta of change between a relative and absolute FVC decline of 5%." ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Horacio Matías Castro, Joaquin Maritano Furcada, Juan Ignacio Enghelmayer" "autores" => array:3 [ 0 => array:2 [ "nombre" => "Horacio Matías" "apellidos" => "Castro" ] 1 => array:2 [ "nombre" => "Joaquin" "apellidos" => "Maritano Furcada" ] 2 => array:2 [ "nombre" => "Juan Ignacio" "apellidos" => "Enghelmayer" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0300289622004896?idApp=UINPBA00003Z" "url" => "/03002896/0000005800000012/v2_202305072241/S0300289622004896/v2_202305072241/en/main.assets" ] "itemAnterior" => array:18 [ "pii" => "S0300289622004823" "issn" => "03002896" "doi" => "10.1016/j.arbres.2022.06.005" "estado" => "S300" "fechaPublicacion" => "2022-12-01" "aid" => "3139" "copyright" => "SEPAR" "documento" => "simple-article" "crossmark" => 1 "subdocumento" => "crp" "cita" => "Arch Bronconeumol. 2022;58:837-9" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:1 [ "total" => 0 ] "en" => array:10 [ "idiomaDefecto" => true "cabecera" => "Scientific Letter" "titulo" => "Increased Blood Eosinophil Count Is Related to Less Daily Physical Activity in Patients With Chronic Obstructive Pulmonary Disease" "tienePdf" => "en" "tieneTextoCompleto" => "en" "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "837" "paginaFinal" => "839" ] ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0005" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1831 "Ancho" => 3175 "Tamanyo" => 228964 ] ] "descripcion" => array:1 [ "en" => "(A) Distribution of daily physical activity patterns between COPD patients with or without increased blood eosinophils count (BEC); (B) Relationship between the number (upper panel) or percentage (lower panel) of the BEC and physical activity level (PAL) of patients with COPD. Abbreviation: r, Pearson correlation coefficient." ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Raúl Galera, Cristina Mergelina, Raquel Casitas, Elisabet Martínez-Cerón, Francisco García Río" "autores" => array:5 [ 0 => array:2 [ "nombre" => "Raúl" "apellidos" => "Galera" ] 1 => array:2 [ "nombre" => "Cristina" "apellidos" => "Mergelina" ] 2 => array:2 [ "nombre" => "Raquel" "apellidos" => "Casitas" ] 3 => array:2 [ "nombre" => "Elisabet" "apellidos" => "Martínez-Cerón" ] 4 => array:2 [ "nombre" => "Francisco" "apellidos" => "García Río" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0300289622004823?idApp=UINPBA00003Z" "url" => "/03002896/0000005800000012/v2_202305072241/S0300289622004823/v2_202305072241/en/main.assets" ] "en" => array:14 [ "idiomaDefecto" => true "cabecera" => "Scientific Letter" "titulo" => "Impact of COVID-19 in Patients With Severe Alpha-1 Antitrypsin Deficiency: The IMCA1 Study of the EARCO Clinical Research Collaboration" "tieneTextoCompleto" => true "saludo" => "To the Director," "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "840" "paginaFinal" => "842" ] ] "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "David G. Parr, Joanna Chorostowska-Wynimko, Angelo Corsico, Cristina Esquinas, Gerard N. McElvaney, Annelot D. Sark, Maria Sucena, Hanan Tanash, Alice M. Turner, Marc Miravitlles" "autores" => array:10 [ 0 => array:4 [ "nombre" => "David G." "apellidos" => "Parr" "email" => array:1 [ 0 => "david.parr@uhcw.nhs.uk" ] "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "*" "identificador" => "cor0005" ] ] ] 1 => array:3 [ "nombre" => "Joanna" "apellidos" => "Chorostowska-Wynimko" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "b" "identificador" => "aff0010" ] ] ] 2 => array:3 [ "nombre" => "Angelo" "apellidos" => "Corsico" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "c" "identificador" => "aff0015" ] ] ] 3 => array:3 [ "nombre" => "Cristina" "apellidos" => "Esquinas" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "d" "identificador" => "aff0020" ] ] ] 4 => array:3 [ "nombre" => "Gerard N." "apellidos" => "McElvaney" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "e" "identificador" => "aff0025" ] ] ] 5 => array:3 [ "nombre" => "Annelot D." "apellidos" => "Sark" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "f" "identificador" => "aff0030" ] ] ] 6 => array:3 [ "nombre" => "Maria" "apellidos" => "Sucena" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "g" "identificador" => "aff0035" ] ] ] 7 => array:3 [ "nombre" => "Hanan" "apellidos" => "Tanash" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "h" "identificador" => "aff0040" ] ] ] 8 => array:3 [ "nombre" => "Alice M." "apellidos" => "Turner" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "i" "identificador" => "aff0045" ] ] ] 9 => array:3 [ "nombre" => "Marc" "apellidos" => "Miravitlles" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "d" "identificador" => "aff0020" ] ] ] ] "afiliaciones" => array:9 [ 0 => array:3 [ "entidad" => "Department of Respiratory Medicine, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UK" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Department of Genetics and Clinical Immunology, National Institute of Tuberculosis and Lung Disease, Warsaw, Poland" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Respiratory Diseases Division, IRCCS Policlinico San Matteo Foundation and University of Pavia, Italy" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Pneumology Department, Hospital Universitari Vall d’Hebron/Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Barcelona Hospital Campus, CIBER de Enfermedades Respiratorias (CIBERES), Barcelona, Spain" "etiqueta" => "d" "identificador" => "aff0020" ] 4 => array:3 [ "entidad" => "Irish Centre for Genetic Lung Disease, Royal College of Surgeons in Ireland, Beaumont Hospital, Dublin, Ireland" "etiqueta" => "e" "identificador" => "aff0025" ] 5 => array:3 [ "entidad" => "Department of Pulmonology, Leiden University Medical Center, Leiden, The Netherlands" "etiqueta" => "f" "identificador" => "aff0030" ] 6 => array:3 [ "entidad" => "Pulmonology Department, Centro Hospitalar Universitário do Porto, Porto, Portugal" "etiqueta" => "g" "identificador" => "aff0035" ] 7 => array:3 [ "entidad" => "Department of Respiratory Medicine and Allergology, Skåne University Hospital, Lund University, Sweden" "etiqueta" => "h" "identificador" => "aff0040" ] 8 => array:3 [ "entidad" => "Institute for Applied Health Research, University of Birmingham, Birmingham, UK" "etiqueta" => "i" "identificador" => "aff0045" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "textoCompleto" => "As we enter the third year of the pandemic, the impact of COVID-19 on patients with pre-existing specific respiratory diseases remains poorly characterised, creating uncertainties for risk management and posing a challenge to delivery of safe, effective, evidence-based care.Patients with severe alpha-1 antitrypsin deficiency (AATD) have increased risk of developing chronic, progressive lung disease, particularly pan-lobular emphysema.<a class="elsevierStyleCrossRef" href="#bib0045">1</a> Pathogenesis is considered one of imbalance between the destructive proteolytic burden resulting from inhaled, pro-inflammatory factors and impaired defences arising from deficiency of alpha-1 antitrypsin (AAT). Increased risk from COVID-19 may be consequent to reduced pulmonary functional reserve and from overwhelmed, impaired anti-inflammatory defences by the cytokine/inflammatory storm associated with COVID-19.<a class="elsevierStyleCrossRefs" href="#bib0050">2,3</a> The likelihood of progressive respiratory failure and irreversible lung damage would be expected to be increased. AAT may also have a beneficial role in modifying the severity of COVID-19 through several different mechanisms.<a class="elsevierStyleCrossRef" href="#bib0060">4</a>The EARCO ERS Clinical Research Collaboration<a class="elsevierStyleCrossRef" href="#bib0065">5</a> sought, at the outset of the pandemic, to estimate the risk posed by COVID-19 to patients with severe AATD. Anonymised data on all known cases of COVID-19 in patients with severe AATD across participating countries was collated into a database to identify and ordinate risk factors for an adverse outcome. Patients age>18 years with severely reduced serum level of AAT due to two inherited pathological alleles in the SERPINA1 gene (PiZZ, PiSZ or rare variants with an equivalent serum AAT level (viz. <60mg/dl i.e. <11μmol/L)<a class="elsevierStyleCrossRef" href="#bib0070">6</a> were included. Diagnosis of COVID-19 was based on a pathognomonic clinical presentation (± a positive confirmatory polymerase chain reaction test). Subjects were identified by EARCO reference centres through direct contact with patients attending the centre or patient contact prompted by information disseminated via national patient groups to their members. Details of patient baseline characteristics and outcome, including hospitalisation, treatment, mortality and spirometry (from historical records and post-acute COVID-19 measurements) were collected. Patients that were not admitted to hospital were assessed ‘virtually’ via phone contact and further data was obtained from hospital records. Ethics approval was obtained from HRA and Health and Care Research Wales (IRAS ID 285484). As a retrospective collection of fully anonymised clinical data from medical records, consent was not considered to be required.Patient characteristics were compared according to genotype and outcome. Normality of distributions was assessed using the Kolmogorov–Smirnov test. For quantitative variables, the Student's t-test (Mann–Whitney U-test if normality was not assumed) or ANOVA tests (in the case of variables with more than 2 categories) were carried out. The Chi-squared test (Fisher test for frequencies<5) was used for comparison of categorical variables. A backward stepwise logistic regression analysis was performed to identify clinical variables related to poor outcome, defined as hospitalisation or death. p-Values<0.05 were considered statistically significant.We identified 105 patients consecutively (65 male, 61%) across 21 centres in 10 countries with a mean (SD) AAT level of 32.8 (19.6) mg/dL, mean (SD) age of 51.3 (12.2) years, baseline FEV1%predicted (measured in 93 patients): 63.4 (31.0) %, (n=93), and PiZZ:PiSZ (or equivalent severity of deficiency) genotype distribution, 81:24. CT-evidenced emphysema was present in 66 (63%) patients and bronchiectasis in 5 (4.7%). Fourteen patients (14%) were receiving regular augmentation therapy. Non-respiratory comorbidities were present in 36 (34%) patients (19 [18%] hypertension, 4 [3%] diabetes, 12 [11%] liver, 2 [2%] renal and 3 [3%] cardiovascular disease). COVID-19 presentation (93 [88%] patients with positive PCR) included worsening breathlessness in 72 (68%) patients, cough in 75 (71%), anosmia and/or dysgeusia in 39 (37%), headache in 51 (49%), myalgia in 55 (52%) and gastrointestinal symptoms in 29 (28%). Hospitalisation occurred in 32 (31%) patients (mean duration, 12.9 [9.1] days), with intensive care admission required in 5 (4.8%) (mean duration, 5.6 [2.7] days), high flow oxygen in 21 (21%) and non-invasive ventilation/continuous positive airway pressure (NIV/CPAP) in 9 (9%). Poor outcome was more frequent in the PiZZ (29 patients, 35.8%) compared to the PiSZ (4 patients, 16.6%) group, although not significant (p=0.076). Four (3.8%) deaths occurred, all of them in PiZZ patients. Paired analysis of decline in FEV1%predicted showed an overall mean (SD) change of −1.8 (5.4) % (n=42, p=0.01) and changes of +1.3 (5.4) % (n=10, p=0.37) and −2.8 (4.7) %, (n=32, p=0.001) in the PiSZ and PiZZ groups, respectively. There was a median (IQR) interval of 167 (63–311) days between the time of ‘pre-COVID-19’ spirometry and onset of COVID-19 symptoms, 120 (84–178) days between symptom onset and ‘post-COVID-19’ spirometry and a median duration of acute illness of 16 (12–39) days (n=37). Regression analyses are shown in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>.<elsevierMultimedia ident="tbl0005"></elsevierMultimedia>In the majority of our patients, COVID-19 was not associated with a poor outcome. Survival with recovery usually occurred, even with pre-existing severe lung disease or following hospitalisation. Non-respiratory comorbidities were more strongly associated with poor outcome than genotype, baseline FEV1 or oxygen saturation, comparable to findings in usual COPD.<a class="elsevierStyleCrossRef" href="#bib0075">7</a> Poor outcome was less likely with symptoms of anosmia or dysgeusia. Although outcome was comparable between PiZZ and PiSZ groups, mortality occurred only in PiZZ patients who also demonstrated reduction in FEV1% predicted, suggestive of accelerated disease progression. Consequently, patients with severe deficiency are advised to still employ effective avoidance strategies.Notwithstanding the unique value of our data, we recognise the potential limitations to our study. Restricted patient access due to shielding may have introduced recruitment bias, however, this is more likely to have selected the most unwell patients and our mortality rate is unlikely to be underestimated. We did not perform an age-matched comparison with the ‘general population’. However, non-respiratory comorbidities, which are the same comorbidities that influence outcomes in the ‘general population’, were more strongly associated with a poor outcome than the level of AATD, FEV1 impairment and oxygen saturation. The evolving nature of the pandemic has introduced confounders since study commencement: vaccines and specific therapies have altered outcomes, but were only widely available following study completion. Our data therefore provides insight into the natural course of the original variant of COVID-19 in AATD patients, against which future comparisons can be made, and which provides a clinical context to indirect evidence of AATD as a risk factor.<a class="elsevierStyleCrossRef" href="#bib0080">8</a>AATD patients remain concerned about contracting COVID-19 and continue to lead isolated lifestyles with consequences to health. Our data provides an estimate of the relative risk arising from AATD which may help guide clinicians and patients, and enable future comparisons to be made.DisclosuresData from a preliminary analysis of the initial participants included in this cohort were presented at the European Respiratory Society Annual Congress 2021 as an e-poster presentation. The poster's abstract was published as a “Late breaking abstract” in the European Respiratory Journal 2021; 58: Suppl. 65, PA2365. <a href="https://erj.ersjournals.com/content/58/suppl_65/PA2365">https://erj.ersjournals.com/content/58/suppl_65/PA2365</a>.Conflicts of interestDavid Parr has received consulting fees from Mereo Biopharma, CSL Behring and Grifols, and speaker fees from CSL Behring and Grifols. Joanna Chorostowska-Wynimko has received research grants, speaker and consulting fees from Grifols, CSL Behring, CelonPharma, Pfizer, AstraZeneca, Boehringer-Ingelheim, speaker and consulting fees from Mereo Biopharma, MSD, BMS, GSK, Novartis, Roche, Chiesi, Amgen, Takeda. Angelo Corsico has nothing to disclose. Cristina Esquinas has received speaker fees from CSL Behring. Gerard N. McElvaney has received research funding from Grifols, Chiesi and PhPharma, consulting fees from Vertex, Illuma bioscience, Inhibrx and Intelia, and speakers fees from CSl Behring. Annelot D. Sark and Hanan Tanash have nothing to disclose. Maria Sucena has received speaker fees from Bial, Boehringer Ingelheim, CSL Behring and Grifols and consulting fees from Bial and CSL Behring. Alice M Turner has received research funding from CSL Behring and Vertex, consulting fees from Takeda and Inhibrx, and speaker fees from CSL Behring. Further research funding from Grifols is being contracted. Marc Miravitlles has received speaker fees from AstraZeneca, Boehringer Ingelheim, Chiesi, Cipla, Menarini, Rovi, Bial, Sandoz, Zambon, CSL Behring, Grifols and Novartis, consulting fees from AstraZeneca, Atriva Therapeutics, Boehringer Ingelheim, Chiesi, GlaxoSmithKline, Bial, Gebro Pharma, CSL Behring, Laboratorios Esteve, Ferrer, Mereo Biopharma, Verona Pharma, Spin Therapeutics, ONO Pharma, pH Pharma, Palobiofarma SL, Takeda, Novartis, Sanofi and Grifols and research grants from Grifols.FundingThis study was supported by the European Respiratory Society EARCO Clinical Research Collaboration." "textoCompletoSecciones" => array:1 [ "secciones" => array:5 [ 0 => array:2 [ "identificador" => "sec0005" "titulo" => "Disclosures" ] 1 => array:2 [ "identificador" => "sec0010" "titulo" => "Conflicts of interest" ] 2 => array:2 [ "identificador" => "sec0015" "titulo" => "Funding" ] 3 => array:2 [ "identificador" => "xack665600" "titulo" => "Acknowledgments" ] 4 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "multimedia" => array:1 [ 0 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:3 [ "leyenda" => "Data for estimated odds ratio (OR) and 95% confidence interval (95% CIs) of the explanatory variables for poor outcome. Factors showing an association in the univariate analyses (p<0.20) were incorporated in the multivariable model. Final variable selection was performed using backward stepwise selection method (pin<0.05, pout>0.10). Single collinearity was evaluated using Pearson correlation (and multicollinearity with variance inflation factor)." "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " colspan="3" align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Univariate</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " colspan="3" align="center" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Multivariable<a class="elsevierStyleCrossRef" href="#tblfn0005">a</a></th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Variable<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">OR \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">95% CI \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">p-Value \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">OR \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">95% CI \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">p-Value \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Male sex \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.02 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.82–4.94 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.125 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Genotype ZZ vs SZ \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.79 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.87–8.95 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.085 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">IV AAT augmentation \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.76 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.22–2.61 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.669 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Emphysema on CT<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.23 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.47–12.22 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.008 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Comorbidities \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.96 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.25–7.01 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.013 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.19 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.62–23.69 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.008 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Hypertension<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.50 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.28–9.57 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.015 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Cough \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.10 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.44–2.75 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.842 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Sputum \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.77 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.77–4.07 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.179 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Worsening breathlessness \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7.14 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.99–25.59 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.003 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8.85 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.67–46.81 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.010 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Anosmia<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.20 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.07–0.54 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.002 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Dysgeusia \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.14 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.04–0.43 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.04 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.01–0.19 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Age (year) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.05 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.01–1.08 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.019 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">BMI (kg/m2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.99 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.91–1.07 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.721 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Temp (°C) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.14 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.77–1.69 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.514 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Sats (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.89 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.83–0.97 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.004 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.88 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.79–0.99 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.028 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Fev1%pred \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.97 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.96–0.99 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.97 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.95–1.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.017 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab3167157.png" ] ] ] "notaPie" => array:3 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "a" "nota" => "Hosmer–Lemeshow goodness-of-fit test, p=0.65. Area under the ROC curve (AUC)=0.90 (95% CI 0.85–0.96)." ] 1 => array:3 [ "identificador" => "tblfn0010" "etiqueta" => "b" "nota" => "Multiple imputation method used for missing data." ] 2 => array:3 [ "identificador" => "tblfn0015" "etiqueta" => "c" "nota" => "Excluded from multivariable model due highly correlation with another variable (r>|±0.5|)." ] ] ] "descripcion" => array:1 [ "en" => "Multivariable logistic regression analysis for variables independently associated with poor outcome (N=105)." ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0015" "bibliografiaReferencia" => array:8 [ 0 => array:3 [ "identificador" => "bib0045" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "European Respiratory Society Statement: Diagnosis and treatment of pulmonary disease in alpha-1 antitrypsin deficiency" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "M. 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Garcia" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.mehy.2020.110394" "Revista" => array:5 [ "tituloSerie" => "Med Hypotheses" "fecha" => "2021" "volumen" => "146" "paginaInicial" => "110394" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/33239231" "web" => "Medline" ] ] ] ] ] ] ] ] 4 => array:3 [ "identificador" => "bib0065" "etiqueta" => "5" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "The European Alpha-1 Research Collaboration (EARCO): a new ERS Clinical Research Collaboration to promote research in alpha-1 antitrypsin deficiency" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "M. Miravitlles" 1 => "J. Chorostowska-Wynimko" 2 => "I. Ferrarotti" 3 => "N. McElvaney" 4 => "K. O’Hara" 5 => "J. 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Chorostowska-Wynimko" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1183/23120541.00181-2019" "Revista" => array:3 [ "tituloSerie" => "ERJ Open Res" "fecha" => "2020" "volumen" => "6" ] ] ] ] ] ] 6 => array:3 [ "identificador" => "bib0075" "etiqueta" => "7" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "W.J. Guan" 1 => "W.H. Liang" 2 => "Y. Zhao" 3 => "H. Liang" 4 => "Z. Chen" 5 => "Y. Li" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1183/13993003.00547-2020" "Revista" => array:5 [ "tituloSerie" => "Eur Respir J" "fecha" => "2020" "volumen" => "55" "paginaInicial" => "2000547" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/32217650" "web" => "Medline" ] ] ] ] ] ] ] ] 7 => array:3 [ "identificador" => "bib0080" "etiqueta" => "8" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Geographical overlap between alpha-1 antitrypsin deficiency and COVID-19 infection in italy: casual or causal?" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:2 [ 0 => "A. Vianello" 1 => "F. Braccioni" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:5 [ "tituloSerie" => "Arch Bronconeumol (Engl Ed)" "fecha" => "2020" "volumen" => "56" "paginaInicial" => "609" "paginaFinal" => "610" ] ] ] ] ] ] ] ] ] ] "agradecimientos" => array:1 [ 0 => array:4 [ "identificador" => "xack665600" "titulo" => "Acknowledgments" "texto" => "Members of the IMCA1 Study Group: Robert Bals, Miriam Barrecheguren, Christian Clarenbach, Ilaria Ferrarotti, Lourdes Lazaro, José Luis Lopez-Campos, Farah Mobeen, Jan Stolk and Eva Taberno.The authors want to thank the participants in the study and the national patients support groups that facilitated awareness of the study through their members." 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Scientific Letter

Impact of COVID-19 in Patients With Severe Alpha-1 Antitrypsin Deficiency: The IMCA1 Study of the EARCO Clinical Research Collaboration

David G. Parra,

Corresponding author

david.parr@uhcw.nhs.uk

Corresponding author.

, Joanna Chorostowska-Wynimkob, Angelo Corsicoc, Cristina Esquinasd, Gerard N. McElvaneye, Annelot D. Sarkf, Maria Sucenag, Hanan Tanashh, Alice M. Turneri, Marc Miravitllesd

a Department of Respiratory Medicine, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UK

b Department of Genetics and Clinical Immunology, National Institute of Tuberculosis and Lung Disease, Warsaw, Poland

c Respiratory Diseases Division, IRCCS Policlinico San Matteo Foundation and University of Pavia, Italy

d Pneumology Department, Hospital Universitari Vall d’Hebron/Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Barcelona Hospital Campus, CIBER de Enfermedades Respiratorias (CIBERES), Barcelona, Spain

e Irish Centre for Genetic Lung Disease, Royal College of Surgeons in Ireland, Beaumont Hospital, Dublin, Ireland

f Department of Pulmonology, Leiden University Medical Center, Leiden, The Netherlands

g Pulmonology Department, Centro Hospitalar Universitário do Porto, Porto, Portugal

h Department of Respiratory Medicine and Allergology, Skåne University Hospital, Lund University, Sweden

i Institute for Applied Health Research, University of Birmingham, Birmingham, UK

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    "textoCompleto" => "<span class="elsevierStyleSections"><p id="par0005" class="elsevierStylePara elsevierViewall">As we enter the third year of the pandemic&#44; the impact of COVID-19 on patients with pre-existing specific respiratory diseases remains poorly characterised&#44; creating uncertainties for risk management and posing a challenge to delivery of safe&#44; effective&#44; evidence-based care&#46;</p><p id="par0010" class="elsevierStylePara elsevierViewall">Patients with severe alpha-1 antitrypsin deficiency &#40;AATD&#41; have increased risk of developing chronic&#44; progressive lung disease&#44; particularly pan-lobular emphysema&#46;<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">1</span></a> Pathogenesis is considered one of imbalance between the destructive proteolytic burden resulting from inhaled&#44; pro-inflammatory factors and impaired defences arising from deficiency of alpha-1 antitrypsin &#40;AAT&#41;&#46; Increased risk from COVID-19 may be consequent to reduced pulmonary functional reserve and from overwhelmed&#44; impaired anti-inflammatory defences by the cytokine&#47;inflammatory storm associated with COVID-19&#46;<a class="elsevierStyleCrossRefs" href="#bib0050"><span class="elsevierStyleSup">2&#44;3</span></a> The likelihood of progressive respiratory failure and irreversible lung damage would be expected to be increased&#46; AAT may also have a beneficial role in modifying the severity of COVID-19 through several different mechanisms&#46;<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">4</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">The EARCO ERS Clinical Research Collaboration<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">5</span></a> sought&#44; at the outset of the pandemic&#44; to estimate the risk posed by COVID-19 to patients with severe AATD&#46; Anonymised data on all known cases of COVID-19 in patients with severe AATD across participating countries was collated into a database to identify and ordinate risk factors for an adverse outcome&#46; Patients age<span class="elsevierStyleHsp" style=""></span>&#62;<span class="elsevierStyleHsp" style=""></span>18 years with severely reduced serum level of AAT due to two inherited pathological alleles in the SERPINA1 gene &#40;PiZZ&#44; PiSZ or rare variants with an equivalent serum AAT level &#40;viz&#46; &#60;60<span class="elsevierStyleHsp" style=""></span>mg&#47;dl i&#46;e&#46; &#60;11<span class="elsevierStyleHsp" style=""></span>&#956;mol&#47;L&#41;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">6</span></a> were included&#46; Diagnosis of COVID-19 was based on a pathognomonic clinical presentation &#40;&#177; a positive confirmatory polymerase chain reaction test&#41;&#46; Subjects were identified by EARCO reference centres through direct contact with patients attending the centre or patient contact prompted by information disseminated via national patient groups to their members&#46; Details of patient baseline characteristics and outcome&#44; including hospitalisation&#44; treatment&#44; mortality and spirometry &#40;from historical records and post-acute COVID-19 measurements&#41; were collected&#46; Patients that were not admitted to hospital were assessed &#8216;virtually&#8217; via phone contact and further data was obtained from hospital records&#46; Ethics approval was obtained from HRA and Health and Care Research Wales &#40;IRAS ID 285484&#41;&#46; As a retrospective collection of fully anonymised clinical data from medical records&#44; consent was not considered to be required&#46;</p><p id="par0020" class="elsevierStylePara elsevierViewall">Patient characteristics were compared according to genotype and outcome&#46; Normality of distributions was assessed using the Kolmogorov&#8211;Smirnov test&#46; For quantitative variables&#44; the Student&#39;s <span class="elsevierStyleItalic">t</span>-test &#40;Mann&#8211;Whitney <span class="elsevierStyleItalic">U</span>-test if normality was not assumed&#41; or ANOVA tests &#40;in the case of variables with more than 2 categories&#41; were carried out&#46; The Chi-squared test &#40;Fisher test for frequencies<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>5&#41; was used for comparison of categorical variables&#46; A backward stepwise logistic regression analysis was performed to identify clinical variables related to poor outcome&#44; defined as hospitalisation or death&#46; <span class="elsevierStyleItalic">p</span>-Values<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;05 were considered statistically significant&#46;</p><p id="par0025" class="elsevierStylePara elsevierViewall">We identified 105 patients consecutively &#40;65 male&#44; 61&#37;&#41; across 21 centres in 10 countries with a mean &#40;SD&#41; AAT level of 32&#46;8 &#40;19&#46;6&#41; mg&#47;dL&#44; mean &#40;SD&#41; age of 51&#46;3 &#40;12&#46;2&#41; years&#44; baseline FEV<span class="elsevierStyleInf">1</span>&#37;predicted &#40;measured in 93 patients&#41;&#58; 63&#46;4 &#40;31&#46;0&#41; &#37;&#44; &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>93&#41;&#44; and PiZZ&#58;PiSZ &#40;or equivalent severity of deficiency&#41; genotype distribution&#44; 81&#58;24&#46; CT-evidenced emphysema was present in 66 &#40;63&#37;&#41; patients and bronchiectasis in 5 &#40;4&#46;7&#37;&#41;&#46; Fourteen patients &#40;14&#37;&#41; were receiving regular augmentation therapy&#46; Non-respiratory comorbidities were present in 36 &#40;34&#37;&#41; patients &#40;19 &#91;18&#37;&#93; hypertension&#44; 4 &#91;3&#37;&#93; diabetes&#44; 12 &#91;11&#37;&#93; liver&#44; 2 &#91;2&#37;&#93; renal and 3 &#91;3&#37;&#93; cardiovascular disease&#41;&#46; COVID-19 presentation &#40;93 &#91;88&#37;&#93; patients with positive PCR&#41; included worsening breathlessness in 72 &#40;68&#37;&#41; patients&#44; cough in 75 &#40;71&#37;&#41;&#44; anosmia and&#47;or dysgeusia in 39 &#40;37&#37;&#41;&#44; headache in 51 &#40;49&#37;&#41;&#44; myalgia in 55 &#40;52&#37;&#41; and gastrointestinal symptoms in 29 &#40;28&#37;&#41;&#46; Hospitalisation occurred in 32 &#40;31&#37;&#41; patients &#40;mean duration&#44; 12&#46;9 &#91;9&#46;1&#93; days&#41;&#44; with intensive care admission required in 5 &#40;4&#46;8&#37;&#41; &#40;mean duration&#44; 5&#46;6 &#91;2&#46;7&#93; days&#41;&#44; high flow oxygen in 21 &#40;21&#37;&#41; and non-invasive ventilation&#47;continuous positive airway pressure &#40;NIV&#47;CPAP&#41; in 9 &#40;9&#37;&#41;&#46; Poor outcome was more frequent in the PiZZ &#40;29 patients&#44; 35&#46;8&#37;&#41; compared to the PiSZ &#40;4 patients&#44; 16&#46;6&#37;&#41; group&#44; although not significant &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;076&#41;&#46; Four &#40;3&#46;8&#37;&#41; deaths occurred&#44; all of them in PiZZ patients&#46; Paired analysis of decline in FEV<span class="elsevierStyleInf">1</span>&#37;predicted showed an overall mean &#40;SD&#41; change of &#8722;1&#46;8 &#40;5&#46;4&#41; &#37; &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>42&#44; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;01&#41; and changes of &#43;1&#46;3 &#40;5&#46;4&#41; &#37; &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>10&#44; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;37&#41; and &#8722;2&#46;8 &#40;4&#46;7&#41; &#37;&#44; &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>32&#44; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;001&#41; in the PiSZ and PiZZ groups&#44; respectively&#46; There was a median &#40;IQR&#41; interval of 167 &#40;63&#8211;311&#41; days between the time of &#8216;pre-COVID-19&#8217; spirometry and onset of COVID-19 symptoms&#44; 120 &#40;84&#8211;178&#41; days between symptom onset and &#8216;post-COVID-19&#8217; spirometry and a median duration of acute illness of 16 &#40;12&#8211;39&#41; days &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>37&#41;&#46; Regression analyses are shown in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0030" class="elsevierStylePara elsevierViewall">In the majority of our patients&#44; COVID-19 was not associated with a poor outcome&#46; Survival with recovery usually occurred&#44; even with pre-existing severe lung disease or following hospitalisation&#46; Non-respiratory comorbidities were more strongly associated with poor outcome than genotype&#44; baseline FEV<span class="elsevierStyleInf">1</span> or oxygen saturation&#44; comparable to findings in usual COPD&#46;<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">7</span></a> Poor outcome was less likely with symptoms of anosmia or dysgeusia&#46; Although outcome was comparable between PiZZ and PiSZ groups&#44; mortality occurred only in PiZZ patients who also demonstrated reduction in FEV<span class="elsevierStyleInf">1</span>&#37; predicted&#44; suggestive of accelerated disease progression&#46; Consequently&#44; patients with severe deficiency are advised to still employ effective avoidance strategies&#46;</p><p id="par0035" class="elsevierStylePara elsevierViewall">Notwithstanding the unique value of our data&#44; we recognise the potential limitations to our study&#46; Restricted patient access due to shielding may have introduced recruitment bias&#44; however&#44; this is more likely to have selected the most unwell patients and our mortality rate is unlikely to be underestimated&#46; We did not perform an age-matched comparison with the &#8216;general population&#8217;&#46; However&#44; non-respiratory comorbidities&#44; which are the same comorbidities that influence outcomes in the &#8216;general population&#8217;&#44; were more strongly associated with a poor outcome than the level of AATD&#44; FEV<span class="elsevierStyleInf">1</span> impairment and oxygen saturation&#46; The evolving nature of the pandemic has introduced confounders since study commencement&#58; vaccines and specific therapies have altered outcomes&#44; but were only widely available following study completion&#46; Our data therefore provides insight into the natural course of the original variant of COVID-19 in AATD patients&#44; against which future comparisons can be made&#44; and which provides a clinical context to indirect evidence of AATD as a risk factor&#46;<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">8</span></a></p><p id="par0040" class="elsevierStylePara elsevierViewall">AATD patients remain concerned about contracting COVID-19 and continue to lead isolated lifestyles with consequences to health&#46; Our data provides an estimate of the relative risk arising from AATD which may help guide clinicians and patients&#44; and enable future comparisons to be made&#46;</p><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0005">Disclosures</span><p id="par0045" class="elsevierStylePara elsevierViewall">Data from a preliminary analysis of the initial participants included in this cohort were presented at the European Respiratory Society Annual Congress 2021 as an e-poster presentation&#46; The poster&#39;s abstract was published as a &#8220;Late breaking abstract&#8221; in the European Respiratory Journal 2021&#59; 58&#58; Suppl&#46; 65&#44; PA2365&#46; <a href="https://erj.ersjournals.com/content/58/suppl_65/PA2365">https&#58;&#47;&#47;erj&#46;ersjournals&#46;com&#47;content&#47;58&#47;suppl&#95;65&#47;PA2365</a>&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Conflicts of interest</span><p id="par0050" class="elsevierStylePara elsevierViewall">David Parr has received consulting fees from Mereo Biopharma&#44; CSL Behring and Grifols&#44; and speaker fees from CSL Behring and Grifols&#46; Joanna Chorostowska-Wynimko has received research grants&#44; speaker and consulting fees from Grifols&#44; CSL Behring&#44; CelonPharma&#44; Pfizer&#44; AstraZeneca&#44; Boehringer-Ingelheim&#44; speaker and consulting fees from Mereo Biopharma&#44; MSD&#44; BMS&#44; GSK&#44; Novartis&#44; Roche&#44; Chiesi&#44; Amgen&#44; Takeda&#46; Angelo Corsico has nothing to disclose&#46; Cristina Esquinas has received speaker fees from CSL Behring&#46; Gerard N&#46; McElvaney has received research funding from Grifols&#44; Chiesi and PhPharma&#44; consulting fees from Vertex&#44; Illuma bioscience&#44; Inhibrx and Intelia&#44; and speakers fees from CSl Behring&#46; Annelot D&#46; Sark and Hanan Tanash have nothing to disclose&#46; Maria Sucena has received speaker fees from Bial&#44; Boehringer Ingelheim&#44; CSL Behring and Grifols and consulting fees from Bial and CSL Behring&#46; Alice M Turner has received research funding from CSL Behring and Vertex&#44; consulting fees from Takeda and Inhibrx&#44; and speaker fees from CSL Behring&#46; Further research funding from Grifols is being contracted&#46; Marc Miravitlles has received speaker fees from AstraZeneca&#44; Boehringer Ingelheim&#44; Chiesi&#44; Cipla&#44; Menarini&#44; Rovi&#44; Bial&#44; Sandoz&#44; Zambon&#44; CSL Behring&#44; Grifols and Novartis&#44; consulting fees from AstraZeneca&#44; Atriva Therapeutics&#44; Boehringer Ingelheim&#44; Chiesi&#44; GlaxoSmithKline&#44; Bial&#44; Gebro Pharma&#44; CSL Behring&#44; Laboratorios Esteve&#44; Ferrer&#44; Mereo Biopharma&#44; Verona Pharma&#44; Spin Therapeutics&#44; ONO Pharma&#44; pH Pharma&#44; Palobiofarma SL&#44; Takeda&#44; Novartis&#44; Sanofi and Grifols and research grants from Grifols&#46;</p></span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Funding</span><p id="par0055" class="elsevierStylePara elsevierViewall">This study was supported by the <span class="elsevierStyleGrantSponsor" id="gs1">European Respiratory Society EARCO Clinical Research Collaboration</span>&#46;</p></span></span>"
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          "leyenda" => "<p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Data for estimated odds ratio &#40;OR&#41; and 95&#37; confidence interval &#40;95&#37; CIs&#41; of the explanatory variables for poor outcome&#46; Factors showing an association in the univariate analyses &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;20&#41; were incorporated in the multivariable model&#46; Final variable selection was performed using backward stepwise selection method &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleInf">in</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;05&#44; <span class="elsevierStyleItalic">p</span><span class="elsevierStyleInf">out</span><span class="elsevierStyleHsp" style=""></span>&#62;<span class="elsevierStyleHsp" style=""></span>0&#46;10&#41;&#46; Single collinearity was evaluated using Pearson correlation &#40;and multicollinearity with variance inflation factor&#41;&#46;</p>"
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                  \t\t\t\t\tvoid\n
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                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t" scope="col">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " colspan="3" align="center" valign="\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Univariate</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " colspan="3" align="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Multivariable<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a></th></tr><tr title="table-row"><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Variable<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">OR&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">95&#37; CI&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">p</span>-Value&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">OR&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">95&#37; CI&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">p</span>-Value&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
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                  \t\t\t\t">Male sex&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">2&#46;02&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">0&#46;82&#8211;4&#46;94&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">0&#46;125&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Genotype ZZ vs SZ&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">2&#46;79&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;87&#8211;8&#46;95&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">0&#46;085&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
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                  \t\t\t\t">IV AAT augmentation&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">0&#46;76&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">0&#46;22&#8211;2&#46;61&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">0&#46;669&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Emphysema on CT<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">4&#46;23&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">1&#46;47&#8211;12&#46;22&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">0&#46;008&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Comorbidities&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">2&#46;96&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">1&#46;25&#8211;7&#46;01&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">0&#46;013&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">6&#46;19&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">1&#46;62&#8211;23&#46;69&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">0&#46;008&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Hypertension<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">3&#46;50&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">1&#46;28&#8211;9&#46;57&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">0&#46;015&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Cough&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">1&#46;10&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">0&#46;44&#8211;2&#46;75&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;842&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Sputum&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">1&#46;77&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;77&#8211;4&#46;07&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;179&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Worsening breathlessness&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">7&#46;14&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">1&#46;99&#8211;25&#46;59&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;003&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">8&#46;85&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;67&#8211;46&#46;81&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;010&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Anosmia<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;20&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;07&#8211;0&#46;54&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;002&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Dysgeusia&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;14&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;04&#8211;0&#46;43&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;04&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">0&#46;01&#8211;0&#46;19&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Age &#40;year&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">1&#46;05&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">1&#46;01&#8211;1&#46;08&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">0&#46;019&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">BMI &#40;kg&#47;m<span class="elsevierStyleSup">2</span>&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;99&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;91&#8211;1&#46;07&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">0&#46;721&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Temp &#40;&#176;C&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;14&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">0&#46;77&#8211;1&#46;69&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;514&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                      "titulo" => "alpha1-Antitrypsin deficiency and the risk of COVID-19&#58; an urgent call to action"
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                      "titulo" => "The European Alpha-1 Research Collaboration &#40;EARCO&#41;&#58; a new ERS Clinical Research Collaboration to promote research in alpha-1 antitrypsin deficiency"
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                        0 => array:2 [
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                            4 => "K&#46; O&#8217;Hara"
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                      "titulo" => "Protocol for the EARCO Registry&#58; a pan-European observational study in patients with &#945;1-antitrypsin deficiency"
                      "autores" => array:1 [
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                          "etal" => true
                          "autores" => array:6 [
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                            2 => "M&#46; Barrecheguren"
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                            4 => "J&#46; Chlumsky"
                            5 => "J&#46; Chorostowska-Wynimko"
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                        0 => array:2 [
                          "etal" => true
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                            2 => "Y&#46; Zhao"
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                            4 => "Z&#46; Chen"
                            5 => "Y&#46; Li"
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                      "titulo" => "Geographical overlap between alpha-1 antitrypsin deficiency and COVID-19 infection in italy&#58; casual or causal&#63;"
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                        0 => array:2 [
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                          "autores" => array:2 [
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        "titulo" => "Acknowledgments"
        "texto" => "<p id="par0060" class="elsevierStylePara elsevierViewall">Members of the IMCA<span class="elsevierStyleInf">1</span> Study Group&#58; Robert Bals&#44; Miriam Barrecheguren&#44; Christian Clarenbach&#44; Ilaria Ferrarotti&#44; Lourdes Lazaro&#44; Jos&#233; Luis Lopez-Campos&#44; Farah Mobeen&#44; Jan Stolk and Eva Taberno&#46;</p><p id="par0065" class="elsevierStylePara elsevierViewall">The authors want to thank the participants in the study and the national patients support groups that facilitated awareness of the study through their members&#46;</p>"
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Article information

ISSN: 03002896
Original language: English

DOI:10.1016/j.arbres.2022.07.002

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