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    "textoCompleto" => "<span class="elsevierStyleSections"><p id="par0005" class="elsevierStylePara elsevierViewall">Chronic obstructive pulmonary disease &#40;COPD&#41; is one of the most common and debilitating disorders globally&#46; Acute exacerbations of COPD &#40;AECOPD&#41; are a defining feature of the disease and a major source of its burden&#46; Consequently&#44; the prevention of AECOPDs is a cornerstone of modern COPD management strategies&#46; In many guidelines&#44; important disease management decisions&#44; in particular the choice of pharmacotherapy&#44; is based on AECOPD history in the previous twelve months&#46;</p><p id="par0010" class="elsevierStylePara elsevierViewall">While intuitive and parsimonious&#44; this approach has several weaknesses that limit its application in clinical practice&#46; First&#44; this approach produces inherently unstable groups over time&#46; We recently demonstrated in 2 large cohorts that reliance on the patients&#8217; AECOPD history often leads to repeated reclassification of patients from year-to-year &#40;from frequent to non-frequent exacerbator phenotype or vice versa&#41; even when the underlying rate of exacerbation remains stable&#46;<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">1</span></a> For example&#44; a patient with a stable underlying AECOPD rate of 2 events per year has a 47&#37; chance of switching between frequent and non-frequent exacerbator in two consecutive years due to chance alone&#46; In this editorial&#44; we highlight a second fundamental weakness of this approach&#58; the &#8220;hiddenness&#8221; of treatment thresholds&#46;</p><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0005">Treatment threshold at the heart of rational decision making</span><p id="par0015" class="elsevierStylePara elsevierViewall">In their classic paper published more than four decades ago&#44; Pauker and Kassirer applied principles of decision theory to argue that the chance that a patient has a particular disease or is at a risk of a particular event is a crucial factor in the choice of treatment&#46;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">2</span></a> Because individuals at a high risk of poor outcomes are more likely to benefit from treatments than those at a low risk&#44; there exists a risk &#8216;treatment threshold&#8217; at which the benefits and harms of a given treatment are in perfect balance&#46; Above this treatment threshold&#44; the benefits of the treatment outweigh its harms&#46; Below this threshold&#44; the reduction in risk will not offset potential treatment harms&#46;</p><p id="par0020" class="elsevierStylePara elsevierViewall">This treatment threshold approach towards clinical decision making has been widely adopted in some specialties&#46; A leading example is primary prevention of cardiovascular diseases &#40;CVD&#41;&#46; For example&#44; the American guidelines on the primary prevention of CVD generally consider a treatment threshold for preventive pharmacotherapies &#40;e&#46;g&#46;&#44; statins&#41; to be between 7&#46;5&#37; and 20&#37; with regards to the 10-year risk for acute CVD events&#46;<a class="elsevierStyleCrossRefs" href="#bib0075"><span class="elsevierStyleSup">3&#44;4</span></a> At risks below 7&#46;5&#37;&#44; preventive therapies are not considered net beneficial&#44; whereas at predicted risks above 20&#37; they are considered highly beneficial&#46; Within the 7&#46;5&#8211;20&#37; range &#40;i&#46;e&#46; the &#8220;grey zone&#8221;&#41;&#44; the benefit&#8211;harm balance hinges on how the patient values reduction in CVD risk versus the risk of adverse events&#46; For some patients&#44; postponing preventative treatment may be the preferred approach&#59; while in those who are more willing to accept the risk of adverse events&#44; aggressive preventive pharmacotherapeutics may be warranted&#46; Thus&#44; a shared decision-making approach is recommended when the risk falls in the grey zone&#46; There are many examples of explicit treatment thresholds on predicted risks in other subspecialties such as fracture prevention in post-menopausal women&#44;<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">5</span></a> or screening for breast cancer&#46;<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">6</span></a></p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">The implicit treatment threshold in history-based COPD management</span><p id="par0025" class="elsevierStylePara elsevierViewall">Contemporary AECOPD prevention strategies are based on patients&#8217; AECOPD history over the previous year premised on the idea that <span class="elsevierStyleItalic">previous exacerbation history is the best predictor of future risk</span>&#46;<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">7</span></a> As a case in point&#44; both the Canadian Thoracic Society &#40;CTS&#41; and the Global initiative for chronic Obstructive Lung Disease &#40;GOLD&#41; recommend dichotomisation of patients into high- or low-AECOPD risk groups based on &#8805;2 moderate AECOPDs or &#8805;1 severe AECOPDs over the past year&#46;<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">8</span></a> This approach does not explicitly attach a quantifiable risk value to high- and low-risk patients&#44; but that does not a mean a risk treatment threshold is not applied&#46;</p><p id="par0030" class="elsevierStylePara elsevierViewall">To elucidate this implicit risk threshold&#44; we analyzed data from ECLIPSE &#40;Evaluation of COPD Longitudinally to identify Predictive Surrogate Endpoints&#41;&#44; a prospective three-year observational cohort study to document the natural history of AECOPDs&#46;<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">7</span></a> We used the AECOPD patterns during the first year to classify patients into risk groups&#46; We then used the second-year data to determine the observed risk of experiencing a moderate&#47;severe AECOPD&#46; For this analysis&#44; there were 1821 individuals who had complete AECOPD data for both years 1 and 2&#46; Ethics approval was obtained from The University of British Columbia&#47;Providence Health Care Human Ethics Board &#40;H11-00786&#41;&#46; The results are provided in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0035" class="elsevierStylePara elsevierViewall">Each row reports the calculated risk of patients experiencing at least one moderate or severe AECOPD in year 2 according to their year 1 AECOPD history&#46; There are two groups that are considered non-frequent exacerbators according to the CTS&#47;GOLD definition&#58; those with no AECOPDs&#44; and those with one moderate AECOPD &#40;the first two rows&#41;&#46; The second-year risk of AECOPD in these groups was&#44; respectively&#44; 33&#37; and 62&#37;&#46; All other groups are considered frequent exacerbators&#46; The second-year risk among frequent exacerbators ranged from 71&#37; to 97&#37;&#46;</p><p id="par0040" class="elsevierStylePara elsevierViewall">Imagine we are considering treatment in a patient who currently uses inhaled long-acting beta-2 agonists &#40;LABA&#41; and long-acting muscarinic antagonists &#40;LAMA&#41;&#46; GOLD&#47;CTS guidelines recommend inhaled corticosteroid &#40;ICS&#41; therapy only for frequent exacerbators &#40;highlighted rows in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#41;&#46; If we apply guideline treatment recommendations to ECLIPSE data&#44; we would prescribe ICS for those with 71&#37; risk for future AECOPDs &#40;fourth row&#41;&#44; but not those with a 62&#37; chance &#40;second row&#41;&#46; One conclusion is thus inescapable&#58; the current definition of a frequent exacerbator phenotype implicitly assigns a treatment threshold of somewhere between 62&#37; and 71&#37; on the 12-month AECOPD risk&#46;</p><p id="par0045" class="elsevierStylePara elsevierViewall">Is this an evidence-based threshold for ICS therapy&#63; Are there any empirical data on patient or physician-based values and preferences of ICS therapy that support this range of treatment threshold&#63; To the best of our knowledge&#44; no formal assessment was conducted to choose a particular range of treatment thresholds for stepping up therapy&#46; Further&#44; because this range of thresholds is opaque&#44; the idea of risk cannot be properly conveyed to patients and thus their voice cannot be incorporated into their management plans&#46; We also note that this range of thresholds is affected by the case-mix observed in ECLIPSE&#44; and might be different in different patient population&#46; This threshold may also be affected by biomarkers of efficacy such as blood eosinophil count&#46; For example&#44; a recent modelling study showed that in patients with a blood eosinophil count of less than 150<span class="elsevierStyleHsp" style=""></span>cells&#47;&#956;L&#44; ICS was not net beneficial regardless of the baseline risk of AECOPD&#46;<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">9</span></a></p></span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Towards a risk-based approach for prevention of AECOPDs</span><p id="par0050" class="elsevierStylePara elsevierViewall">If the principles of rational decision-making are to be applied&#44; the treatment threshold should be determined based on a careful consideration of the benefit&#8211;harm profile of individual treatments as well as the preferences and values of patients who ultimately bear the consequence of our decisions&#46; To move the COPD community towards true personalized medicine and precision health&#44; we advocate several important next steps&#46; The first is to embrace the idea of multivariable risk prediction for quantitative risk generation&#46; While AECOPD history carries some information on the risk of AECOPD&#44; other patient and disease characteristics in aggregate can significantly improve the predictability of AECOPD risk&#44;<a class="elsevierStyleCrossRef" href="#bib0110"><span class="elsevierStyleSup">10</span></a> with a recent analysis demonstrating that validated risk prediction algorithms provide higher clinical utility compared to AECOPD history alone across a wide range of treatment thresholds&#46;<a class="elsevierStyleCrossRef" href="#bib0115"><span class="elsevierStyleSup">11</span></a></p><p id="par0055" class="elsevierStylePara elsevierViewall">Another step is to decide on treatment thresholds&#46; This can be based on quantitative benefit&#8211;harm analysis that considers the totality of evidence on the effectiveness and adverse events profile of a given medication&#44; combined with eliciting the preferences of patients on how they trade off the benefits and harms of a treatment&#46;<a class="elsevierStyleCrossRef" href="#bib0120"><span class="elsevierStyleSup">12</span></a> Importantly&#44; treatment thresholds might be different for different subgroups and across different treatment modalities&#46; For example&#44; it is unlikely that the decision to add a relatively safe drug like LAMA would correspond to the same threshold as a more controversial treatment such as maintenance oral azithromycin&#46; Finally&#44; we will need empirical evidence in terms of real world &#8216;impact&#8217; studies that compare the outcomes of using such risk-based approach towards disease management versus the <span class="elsevierStyleItalic">status quo</span>&#46; The path in front of us might be long&#44; but the shortcomings of a history-based approach are apparent&#44; and so are the promises and potentials of an objective and transparent risk-based approach for COPD management&#46;</p></span></span>"
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Editorial
The Hidden and Unchecked Judgement Calls When Using Exacerbation History for Managing COPD
Mohsen Sadatsafavia,
Corresponding author
msafavi@mail.ubc.ca

Corresponding author.
, Shawn D. Aaronb, Andrea S. Gershonc, Milo Puhand, Amin Adibia, Don D. Sine
a Respiratory Evaluation Sciences Program, Collaboration for Outcomes Research and Evaluation, Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, Canada
b The Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Canada
c Institute of Clinical Evaluation Sciences, University of Toronto, Toronto, Canada
d Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
e Centre for Heart Lung Innovation, University of British Columbia, Vancouver, Canada
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    "textoCompleto" => "<span class="elsevierStyleSections"><p id="par0005" class="elsevierStylePara elsevierViewall">Chronic obstructive pulmonary disease &#40;COPD&#41; is one of the most common and debilitating disorders globally&#46; Acute exacerbations of COPD &#40;AECOPD&#41; are a defining feature of the disease and a major source of its burden&#46; Consequently&#44; the prevention of AECOPDs is a cornerstone of modern COPD management strategies&#46; In many guidelines&#44; important disease management decisions&#44; in particular the choice of pharmacotherapy&#44; is based on AECOPD history in the previous twelve months&#46;</p><p id="par0010" class="elsevierStylePara elsevierViewall">While intuitive and parsimonious&#44; this approach has several weaknesses that limit its application in clinical practice&#46; First&#44; this approach produces inherently unstable groups over time&#46; We recently demonstrated in 2 large cohorts that reliance on the patients&#8217; AECOPD history often leads to repeated reclassification of patients from year-to-year &#40;from frequent to non-frequent exacerbator phenotype or vice versa&#41; even when the underlying rate of exacerbation remains stable&#46;<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">1</span></a> For example&#44; a patient with a stable underlying AECOPD rate of 2 events per year has a 47&#37; chance of switching between frequent and non-frequent exacerbator in two consecutive years due to chance alone&#46; In this editorial&#44; we highlight a second fundamental weakness of this approach&#58; the &#8220;hiddenness&#8221; of treatment thresholds&#46;</p><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0005">Treatment threshold at the heart of rational decision making</span><p id="par0015" class="elsevierStylePara elsevierViewall">In their classic paper published more than four decades ago&#44; Pauker and Kassirer applied principles of decision theory to argue that the chance that a patient has a particular disease or is at a risk of a particular event is a crucial factor in the choice of treatment&#46;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">2</span></a> Because individuals at a high risk of poor outcomes are more likely to benefit from treatments than those at a low risk&#44; there exists a risk &#8216;treatment threshold&#8217; at which the benefits and harms of a given treatment are in perfect balance&#46; Above this treatment threshold&#44; the benefits of the treatment outweigh its harms&#46; Below this threshold&#44; the reduction in risk will not offset potential treatment harms&#46;</p><p id="par0020" class="elsevierStylePara elsevierViewall">This treatment threshold approach towards clinical decision making has been widely adopted in some specialties&#46; A leading example is primary prevention of cardiovascular diseases &#40;CVD&#41;&#46; For example&#44; the American guidelines on the primary prevention of CVD generally consider a treatment threshold for preventive pharmacotherapies &#40;e&#46;g&#46;&#44; statins&#41; to be between 7&#46;5&#37; and 20&#37; with regards to the 10-year risk for acute CVD events&#46;<a class="elsevierStyleCrossRefs" href="#bib0075"><span class="elsevierStyleSup">3&#44;4</span></a> At risks below 7&#46;5&#37;&#44; preventive therapies are not considered net beneficial&#44; whereas at predicted risks above 20&#37; they are considered highly beneficial&#46; Within the 7&#46;5&#8211;20&#37; range &#40;i&#46;e&#46; the &#8220;grey zone&#8221;&#41;&#44; the benefit&#8211;harm balance hinges on how the patient values reduction in CVD risk versus the risk of adverse events&#46; For some patients&#44; postponing preventative treatment may be the preferred approach&#59; while in those who are more willing to accept the risk of adverse events&#44; aggressive preventive pharmacotherapeutics may be warranted&#46; Thus&#44; a shared decision-making approach is recommended when the risk falls in the grey zone&#46; There are many examples of explicit treatment thresholds on predicted risks in other subspecialties such as fracture prevention in post-menopausal women&#44;<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">5</span></a> or screening for breast cancer&#46;<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">6</span></a></p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">The implicit treatment threshold in history-based COPD management</span><p id="par0025" class="elsevierStylePara elsevierViewall">Contemporary AECOPD prevention strategies are based on patients&#8217; AECOPD history over the previous year premised on the idea that <span class="elsevierStyleItalic">previous exacerbation history is the best predictor of future risk</span>&#46;<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">7</span></a> As a case in point&#44; both the Canadian Thoracic Society &#40;CTS&#41; and the Global initiative for chronic Obstructive Lung Disease &#40;GOLD&#41; recommend dichotomisation of patients into high- or low-AECOPD risk groups based on &#8805;2 moderate AECOPDs or &#8805;1 severe AECOPDs over the past year&#46;<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">8</span></a> This approach does not explicitly attach a quantifiable risk value to high- and low-risk patients&#44; but that does not a mean a risk treatment threshold is not applied&#46;</p><p id="par0030" class="elsevierStylePara elsevierViewall">To elucidate this implicit risk threshold&#44; we analyzed data from ECLIPSE &#40;Evaluation of COPD Longitudinally to identify Predictive Surrogate Endpoints&#41;&#44; a prospective three-year observational cohort study to document the natural history of AECOPDs&#46;<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">7</span></a> We used the AECOPD patterns during the first year to classify patients into risk groups&#46; We then used the second-year data to determine the observed risk of experiencing a moderate&#47;severe AECOPD&#46; For this analysis&#44; there were 1821 individuals who had complete AECOPD data for both years 1 and 2&#46; Ethics approval was obtained from The University of British Columbia&#47;Providence Health Care Human Ethics Board &#40;H11-00786&#41;&#46; The results are provided in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0035" class="elsevierStylePara elsevierViewall">Each row reports the calculated risk of patients experiencing at least one moderate or severe AECOPD in year 2 according to their year 1 AECOPD history&#46; There are two groups that are considered non-frequent exacerbators according to the CTS&#47;GOLD definition&#58; those with no AECOPDs&#44; and those with one moderate AECOPD &#40;the first two rows&#41;&#46; The second-year risk of AECOPD in these groups was&#44; respectively&#44; 33&#37; and 62&#37;&#46; All other groups are considered frequent exacerbators&#46; The second-year risk among frequent exacerbators ranged from 71&#37; to 97&#37;&#46;</p><p id="par0040" class="elsevierStylePara elsevierViewall">Imagine we are considering treatment in a patient who currently uses inhaled long-acting beta-2 agonists &#40;LABA&#41; and long-acting muscarinic antagonists &#40;LAMA&#41;&#46; GOLD&#47;CTS guidelines recommend inhaled corticosteroid &#40;ICS&#41; therapy only for frequent exacerbators &#40;highlighted rows in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#41;&#46; If we apply guideline treatment recommendations to ECLIPSE data&#44; we would prescribe ICS for those with 71&#37; risk for future AECOPDs &#40;fourth row&#41;&#44; but not those with a 62&#37; chance &#40;second row&#41;&#46; One conclusion is thus inescapable&#58; the current definition of a frequent exacerbator phenotype implicitly assigns a treatment threshold of somewhere between 62&#37; and 71&#37; on the 12-month AECOPD risk&#46;</p><p id="par0045" class="elsevierStylePara elsevierViewall">Is this an evidence-based threshold for ICS therapy&#63; Are there any empirical data on patient or physician-based values and preferences of ICS therapy that support this range of treatment threshold&#63; To the best of our knowledge&#44; no formal assessment was conducted to choose a particular range of treatment thresholds for stepping up therapy&#46; Further&#44; because this range of thresholds is opaque&#44; the idea of risk cannot be properly conveyed to patients and thus their voice cannot be incorporated into their management plans&#46; We also note that this range of thresholds is affected by the case-mix observed in ECLIPSE&#44; and might be different in different patient population&#46; This threshold may also be affected by biomarkers of efficacy such as blood eosinophil count&#46; For example&#44; a recent modelling study showed that in patients with a blood eosinophil count of less than 150<span class="elsevierStyleHsp" style=""></span>cells&#47;&#956;L&#44; ICS was not net beneficial regardless of the baseline risk of AECOPD&#46;<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">9</span></a></p></span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Towards a risk-based approach for prevention of AECOPDs</span><p id="par0050" class="elsevierStylePara elsevierViewall">If the principles of rational decision-making are to be applied&#44; the treatment threshold should be determined based on a careful consideration of the benefit&#8211;harm profile of individual treatments as well as the preferences and values of patients who ultimately bear the consequence of our decisions&#46; To move the COPD community towards true personalized medicine and precision health&#44; we advocate several important next steps&#46; The first is to embrace the idea of multivariable risk prediction for quantitative risk generation&#46; While AECOPD history carries some information on the risk of AECOPD&#44; other patient and disease characteristics in aggregate can significantly improve the predictability of AECOPD risk&#44;<a class="elsevierStyleCrossRef" href="#bib0110"><span class="elsevierStyleSup">10</span></a> with a recent analysis demonstrating that validated risk prediction algorithms provide higher clinical utility compared to AECOPD history alone across a wide range of treatment thresholds&#46;<a class="elsevierStyleCrossRef" href="#bib0115"><span class="elsevierStyleSup">11</span></a></p><p id="par0055" class="elsevierStylePara elsevierViewall">Another step is to decide on treatment thresholds&#46; This can be based on quantitative benefit&#8211;harm analysis that considers the totality of evidence on the effectiveness and adverse events profile of a given medication&#44; combined with eliciting the preferences of patients on how they trade off the benefits and harms of a treatment&#46;<a class="elsevierStyleCrossRef" href="#bib0120"><span class="elsevierStyleSup">12</span></a> Importantly&#44; treatment thresholds might be different for different subgroups and across different treatment modalities&#46; For example&#44; it is unlikely that the decision to add a relatively safe drug like LAMA would correspond to the same threshold as a more controversial treatment such as maintenance oral azithromycin&#46; Finally&#44; we will need empirical evidence in terms of real world &#8216;impact&#8217; studies that compare the outcomes of using such risk-based approach towards disease management versus the <span class="elsevierStyleItalic">status quo</span>&#46; The path in front of us might be long&#44; but the shortcomings of a history-based approach are apparent&#44; and so are the promises and potentials of an objective and transparent risk-based approach for COPD management&#46;</p></span></span>"
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                  <table border="0" frame="\n
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                  \t\t\t\t">Severe&#58; 0&#47;Moderate&#58; 0&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">Severe&#58; 0&#47;Moderate&#58; 1&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">Non-frequent exacerbator&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">62&#37; &#40;57&#37;&#8211;67&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">83&#37; &#40;79&#37;&#8211;87&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                      "titulo" => "Should the number of acute exacerbations in the previous year be used to guide treatments in COPD&#63;"
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                          "etal" => false
                          "autores" => array:6 [
                            0 => "M&#46; Sadatsafavi"
                            1 => "J&#46; McCormack"
                            2 => "J&#46; Petkau"
                            3 => "L&#46;D&#46; Lynd"
                            4 => "T&#46;Y&#46; Lee"
                            5 => "D&#46;D&#46; Sin"
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                      "doi" => "10.1183/13993003.02122-2020"
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                        "tituloSerie" => "Eur Respir J"
                        "fecha" => "2021"
                        "volumen" => "57"
                        "paginaInicial" => "2002122"
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Article information
ISSN: 03002896
Original language: English
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