Pere Almagro

Spanish guideline for COPD (GesEPOC). Update 2014.

aServicio de Neumologia, Hospital Universitari Vall d’Hebron, Barcelona, Spain bCIBER de Enfermedades Respiratorias (CIBERES), Spain cUnidad de Neumologia, Servicio de Medicina Interna, Hospital de Requena, Valencia, Spain dServicio de Neumologia, Hospital Clinico San Carlos, Madrid, Spain eCentro de Salud Francia, Direccion Asistencial Oeste, Madrid, Spain fServicio de Medicina Interna, Hospital Universitari Mutua de Terrassa, Terrasa, Barcelona, Spain gCentro de Salud Lucena I, Lucena, Cordoba, Spain hServicio de Neumologia, Hospital San Pedro de Alcantara, Caceres, Spain iCentro de Salud Menasalbas, Toledo, Spain jServicio de Urgencias, Hospital General Universitario Reina Sofia, Murcia, Spain kServicio de Urgencias, Hospital General Yague, Burgos, Spain lMedicina Fisica y Rehabilitacion, Parc de Salut Mar, Grupo de Investigacion en Rehabilitacion, Institut Hospital del Mar d’Investigacions Mediques, Universitat Autonoma de Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain mUnidad de Fisioterapia Respiratoria, Hospital Universitario de Gran Canaria Dr. Negrin, Facultad de Ciencias de la Salud, Universidad de Las Palmas de Gran Canaria, Spain nServicio de Medicina Fisica y Rehabilitacion, Hospital Germans Trias i Pujol, Universitat Autonoma de Barcelona, Badalona, Barcelona, Spain nServicio de Medicina Fisica y Rehabilitacion, Hospital Parc Tauli, Universitat Autonoma de Barcelona, Sabadell, Barcelona, Spain oCentro de Salud Gandhi, Madrid, Spain pServicio de Medicina Interna, Hospital Royo Vilanova, Zaragoza, Spain qFundacion Caubet-Cimera FISIB Illes Balears, Bunyola, Baleares, Spain rServicio de Neumologia, Hospital Universitario de la Princesa, Instituto de Investigacion Sanitaria Princesa (IP), Madrid, Spain

Distribution and Prognostic Validity of the New Global Initiative for Chronic Obstructive Lung Disease Grading Classification

BACKGROUND The new Global Initiative for Chronic Obstructive Lung Disease (GOLD) update includes airflow limitation, history of COPD exacerbations, and symptoms to classify and grade COPD severity. We aimed to determine their distribution in 11 well-defined COPD cohorts and their prognostic validity up to 10 years to predict time to death. METHODS Spirometry in all 11 cohorts was postbronchodilator. Survival analysis and C statistics were used to compare the two GOLD systems by varying time points. RESULTS Of 3,633 patients, 1,064 (33.6%) were in new GOLD patient group A (low risk, less symptoms), 515 (16.3%) were B (low risk, more symptoms), 561 (17.7%) were C (high risk, less symptoms), and 1,023 (32.3%) were D (high risk, more symptoms). There was great heterogeneity of this distribution within the cohorts ( x (2) , P < .01). No differences were seen in the C statistics of old vs new GOLD grading to predict mortality at 1 year (0.635 vs 0.639, P = .53), at 3 years (0.637 vs 0.645, P = .21), or at 10 years (0.639 vs 0.642, P = .76). CONCLUSIONS The new GOLD grading produces an uneven split of the COPD population, one third each in A and D patient groups, and its prognostic validity to predict time to death is no different than the old GOLD staging based in spirometry only.

Multicomponent indices to predict survival in COPD: the COCOMICS study

Guidelines recommend defining chronic obstructive pulmonary disease (COPD) by airflow obstruction and other factors, but no studies have evaluated the ability of existing multicomponent indices to predict mortality up to 10 years. We conducted a patient-based pooled analysis. Survival analysis and C statistics were used to determine the best COPD index/indices according to several construct variables and by varying time-points. Individual data of 3633 patients from 11 COPD cohorts were collected, totalling the experience of 15 878 person-years. Overall, there were 1245 death events within our cohorts, with a Kaplan–Meier survival of 0.963 at 6 months, which was reduced to 0.432 at 10 years. In all patients, ADO (age, dyspnoea and forced expiratory volume in 1 s), BODE (body mass index, airflow obstruction, dyspnoea and exercise capacity) and e-BODE (BODE plus exacerbations) were the best indices to predict 6-month mortality. The ADO index was the best to predict 12-month (C statistic 0.702), 5-year (C statistic 0.695) and 10-year mortality (C statistic 0.698), and was significantly better than BODE (all p<0.05). The best indices to predict death by C statistics when adjusting by age were e-BODE, BODEx (substitution of exacerbations for exercise capacity) and BODE. No index predicts short-term survival of COPD well. All BODE modifications scored better than ADO after age adjustment. The ADO and BODE indices are overall the most valid multicomponent indices to predict time to death in all COPD patients.

Pseudomonas aeruginosa in patients hospitalised for COPD exacerbation: a prospective study.

Risk factors for Pseudomonas aeruginosa (PA) isolation in patients hospitalised for chronic obstructive pulmonary disease (COPD) exacerbation remain controversial. The aim of our study was to determine the incidence and risk factors for PA isolation in sputum at hospital admission in a prospective cohort of patients with acute exacerbation of COPD. We prospectively studied all patients with COPD exacerbation admitted to our hospital between June 2003 and September 2004. Suspected predictors of PA isolation were studied. Spirometry tests and 6-min walking tests were performed 1 month after the patients were discharged. High-resolution computed tomography (HRCT) was performed in a randomised manner in one out of every two patients to quantify the presence and extent of bronchiectasis. Patients were followed up during the following year for hospital re-admissions. A total of 188 patients were included, of whom 31 (16.5%) had PA in sputum at initial admission. The BODE (body mass index, airflow obstruction, dyspnoea, exercise capacity) index (OR 2.18, CI 95% 1.26–3.78; p = 0.005), admissions in the previous year (OR 1.65, CI 95% 1.13–2.43; p = 0.005), systemic steroid treatment (OR 14.7, CI 95% 2.28–94.8; p = 0.01), and previous isolation of PA (OR 23.1, CI 95% 5.7–94.3; p<0.001) were associated with PA isolation. No relationship was seen between bronchiectasis in HRCT and antibiotic use in the previous 3 months. PA in sputum at hospital admission is more frequent in patients with poorer scoring on the BODE index, previous hospital admissions, oral corticosteroids and prior isolation of PA.

A new approach to grading and treating COPD based on clinical phenotypes: summary of the Spanish COPD guidelines (GesEPOC).

After the development of the COPD Strategy of the National Health Service in Spain, all scientific societies, patient organisations, and central and regional governments formed a partnership to enhance care and research in COPD. At the same time, the Spanish Society of Pneumology and Thoracic Surgery (SEPAR) took the initiative to convene the various scientific societies involved in the National COPD Strategy and invited them to participate in the development of the new Spanish guidelines for COPD (Guía Española de la EPOC; GesEPOC). Probably the more innovative approach of GesEPOC is to base treatment of stable COPD on clinical phenotypes, a term which has become increasingly used in recent years to refer to the different clinical forms of COPD with different prognostic implications. The proposed phenotypes are: (A) infrequent exacerbators with either chronic bronchitis or emphysema; (B) overlap COPD-asthma; (C) frequent exacerbators with emphysema predominant; and (D) frequent exacerbators with chronic bronchitis predominant. The assessment of severity has also been updated with the incorporation of multidimensional indices. The severity of the obstruction, as measured by forced expiratory volume in 1 second, is essential but not sufficient. Multidimensional indices such as the BODE index have shown excellent prognostic value. If the 6-minute walking test is not performed routinely, its substitution by the frequency of exacerbations (BODEx index) provides similar prognostic properties. This proposal aims to achieve a more personalised management of COPD according to the clinical characteristics and multidimensional assessment of severity.

Recent improvement in long-term survival after a COPD hospitalisation

Background Evidence-based international guidelines on chronic obstructive pulmonary disease (COPD), and their corresponding recommendations, were established to improve individual COPD prognosis, and ultimately to improve survival. The aim of this study was to determine whether the long-term mortality after discharge from a COPD hospitalisation has improved recently, and the effect of co-morbidity treatment in improving COPD prognosis. Methods In a prospective cohort study design of two cohorts 7 years apart, patients discharged from the same university hospital after a COPD exacerbation were followed-up, and their outcomes compared. Demographic and clinical variables, as well as lung function, were collected with the same protocol by the same investigators. Comprehensive assessments of co-morbidities and treatments were undertaken. Kaplan–Meier survival curves were estimated, and outcomes were compared by means of Cox regression methods. Results Overall, 135 participants in the 1996–7 cohort and 181 participants in the 2003–4 cohort were studied. Both cohorts were comparable in their baseline demographic and clinical variables, and median follow-up was 439 days. The 3-year mortality was lower in the 2003–4 cohort (38.7%) than in the 1996–7 cohort (47.4%) (p=0.017), and the RR of death after adjustment for gender, age, body mass index, co-morbidities, lung function and mMRC (modified Medical Research Council scale) dyspnoea was 0.66 (95% CI 0.45 to 0.97). Long-term survival improved in the second cohort for patients with COPD with heart failure or cancer (p<0.001). Conclusions A recent trend towards better prognosis of patients with COPD after hospital discharge is described and is likely to be associated with better management and treatment of COPD and co-morbidities.

Guía española de la EPOC (GesEPOC). Actualización 2014

Servicio de Neumología, Hospital Universitari Vall d’Hebron, Barcelona, Spain CIBER de Enfermedades Respiratorias (CIBERES), Spain Unidad de Neumología, Servicio de Medicina Interna, Hospital de Requena, Valencia, Spain Servicio de Neumología, Hospital Clínico San Carlos, Madrid, Spain Centro de Salud Francia, Dirección Asistencial Oeste, Madrid, Spain Servicio de Medicina Interna, Hospital Universitari Mútua de Terrassa, Terrasa, Barcelona, Spain Centro de Salud Lucena I, Lucena, Córdoba, Spain Servicio de Neumología, Hospital San Pedro de Alcántara, Cáceres, Spain Centro de Salud Menasalbas, Toledo, Spain Servicio de Urgencias, Hospital General Universitario Reina Sofía, Murcia, Spain Servicio de Urgencias, Hospital General Yagüe, Burgos, Spain Medicina Física y Rehabilitación, Parc de Salut Mar, Grupo de Investigación en Rehabilitación, Institut Hospital del Mar d’Investigacions Mèdiques, Universitat Autònoma de Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain Unidad de Fisioterapia Respiratoria, Hospital Universitario de Gran Canaria Dr. Negrín, Facultad de Ciencias de la Salud, Universidad de Las Palmas de Gran Canaria, Spain Servicio de Medicina Física y Rehabilitación, Hospital Germans Trias i Pujol, Universitat Autònoma de Barcelona, Badalona, Barcelona, Spain Servicio de Medicina Física y Rehabilitación, Hospital Parc Taulí, Universitat Autònoma de Barcelona, Sabadell, Barcelona, Spain Centro de Salud Gandhi, Madrid, Spain Servicio de Medicina Interna, Hospital Royo Vilanova, Zaragoza, Spain Fundación Caubet-Cimera FISIB Illes Balears, Bunyola, Baleares, Spain Servicio de Neumología, Hospital Universitario de la Princesa, Instituto de Investigación Sanitaria Princesa (IP), Madrid, SpainServicio de Neumología, Hospital Universitari Vall d’Hebron, Barcelona, España CIBER de Enfermedades Respiratorias (CIBERES), España Unidad de Neumología, Servicio de Medicina Interna, Hospital de Requena, Valencia, España Servicio de Neumología, Hospital Clínico San Carlos, Madrid, España Centro de Salud Francia, Dirección Asistencial Oeste, Madrid, España Servicio de Medicina Interna, Hospital Universitari Mútua de Terrassa, Terrasa, Barcelona, España Centro de Salud Lucena I, Lucena, Córdoba, España Servicio de Neumología, Hospital San Pedro de Alcántara, Cáceres, España Centro de Salud Menasalbas, Toledo, España Servicio de Urgencias, Hospital General Universitario Reina Sofía, Murcia, España Servicio de Urgencias, Hospital General Yagüe, Burgos, España Medicina Física y Rehabilitación, Parc de Salut Mar, Grupo de Investigación en Rehabilitación, Institut Hospital del Mar d’Investigacions Mèdiques, Universitat Autònoma de Barcelona, Universitat Internacional de Catalunya, Barcelona, España Unidad de Fisioterapia Respiratoria, Hospital Universitario de Gran Canaria Dr. Negrín, Facultad de Ciencias de la Salud, Universidad de Las Palmas de Gran Canaria, España Servicio de Medicina Física y Rehabilitación, Hospital Germans Trias i Pujol, Universitat Autònoma de Barcelona, Badalona, Barcelona, España Servicio de Medicina Física y Rehabilitación, Hospital Parc Taulí, Universitat Autònoma de Barcelona, Sabadell, Barcelona, España Centro de Salud Gandhi, Madrid, España Servicio de Medicina Interna, Hospital Royo Vilanova, Zaragoza, España Fundación Caubet-Cimera FISIB Illes Balears, Bunyola, Baleares, España Servicio de Neumología, Hospital Universitario de la Princesa, Instituto de Investigación Sanitaria Princesa (IP), Madrid, España

Mortality prediction in chronic obstructive pulmonary disease comparing the GOLD 2007 and 2011 staging systems: a pooled analysis of individual patient data

BACKGROUND There is no universal consensus on the best staging system for chronic obstructive pulmonary disease (COPD). Although documents (eg, the Global Initiative for Chronic Obstructive Lung Disease [GOLD] 2007) have traditionally used forced expiratory volume in 1 s (FEV1) for staging, clinical parameters have been added to some guidelines (eg, GOLD 2011) to improve patient management. As part of the COPD Cohorts Collaborative International Assessment (3CIA) initiative, we aimed to investigate how individual patients were categorised by GOLD 2007 and 2011, and compare the prognostic accuracy of the staging documents for mortality. METHODS We searched reports published from Jan 1, 2008, to Dec 31, 2014. Using data from cohorts that agreed to participate and had a minimum amount of information needed for GOLD 2007 and 2011, we did a patient-based pooled analysis of existing data. With use of raw data, we recalculated all participant assignments to GOLD 2007 I-IV classes, and GOLD 2011 A-D stages. We used survival analysis, C statistics, and non-parametric regression to model time-to-death data and compare GOLD 2007 and GOLD 2011 staging systems to predict mortality. FINDINGS We collected individual data for 15 632 patients from 22 COPD cohorts from seven countries, totalling 70 184 person-years. Mean age of the patients was 63·9 years (SD 10·1); 10 751 (69%) were men. Based on FEV1 alone (GOLD 2007), 2424 (16%) patients had mild (I), 7142 (46%) moderate (II), 4346 (28%) severe (III), and 1670 (11%) very severe (IV) disease. We compared staging with the GOLD 2007 document with that of the new GOLD 2011 system in 14 660 patients: 5548 (38%) were grade A, 2733 (19%) were grade B, 1835 (13%) were grade C, and 4544 (31%) were grade D. GOLD 2011 shifted the overall COPD severity distribution to more severe categories. There were nearly three times more COPD patients in stage D than in former stage IV (p<0·05). The predictive capacity for survival up to 10 years was significant for both systems (p<0·01) but area under the curves were only 0·623 (GOLD 2007) and 0·634 (GOLD 2011), and GOLD 2007 and 2011 did not differ significantly. We identified the percent predicted FEV1 thresholds of 85%, 55% and 35% as better to stage COPD severity for mortality, which are similar to the ones used previously. INTERPRETATION Neither GOLD COPD classification schemes have sufficient discriminatory power to be used clinically for risk classification at the individual level to predict total mortality for 3 years of follow-up and onwards. Increasing intensity of treatment of patients with COPD due to their GOLD 2011 reclassification is not known to improve health outcomes. Evidence-based thresholds should be searched when exploring the prognostic ability of current and new COPD multicomponent indices. FUNDING None.

Prevalence, Risk Factors and Diagnostic Accuracy of COPD Among Smokers in Primary Care

Abstract The prevalence of COPD is high, and most cases remain undiagnosed. In contrast, some patients labeled and treated as COPD do not have spirometric confirmation. Our objective was to determine the prevalence of COPD among smokers aged 45 years or older and investigate the accuracy of diagnosis of COPD in primary care. A population-based, epidemiological study was conducted in a primary care centre among subjects older than 45 years with a history of smoking. The participants underwent a clinical questionnaire and spirometry with bronchodilator test. Additionally, participants with newly diagnosed COPD, defined as postbronchodilator FEV1/FVC<0.7, underwent 4-week treatment with formoterol and budesonide to rule out reversible airflow obstruction. A total of 1,738 individuals (84.4% male) with a mean age of 59.9 years were included. The prevalence of COPD was 24.3% (95%, CI 22.3–26.4), with an overall underdiagnosis of 56.7%. Patients with COPD were older, more frequently male, with a lower body mass index, a longer history of smoking, lower educational level, previous occupational exposure, and more cardiovascular co-morbidity (all p < 0.001). After 4 weeks of treatment, 16% of initially obstructed patients had normal spirometry; in addition, 15.6% of individuals with a diagnosis of COPD did not have airflow obstruction. One out of four smokers 45 years or older presenting in primary care have airflow obstruction, mostly undiagnosed. However, among those with an initial diagnosis of COPD up to 16% will normalise spirometry after 4 weeks of treatment. There is also a significant number of individuals misdiagnosed with COPD.

Underdiagnosis and prognosis of chronic obstructive pulmonary disease after percutaneous coronary intervention: a prospective study

Background Retrospective studies based on clinical data and without spirometric confirmation suggest a poorer prognosis of patients with ischemic heart disease (IHD) and chronic obstructive pulmonary disease (COPD) following percutaneous coronary intervention (PCI). The impact of undiagnosed COPD in these patients is unknown. We aimed to evaluate the prognostic impact of COPD – previously or newly diagnosed – in patients with IHD treated with PCI. Methods Patients with IHD confirmed by PCI were consecutively included. After PCI they underwent forced spirometry and evaluation for cardiovascular risk factors. All-cause mortality, new cardiovascular events, and their combined endpoint were analyzed. Results A total of 133 patients (78%) male, with a mean (SD) age of 63 (10.12) years were included. Of these, 33 (24.8%) met the spirometric criteria for COPD, of whom 81.8% were undiagnosed. IHD patients with COPD were older, had more coronary vessels affected, and a greater history of previous myocardial infarction. Median follow-up was 934 days (interquartile range [25%–75%]: 546–1,160). COPD patients had greater mortality (P=0.008; hazard ratio [HR]: 8.85; 95% confidence interval [CI]: 1.76–44.47) and number of cardiovascular events (P=0.024; HR: 1.87; 95% CI: 1.04–3.33), even those without a previous diagnosis of COPD (P=0.01; HR: 1.78; 95% CI: 1.12–2.83). These differences remained after adjustment for sex, age, number of coronary vessels affected, and previous myocardial infarction (P=0.025; HR: 1.83; 95% CI: 1.08–3.1). Conclusion Prevalence and underdiagnosis of COPD in patients with IHD who undergo PCI are both high. These patients have an independent greater mortality and a higher number of cardiovascular events during follow-up.