In this multicenter cross-sectional study, the clinical features of patients with eosinophilic AECOPD were explored. Based on the two cut-off values of blood EOS, the patients were divided into 3 subgroups, normal eosinophils AECOPD (NEOS-AECOPD) was defined as EOS% < 2% and EOS counts < 200 cells/μL, mild increased eosinophils AECOPD (MEOS-AECOPD) was defined as EOS% 2%-2.99% and/or EOS counts 200-299 cells/μl, and severe increased eosinophils AECOPD (SEOS-AECOPD) was defined as EOS% ≥ 3% and/or EOS counts ≥ 300 cells/μL. Our results showed that lymphocytes%, NS%, PCT, and AG were the independent factors associated with blood EOS in AECOPD patients. Then, these results indicate that viral dominant infection probably was related to eosinophilic AECOPD. And, non-eosinophilic AECOPD was more likely associated with bacterial dominant infections.
As the most common lung disorder, the prevalence of COPD is still increasing in recent years [2, 3, 5]. It was estimated that the prevalence of COPD was 11.7% (8.4%-15.0%) and the COPD case number was about 384 million globally in 2010 [3, 4]. Wang, C et al showed that the overall prevalence of COPD in mainland China was 8.6% (95% CI 7.5-9.9) in ≥ 40 years-old population, namely about 99.9 (95% CI 76.3-135.7) million cases [2, 3]. Simultaneously, COPD is a chronic disease with high mortality and disability. It was reported that about 3 million people dead from COPD every year [3, 31]. Patel JG et al showed that COPD caused average of 5 more days of work absence and $641 short-term disability associated extra costs each year in the USA . It was estimated that the global years lived with disability (YLDs) of COPD was about 29.4 million in 2010 .
Nevertheless, COPD is a highly heterogeneous disease, with significantly differences in treatment response and outcomes in patients. Mounting evidence suggested that individual therapy and target therapy are the major trends of COPD in the future. Then, to explore and differentiate the phenotypes of COPD is valuable in clinical practice. In recent years, amount of studies showed that blood eosinophil is an effective, stable, and available biomarker in COPD, which can be used to define the phenotypes of COPD [17, 25, 34, 35]. However, the cut-off value of blood EOS is still in debate, ranging from 150 to 400 cells/μL and/or 2% to 4% in different studies [17, 18, 22, 24, 25, 34-36]. Then, in this study, both 200 cells/μL and 300 cells/μL, and, 2% and 3% were considered as the cut-off values of blood EOS counts and EOS% in AECOPD patients (Figure 1). According to demographic data, no differences in sex, age, BMI, smoking status, lung functions (GOLD stages), and most of comorbidities and complications were found among 3 groups (Table 1). Only connective tissue disease (CTD) was found significant differently among 3 groups. The rate of CTD in SEOS-AECOPD was higher than NEOS- and MEOS-AECOPD group (Table 1). These results indicate that sex, BMI, smoking, and lung function were not associated with blood EOS in AECOPD patients.
The correlations between blood EOS and EOS in the lungs (induced sputum, BAL, and tissues) were still in controversy. Many studied showed that blood EOS was considered to be a reasonably good predictor of EOS in airways in COPD patients [22, 37, 38]. Eltboli O et al showed that the strong correlations between blood EOS% and the submucosal eosinophil counts (r = 0.57) and reticular basement membrane (RBM) thickness (r = 0.59) were found in COPD . Kolsum U et al reported that compared with COPD with blood EOS < 150 cells/μL, EOS% in induced sputum, BALF, and submucosa were all significantly increased in COPD with blood EOS > 300 cells/μL . Nevertheless, several studies found that the correlation between lung tissue and blood EOS was not very well [36, 39]. Turato G et al explored the correlations between blood eosinophils and central airways, peripheral airways, and lung parenchyma, from COPD patients underwent lung resection for solitary pulmonary nodules without additional complications . Initially, no difference in the eosinophil number in central airways, peripheral airways, and lung parenchyma was observed in COPD, and, pulmonary eosinophil counts weren’t associated with disease severity. Subsequently, they revealed that the correlations between blood eosinophils and any of the three lung compartments were not significant. Meanwhile, in a randomized, double-blind, placebo-controlled trial (RCT), EOS counts and EOS% in induced sputum were markedly reduced after 16 weeks of roflumilast (a PDE4 inhibitor) treatment in COPD . However, blood eosinophil counts were not changed by roflumilast. Whatever, the significant differences in some aspects of clinical characteristics and outcomes were identified between eosinophilic and non-eosinophilic AECOPD patients by many studies [17, 20, 23-25, 30, 35, 40]. Mounting evidence showed that increased blood EOS was associated with higher risk readmission, severe lung function impairment, longer LHS and survival time, and better ICS response in COPD patients [23-25]. Nevertheless, the clinical features, particularly laboratory parameters, of eosinophilic AECOPD were still not well studied. In this study, commonly used laboratory parameters and tests, including blood routine, PCT, ESR, CRP, ABG, serum electrolytes, liver function test, and renal function test, were included. Our data showed that the rates of fever and MV, WBC, NS, NS%, lymphocytes%, NLR, PCT, CRP, ESR, AG, serum Na, serum K, serum Ca, serum Mg, BUN, DBIL, and LHS were significantly different among 3 groups (Table 2). Subsequently, 19 variables with significantly differences in univariate analysis were included in multiple logistic regression model. We found that lymphocytes%, NS%, PCT, and AG were independently associated with blood EOS in AECOPD patients.
Meanwhile, as shown in Table 4, lymphocytes% was positively, and, NS%, PCT, and AG were negatively correlated with both blood EOS counts and EOS% in AECOPD. In this study, according to the criteria, asthma was strictly excluded, which was considered to be the most commonly confounder of the COPD study [18, 23, 40]. Meanwhile, patients with recent system steroid use and immunosuppressive agents use were also excluded. These data indicate that inflammatory types were significantly different between eosinophilic and non-eosinophilic AECOPD patients. Namely, eosinophils and lymphocytes were the major inflammatory cells in eosinophilic AECOPD, and, neutrophils were the dominant inflammatory cells in non-eosinophilic AECOPD. Meanwhile, it is well known that respiratory tract infection is the leading etiology of acute exacerbation in COPD [3, 35, 41-43]. Among them, bacteria and viruses are the most common pathogens. In a prospective observational study, Bafadhel M et al showed that 55% and 29% of acute exacerbation were related to bacterial and viral infection in COPD . Meanwhile, Papi A et al demonstrated that bacterial and/or viral infection was found in 78.1% (29.7% bacterial, 23.4% viral, 25% viral/bacterial coinfection) of AECOPD patients . Simultaneously, several studies showed that airway eosinophilic inflammation was related to viral infection in AECOPD [35, 41]. Additionally, it is confirmed that blood neutrophils and PCT are the biomarkers of bacterial infection in COPD . In a meta-analysis, Ni W et al showed that the sensitivity and specificity of PCT in diagnosing bacterial infections were 0.60 and 0.76, and AUC of ROC curve was 0.77 . Ergan B et al found that compared with culture-negative patients, PCT was markedly increased in culture-positive patients in AECOPD . Their data also showed that 0.25 ng/ml was the optimal cut-off value, with 63% sensitivity, 67% specificity, and 0.73 AUC, to predict bacterial infection in AECOPD. Collectively, our results suggested that viral and virus dominant infections probably were the major etiology of eosinophilic acute exacerbation in COPD. Then, non-eosinophilic acute exacerbation in COPD was more likely associated with bacterial and bacterial dominant infection.
Additionally, NS%, PCT, and AG were negatively correlated with blood EOS in AECOPD (Table 4). And, AG, PCT, and NS% in SEOS-AECOPD were significantly lower than NEOS-AECOPD and MESO-AECOPD (Table 2). No difference in metabolic acidosis was observed in three groups (Table 1). Circulation and tissue hypoperfusion are associated with severe infection in clinical practice. Generally, hypoperfusion-induced hyperlactacidemia is the major reason for increased AG in infection diseases patients without renal failure and ketoacidosis. Durmuş U et al revealed that lactate clearance in AEOPD patients with hospitalization (severe patients) was significantly lower than in AECOPD patients without hospitalization (non-severe patients) . Taken together, these results indicate that bacterial infection and systemic inflammation in non-eosinophilic AECOPD were more severe than in eosinophilic AECOPD.
Due to low positive rates of sputum cultures, specimen contamination, and airway bacterial colonization in COPD patients, the pathogen results were not included to reduce biases and confounders, which was also one of the major limitations of our current study. Therefore, the direct correlations between pathogen types and blood eosinophils were not evaluated. The main strength of our study is that relatively comprehensive laboratory data were collected, which accurately evaluated the severity and complications of the underlying diseases. Particularly, chest HRCT scan was performed in each patient, which effectively promoted the diagnosis accuracy and excluded most other lung diseases. Furthermore, the different cut-off values of blood EOS were considered, making our data more convincible.