Clinical differences between eosinophilic and non-eosinophilic acute exacerbation of chronic obstructive pulmonary disease (AECOPD), a multicenter cross-sectional study


 Background AECOPD is highly heterogeneous with respect to etiology and inflammation. COPD with higher blood eosinophils is associated with increased readmission rates and better corticosteroid response. However, the clinical features of eosinophilic AECOPD aren’t well explored. Then, the aim of this study was to investigate the clinical differences between eosinophilic and non-eosinophilic AECOPD. Methods A total of 643 AECOPD patients were enrolled in this multicenter cross-sectional study. Finally, 455 were included, 214 in normal eosinophils AECOPD (NEOS-AECOPD) group, 63 in mild increased eosinophils AECOPD (MEOS-AECOPD) group, and 138 in severe increased eosinophils AECOPD (SEOS-AECOPD) group. Then, demographic data, underlying diseases, symptoms, and laboratory findings were collected. Multiple logistic regression was performed to identify the independent factors associated with blood EOS. Correlations between blood EOS and its associated independent factors were evaluated. Results The significant differences in 19 factors, including underlying disease, clinical symptom, and laboratory parameters, were identified by univariate analysis. Subsequently, multiple logistic regression revealed that lymphocytes%, neutrophils% (NS%), procalcitonin (PCT), and anion gap (AG) were associated with blood EOS in AECOPD. Both blood EOS counts and EOS% significantly correlated with lymphocytes%, NS%, PCT, and AG. Conclusions The blood EOS was independently associated with lymphocytes%, NS%, PCT, and AG in AECOPD patients. Lymphocytes% was lower, and, NS%, PCT, and AG were higher in eosinophilic AECOPD. Our results indicate that viral dominant infections probably were the major etiology of eosinophilic AECOPD. Non-eosinophilic AECOPD was more likely associated with bacterial dominant infections. The systemic inflammation in non-eosinophilic AECOPD was more severe.


Background
COPD is the most common chronic pulmonary disorder. It is found that the prevalence of COPD is gradually increasing in recent decades [1][2][3]. Wang C et al showed that the prevalence of COPD was 8.6%, about 99.9 million patients, in mainland China [2]. It is estimated that about 3.2 million people died from COPD worldwide in 2015 [1]. Globally, COPD is going to be the third leading cause of death by diseases in recent years [3,4]. Meanwhile, COPD is also a highly heterogeneous disease [5,6]. In clinical practice, the response and outcome of the treatments were different individually. Most clinicians realized the importance and needs of individual and target therapies in COPD.
However, mounting evidence reported that sputum and blood eosinophils also increased in a subset of COPD patients [17,21,22]. Several studies showed that higher blood eosinophil counts were associated with an increased risk of readmission, severe lung function impairment, and longer length hospital stay (LHS) in COPD [23][24][25][26]. Some studies identi ed that inhaled corticosteroid (ICS) plus long-acting β2-agonist (LABA) and ICS plus LABA plus long-acting muscarinic antagonist (LAMA) brought more bene ts in eosinophilic (EOS) COPD than in non-eosinophilic COPD [27,28]. Therefore, increased blood EOS was considered to be a "treatable trait" of COPD [18,24]. Nevertheless, the clinical features of eosinophilic hospitalized AECOPD are still not well studied. Thus, the aim of this study was to investigate the clinical differences between eosinophilic and non-eosinophilic AECOPD.
Additionally, the best cut-off value of blood EOS is still not determined. With the cut-off of EOS% ≥ 2% and/or EOS counts ≥ 200 cells/μL, Couillard S et al showed that the risk of 12-month COPD-related readmission in eosinophilic AECOPD was increased and LHS was not different, compared with non-eosinophilic AECOPD [21]. With the cut-off value of 300 cells/μL, Qi YJ et al found that sputum microbiome richness and plasma IL-6 level in eosinophilic AECOPD decreased more signi cantly than in non-eosinophilic AECOPD, after 7 days treatments [29]. Cheng SL et al demonstrated that the ICS response in COPD with EOS% > 3% was better than non-eosinophilic COPD [30]. Therefore, in our study, based on both blood EOS counts and EOS%, the patients with AECOPD were divided into 3 subgroups (Figure 1).

Study design and population
This multicenter cross-sectional study was performed at respiratory departments of two tertiary hospitals in China between January 2017 and January 2020. This study was approved by the Research Ethics Committees of our hospital (No. 2019-23) in accordance with the Declaration of Helsinki. Informed consent was obtained from all the patients by the responsible physician or an appropriately trained staff member. Standard care and treatments were provided in our study according to current clinical guidelines [3,5].

Sample size determinations
As for sample size, a minimum total of 159 (53 in each group) was required to detect at least a 25% difference in effect size for an 80% power, assuming α = 0.05 and allocation ratio = 1:1:1. Furthermore, 20% more (64 in each group) patients were recruited.

Inclusion and exclusion criteria
The inclusion criterion was COPD exacerbation requiring hospitalization. Exclusion criteria were as follows: age < 40 years, non-respiratory failure patients without lung function test, active pulmonary tuberculosis (TB), asthma, bronchiectasis, pneumoconiosis, interstitial lung diseases (ILDs), other chronic lung diseases, dysphagia and aspiration, dementia, hospital-acquired pneumonia (HAP), immunocompromised status (organ transplant, system steroid use within the last 2 weeks, immunosuppressive agents use within the last 4 weeks, and HIV infection), history of malignant diseases, renal failure, and liver failure. A total of 643 patients with hospitalized AECOPD were enrolled. Finally, 455 were included, 214 in normal eosinophils AECOPD (NEOS-AECOPD) group, 63 in mild increased eosinophils AECOPD (MEOS-AECOPD) group, and 138 in severe increased eosinophils AECOPD (SEOS-AECOPD) group ( Figure 1).

De nitions
According to the COPD guidelines [3,5], the diagnosis of COPD was con rmed by the pulmonologists, based on noxious stimuli exposure history, risk factors, clinical symptoms, and spirometry (FEV1/FVC% < 0.7 after bronchodilator inhalation). AECOPD was de ned as an event in the natural course of the disease characterized by acute changes in clinical symptoms beyond normal day-to-day variation, resulting in additional therapy [3,5]. Both blood EOS counts and EOS% were considered to set the cut-off values of EOS. In this study, normal eosinophils AECOPD (NEOS-AECOPD) was de ned as AECOPD with EOS% < 2% and EOS counts < 200 cells/μL. Mild increased eosinophils AECOPD (MEOS-AECOPD) was de ned as AECOPD with EOS% 2%-2.99% and/or EOS counts 200-299 cells/μl. Severe increased eosinophils AECOPD (SEOS-AECOPD) was de ned as AECOPD with EOS% ≥ 3% and/or EOS counts ≥ 300 cells/μL. The ex-smoker was de ned as abstaining from smoking ≥ 6 months. Neutrophils-to-lymphocytes ratio (NLR) was de ned as neutrophils divided by lymphocytes in the blood.

Data collection
In our study, demographic data, underlying diseases, comorbid conditions, symptoms, and length of hospital stay (LHS) were recorded and collected. The blood samples for laboratory tests and lung function tests were all collected and performed within 24h after admission. However, for safety reason and cooperation concerns, the spirometer test wasn't performed in patients with respiratory failure. All patients underwent CT scans within 48 hours of hospitalization and the results were reviewed by one independent radiologist and one pulmonologist in each hospital.

Statistical analysis
Data were analyzed using SPSS 20.0 software (SPSS Inc., Chicago, IL, USA). Continuous variables were expressed as the Mean ± Standard Deviation (SD), and categorical data were expressed as frequencies. The data distribution was analyzed by Kolmogorov-Smirnov test. Continuous variables with normal distribution were analyzed by one-way ANOVA with LSD and SNK's post-hoc test. Continuous variables with abnormal distribution and ordinal variables were measured by Kruskal-Wallis H test. Chi square test or Fisher's exact test was used to analyze categorical variables. Multiple logistic regression analysis was performed to investigate the independent risk factors associated with blood eosinophils in AECOPD patients.
Spearman rank correlation coe cient was calculated to analyze correlations. A threshold of p < 0.05 was considered to be signi cant.

Multiple logistic regression analysis in AECOPD patients.
To explore independent factors associated with blood eosinophils in AECOPD patients, multiple logistic regression analysis was performed. In multiple logistic regression model, 19 factors signi cantly association with blood eosinophils in univariate analysis, including the rates of CTD, 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 included. Multiple logistic regression analysis revealed that lymphocytes%, NS%, PCT, and AG were independently associated with blood eosinophils in AECOPD patients (Table   3).
Since lymphocytes%, NS%, PCT, and AG were independently associated with blood eosinophils in AECOPD patients. Then, their correlations with blood EOS counts and EOS% were explored. The signi cant correlations were found between blood EOS counts and lymphocytes%, NS%, PCT, AG, and, between blood EOS% and lymphocytes%, NS%, PCT, AG in patients with AECOPD (Table 4). Among them, lymphocytes% was positively, and, NS%, PCT, and AG were negatively correlated with blood EOS counts and EOS%.

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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 de ned as EOS% < 2% and EOS counts < 200 cells/μL, mild increased eosinophils AECOPD (MEOS-AECOPD) was de ned as EOS% 2%-2.99% and/or EOS counts 200-299 cells/μl, and severe increased eosinophils AECOPD (SEOS-AECOPD) was de ned 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 [32]. It was estimated that the global years lived with disability (YLDs) of COPD was about 29.4 million in 2010 [33].
Nevertheless, COPD is a highly heterogeneous disease, with signi cantly 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 de ne 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][35][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 signi cant 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 [37].
Kolsum U et al reported that compared with COPD with blood EOS < 150 cells/μL, EOS% in induced sputum, BALF, and submucosa were all signi cantly increased in COPD with blood EOS > 300 cells/μL [38]. 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 [36]. 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 signi cant. Meanwhile, in a randomized, double-blind, placebo-controlled trial (RCT), EOS counts and EOS% in induced sputum were markedly reduced after 16 weeks of ro umilast (a PDE4 inhibitor) treatment in COPD [39]. However, blood eosinophil counts were not changed by ro umilast. Whatever, the signi cant differences in some aspects of clinical characteristics and outcomes were identi ed 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][24][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 signi cantly different among 3 groups (Table 2).
Subsequently, 19 variables with signi cantly 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 in ammatory types were signi cantly different between eosinophilic and non-eosinophilic AECOPD patients. Namely, eosinophils and lymphocytes were the major in ammatory cells in eosinophilic AECOPD, and, neutrophils were the dominant in ammatory cells in noneosinophilic AECOPD. Meanwhile, it is well known that respiratory tract infection is the leading etiology of acute exacerbation in COPD [3,35,[41][42][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 [43]. 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 [41]. Simultaneously, several studies showed that airway eosinophilic in ammation was related to viral infection in AECOPD [35,41]. Additionally, it is con rmed that blood neutrophils and PCT are the biomarkers of bacterial infection in COPD [44]. In a meta-analysis, Ni W et al showed that the sensitivity and speci city of PCT in diagnosing bacterial infections were 0.60 and 0.76, and AUC of ROC curve was 0.77 [44]. Ergan B et al found that compared with culture-negative patients, PCT was markedly increased in culture-positive patients in AECOPD [45]. Their data also showed that 0.25 ng/ml was the optimal cut-off value, with 63% sensitivity, 67% speci city, 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 signi cantly 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 signi cantly lower than in AECOPD patients without hospitalization (non-severe patients) [46]. Taken together, these results indicate that bacterial infection and systemic in ammation 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.

Conclusions
Collectively, our results indicated that lymphocytes%, NS%, PCT, and AG were the independent factors associated with blood EOS in AECOPD patients. Viral and viral dominant infections probably were the major etiology of eosinophilic AECOPD. Then, non-eosinophilic AECOPD was more likely associated with bacterial and bacterial dominant infections. The systemic in ammation in non-eosinophilic AECOPD was more severe than in eosinophilic AECOPD. Nevertheless, further study with high sensitivity and speci city in pathogen tests, such as bronchoscope, should be carried out to validate this result.   Figure 1 The ow diagram of the study.