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Research Article
This cross-sectional study characterized pathogen distribution using serological testing and sputum culture in hospitalized patients with acute exacerbations of chronic obstructive pulmonary disease in Heyuan and examined infection types across disease severity stages.
This cross-sectional study aimed to characterize the pathogen profile among hospitalized patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) in the Heyuan region and examine the distribution of infection types across severity grades defined by the Global Initiative for Chronic Obstructive Lung Disease (GOLD). The study included 203 hospitalized patients with AECOPD from the largest comprehensive tertiary Grade A hospital in Heyuan. Pathogen screening was performed using serological antibody testing and sputum culture. The overall pathogen detection rate was 50.25%, while non-infectious factors accounted for 49.75%. Atypical pathogens were frequently detected, with Mycoplasma pneumoniae accounting for 35.96% and influenza virus for 11.82%. Mixed infections comprised 17.24%, and pure atypical pathogen infections represented 22.17%. Among the 109 AECOPD patients stratified by disease severity, simple viral and mixed pathogen infections had the highest combined proportions of severe and very severe cases (100.0% and 92.9%, respectively). These findings characterize pathogen detection patterns among hospitalized patients with AECOPD in Heyuan and demonstrate variation in infection types across GOLD severity grades. The findings should be interpreted cautiously because serological detection, particularly M. pneumoniae immunoglobulin G (IgG), cannot independently distinguish previous exposure from active infection. C-reactive protein (CRP) and procalcitonin (PCT) measurements may provide additional information when evaluating infection patterns; however, the observational study design does not establish treatment efficacy or support GOLD-stage-specific therapeutic recommendations.
Chronic obstructive pulmonary disease (COPD) is a leading cause of illness and death worldwide, with acute exacerbations (AECOPD) acting as key drivers of disease progression and associated mortality1. These acute episodes, characterized by a sudden worsening of respiratory symptoms, are often precipitated by respiratory infections, including viruses, bacteria, and atypical pathogens2,3. While the influence of bacterial infections is well documented, recognition of viral and atypical pathogens, such as Mycoplasma pneumoniae and Chlamydia pneumoniae, as important contributors to exacerbation events has grown in recent years4. Geographic variability and differences in patient demographics influence the distribution of these pathogens, making their relationship with disease severity—categorized according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) grading system—an area requiring further study5.
The current diagnostic approach for AECOPD relies mainly on conventional sputum cultures, a method with notable limitations, including a low positivity rate of 34.28%–41.12%6,7, long turnaround times, and a limited ability to detect fastidious or non-culturable organisms. As such, this conventional approach often fails to provide a complete picture of the infection profile. In particular, it is unable to detect non-bacterial pathogens, including viruses and atypical agents, which are important triggers of exacerbations8,9. Previous investigations have shown that atypical pathogens detected using serological methods may be comparatively rare in certain populations, while their identification remains limited by the insensitivity of culture-based diagnostics4,10. Reliance on traditional culture practices creates a diagnostic gap, potentially leading to the underrecognition of mixed infections and inappropriate use of antibiotics, which may contribute to increasing antimicrobial resistance11.
Previous investigations have shown that atypical pathogens and viruses, such as M. pneumoniae and respiratory syncytial virus, occur in patients experiencing respiratory exacerbations but may escape detection through routine testing12,13. The complexity of the etiology is further increased by the coexistence of diverse pathogen types, including atypical bacteria, viruses, and fungi, which can complicate empirical antibiotic treatment14. Difficulties in identifying these pathogens may arise from the limitations of conventional culture-based methodologies coupled with insufficient clinical vigilance, particularly among frontline practitioners in resource-limited settings7.
Existing epidemiological studies on AECOPD have largely originated from economically advanced eastern cities or prominent teaching hospitals, providing limited data that may not capture the full spectrum of the disease in economically disadvantaged regions with limited medical resources15. Previous studies have shown that individuals with chronic illnesses residing in rural and underserved areas encounter significant barriers to healthcare access, including lower provider density, greater distances to medical facilities, and higher poverty rates, which often contribute to delayed diagnoses and suboptimal management16,17. The microbiological profile of AECOPD in such areas may differ from that observed in urban environments because of differences in environmental exposures, socioeconomic influences, and healthcare-seeking behaviors18. Consequently, conclusions drawn from well-resourced urban centers may not directly apply to empirical antimicrobial strategies in regions such as northeastern Guangdong, where local epidemiological data remain limited. This geographic discrepancy highlights the need for targeted investigations to characterize the pathogen profile of AECOPD in resource-constrained settings.
Given such heterogeneity, reliance on a single empirical antibiotic strategy without knowledge of the local microbiological profile may lead to suboptimal treatment outcomes and increased inappropriate antimicrobial use19,20. A thorough understanding of the local pathogen profile is important for AECOPD management because misuse of antimicrobial agents contributes to increasing antibiotic resistance11. Investigations have demonstrated the frequent presence of non-typeable Haemophilus influenzae, Streptococcus pneumoniae, and Moraxella catarrhalis as prevalent bacterial pathogens in numerous settings21; however, the distribution of these organisms varies according to geographic factors, patient demographics, and disease severity22,23. A proportion of exacerbations has also been associated with atypical pathogens, including M. pneumoniae and C. pneumoniae, as well as respiratory viruses such as influenza and respiratory syncytial virus8.
To characterize the pathogen profile of AECOPD in this region, we combined serological antibody testing with sputum culture to provide a broader picture of pathogen distribution. The findings are intended to characterize local pathogen detection patterns and provide regional epidemiological information relevant to AECOPD management and local public health efforts.
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This study was approved by the Medical Ethics Committee of Heyuan People’s Hospital, Guangdong Provincial People’s Hospital Heyuan Hospital (approval ID: YXYJLL-BBCJ20210707). The requirement for informed consent was formally waived by the Ethics Committee because residual serum, sputum, or BALF specimens obtained during routine clinical care were used.
Study subjects
This cross-sectional study included 203 patients with AECOPD treated at the largest comprehensive tertiary Grade A hospital in the Heyuan region between October 2021 and August 2022. The inclusion criteria were as follows: (1) age >40 years; and (2) a diagnosis of AECOPD based on the 2021 GOLD guidelines. The exclusion criteria were as follows: (1) use of injectable corticosteroids within 1 month prior to admission; (2) the presence of other chronic lung diseases, such as active pulmonary tuberculosis, bronchiolitis obliterans, severe interstitial lung disease, bronchiectasis, diffuse panbronchiolitis, or lung cancer; and (3) incomplete medical records.
Methods
Blood sample testing
After enrollment, in addition to routine tests, residual blood samples from other tests conducted within 3 days of admission were collected. The residual blood samples were collected on the same day, aliquoted, stored at −20°C for one month, and retained for subsequent antibody analysis. Repeated freeze-thaw cycles were strictly avoided before testing. After all enrollments were completed, antibody tests were uniformly performed using a chemiluminescent magnetic particle detection platform for respiratory syncytial virus, adenovirus, enterovirus 71, Coxsackie virus B, influenza A virus, influenza B virus, C. pneumoniae, and L. pneumophila IgM antibodies and M. pneumoniae IgG antibodies. The assay positivity cutoff value for IgM was S/CO ≥ 1.0. A positive case of M. pneumoniae was defined as meeting both criteria: IgG ≥ 30.0 AU/mL and CRP > 10 mg/L. IgM, PCR, paired serology, and other confirmatory diagnostic methods were not used to identify M. pneumoniae. Strict internal quality-control procedures provided by the manufacturer were followed throughout the testing process.
Sputum or BALF sample testing
After enrollment, residual sputum or BALF specimens from other tests conducted within 3 days of admission were collected. All sputum specimens were initially screened by smear microscopy to evaluate cellular composition under light microscopy. Sputum quality was assessed under a low-power field (100× magnification). Sputum was considered of acceptable quality if it fulfilled either of the following criteria: <10 squamous epithelial cells and >25 leukocytes per low-power field, or >10 squamous epithelial cells per low-power field with a squamous epithelial cell-to-leukocyte ratio of <1:2.5. Qualified sputum specimens were cultured according to standard laboratory procedures, followed by automated bacterial identification and AST. Sputum samples were cultured on blood agar, chocolate agar, and Sabouraud agar plates and incubated at 35°C with 5% CO₂ for up to 72 h. Colony growth was assessed after 18–24 h, and suspected pathogenic colonies were selected and purified. Pathogen identification and AST were performed using commercial kits.
Observation content
The distribution of various pathogens in patients with AECOPD was analyzed. Infection types according to different GOLD stages were analyzed.
Statistical analysis
SPSS version 23.0 was used for data processing and statistical analysis. Measurement data were expressed as x̄ ± s and analyzed using the t-test. Count data were expressed as n (%) and analyzed using the χ2 test. The assumptions of the χ2 test were evaluated before statistical analysis. When expected cell counts were <5, Fisher’s exact test was used instead of the χ2 test. P < 0.05 was considered statistically significant. GOLD grading was performed according to the classification criteria in the 2021 GOLD guidelines: mild (FEV1%Pred ≥ 80%), moderate (50% ≤ FEV1%Pred < 80%), severe (30% ≤ FEV1%Pred < 50%), and very severe (FEV1%Pred < 30%).
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Baseline clinical characteristics
In total, 203 patients diagnosed with AECOPD were included in the study. Of these, 183 (90.1%) were male and 20 (9.9%) were female. The participants ranged in age from 43 to 93 years, with a mean age of 73.33 ± 9.17 years. The mean length of hospital stay was 9.56 ± 11.06 days, with a minimum of 3 days and a maximum of 145 days. Cough was the most prevalent clinical symptom, occurring in 195 patients (96.06%), followed by mucopurulen...
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In this study, we found an overall pathogen detection rate of 50.25% among patients with AECOPD. Atypical pathogens, primarily M. pneumoniae (35.96%), and viral agents, most commonly influenza virus (11.82%), accounted for substantial proportions of the detected pathogens. These findings describe the pathogen-detection patterns observed among patients with AECOPD in the Heyuan region. The M. pneumoniae positivity rate according to the study criterion was 35.96%. However, the positivity rate in our cohor...
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Conflict of Interest:
The authors declare that they have no conflicts of interest.
This work was supported by the Heyuan Special Topic on the Social Development Science and Technology Plan Project (No. 210730081601382). The authors thank Zhengzhou Antu Bioengineering Co., Ltd., for providing the detection reagents.
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| Name | Company | Catalog Number | Comments |
|---|---|---|---|
| Adenovirus IgM Antibody Detection Kit (Magnetic Particle Chemiluminescence Method) | Zhengzhou Antu Bioengineering Co., Ltd. | 30041604CM01 | For antibody detection |
| Automated Bacterial Identification and Antimicrobial Susceptibility Testing System | Beckman Coulter Commercial Enterprise (China) Co., Ltd. | MicroScan-WalkAway 96 Plus | Instrument used for automated bacterial identification and antimicrobial susceptibility testing; corresponding panels are listed below |
| Blood Agar Plate (BAP) | Jiangmen Kailin Trading Co., Ltd. | P0901 | For bacterial isolation and culture |
| Chocolate Agar Plate (CAP) | Guangzhou Detgerm Microbiological Science Ltd. | LS0209 | For bacterial isolation and culture |
| Chlamydia pneumoniae IgM Antibody Detection Kit (Magnetic Particle Chemiluminescence Method) | Zhengzhou Antu Bioengineering Co., Ltd. | 30041602CM01 | For antibody detection |
| Coxsackievirus Group B IgM Antibody Detection Kit (Magnetic Particle Chemiluminescence Method) | Zhengzhou Antu Bioengineering Co., Ltd. | 30041609CM01 | For antibody detection |
| Enterovirus 71 IgM Antibody Detection Kit (Magnetic Particle Chemiluminescence Method) | Zhengzhou Antu Bioengineering Co., Ltd. | 30041608CM01 | For antibody detection |
| Gram-negative Bacteria Identification and Antimicrobial Susceptibility Panel NUC79 | Beckman Coulter Commercial Enterprise (China) Co., Ltd. | B1017-431 | For bacterial identification and antimicrobial susceptibility testing |
| Influenza A Virus IgM Antibody Detection Kit (Magnetic Particle Chemiluminescence Method) | Zhengzhou Antu Bioengineering Co., Ltd. | 30041614CM01 | For antibody detection |
| Influenza B Virus IgM Antibody Detection Kit (Magnetic Particle Chemiluminescence Method) | Zhengzhou Antu Bioengineering Co., Ltd. | 30041615CM01 | For antibody detection |
| Legionella pneumophila IgM Antibody Detection Kit (Magnetic Particle Chemiluminescence Method) | Zhengzhou Antu Bioengineering Co., Ltd. | 30041605CM01 | For antibody detection |
| Light Microscope | Olympus Corporation | CX21 | Used for microscopic assessment of sputum specimen quality |
| Magnetic Particle Chemiluminescence Detection Platform | Zhengzhou Antu Bioengineering Co., Ltd. | Au2000 | Instrument used for serological antibody testing |
| Mycoplasma pneumoniae IgG Antibody Detection Kit (Magnetic Particle Chemiluminescence Method) | Zhengzhou Antu Bioengineering Co., Ltd. | 30041607CM01 | For antibody detection |
| PC33/Gram-positive Bacteria Identification and Antimicrobial Susceptibility Panel | Beckman Coulter Commercial Enterprise (China) Co., Ltd. | B1017-211 | For bacterial identification and antimicrobial susceptibility testing |
| Respiratory Syncytial Virus IgM Antibody Detection Kit (Magnetic Particle Chemiluminescence Method) | Zhengzhou Antu Bioengineering Co., Ltd. | 30041603CM01 | For antibody detection |
| Sabouraud Dextrose Agar (SDA) | Jiangmen Kailin Trading Co., Ltd. | P0719 | For fungal isolation and culture |
| SPSS, Version 23.0 | IBM Corp. | RRID:SCR_019096 | Statistical analysis software |
| Yeast-like Fungus Antimicrobial Susceptibility Test Kit | bioMérieux (Shanghai) Biological Product Co., Ltd. | 14204 | For fungal antimicrobial susceptibility testing |
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