Factors affecting the severity of respiratory infections: a hospital-based cross-sectional study
Abstract Background Acute respiratory infections (ARIs) are a leading cause of global morbidity and mortality, with disease severity influenced by factors such as advanced age, underlying comorbidities, and pathogen type. This report analyzed the association between several clinical variables and di...
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BMC
2025-05-01
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| Series: | BMC Infectious Diseases |
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| Online Access: | https://doi.org/10.1186/s12879-025-11121-z |
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| author | Yunshao Xu Li Qi Jule Yang Yuping Duan Mingyue Jiang Yanxia Sun Yanlin Cao Zeni Wu Wenge Tang Luzhao Feng |
| author_facet | Yunshao Xu Li Qi Jule Yang Yuping Duan Mingyue Jiang Yanxia Sun Yanlin Cao Zeni Wu Wenge Tang Luzhao Feng |
| author_sort | Yunshao Xu |
| collection | DOAJ |
| description | Abstract Background Acute respiratory infections (ARIs) are a leading cause of global morbidity and mortality, with disease severity influenced by factors such as advanced age, underlying comorbidities, and pathogen type. This report analyzed the association between several clinical variables and disease severity. Methods A hospital-based cross-sectional study was conducted from September 2023 to April 2024, with data collected from eight districts in Chongqing, China. The study included 1,638 patients with ARIs, including both severe and mild cases. Severe cases were identified using the qSOFA and APACHE II scores, while demographic and clinical data were obtained via questionnaires and hospital records. Pathogen detection was performed using real-time quantitative PCR. Data analysis was carried out using Stata 17.0, with multiple logistic regression models assessing the associations between clinical factors and disease severity. Results Influenza A was the most prevalent pathogen, detected in 65.1% of severe cases and 32.9% of mild cases (P < 0.001). 42.0% (165/393) of severe cases had viral and bacterial co-infections, compared to 26.8% (334/1,245) of mild cases (P < 0.001). The most common pathogens in co-infections included influenza A and Streptococcus pneumoniae. Severe cases were more common in rural areas (28.8% vs. 18.1%, P < 0.001) and among older adults (≥ 60 years) (28.2% vs. 13.5%, P < 0.001). Clinical symptoms such as fever (61.8% vs. 40.9%, P < 0.001), cough (68.7% vs. 53.2%, P < 0.001), and dyspnea (34.8% vs. 15.1%, P < 0.001) were significantly more prevalent in severe cases. Logistic regression analysis showed that influenza A (OR: 4.52, 95% CI: 3.51–5.85), Streptococcus pneumoniae (OR: 1.54, 95% CI: 1.28–2.15), and pre-existing cardiovascular diseases (OR: 1.96, 95% CI: 1.28–2.99) were significantly associated with the development of severe outcomes. Conclusions This study underscores the complex interplay of factors influencing ARI severity, including pathogen type, co-infections, age, and underlying medical conditions. Early identification of high-risk patients, particularly those with bacterial co-infections and cardiovascular comorbidities, is essential for improving clinical outcomes in ARI patients. Targeted treatment and preventative strategies are needed to mitigate severe disease in vulnerable populations. Clinical trial number Not applicable. |
| format | Article |
| id | doaj-art-418c49fc5fd84102b78e9ea39a73db96 |
| institution | OA Journals |
| issn | 1471-2334 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | BMC |
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| series | BMC Infectious Diseases |
| spelling | doaj-art-418c49fc5fd84102b78e9ea39a73db962025-08-20T01:52:24ZengBMCBMC Infectious Diseases1471-23342025-05-012511910.1186/s12879-025-11121-zFactors affecting the severity of respiratory infections: a hospital-based cross-sectional studyYunshao Xu0Li Qi1Jule Yang2Yuping Duan3Mingyue Jiang4Yanxia Sun5Yanlin Cao6Zeni Wu7Wenge Tang8Luzhao Feng9Public Health Emergency Management Innovation Center, State Key Laboratory of Respiratory Health and Multimorbidity, Key Laboratory of Pathogen Infection Prevention and Control (Peking Union Medical College), School of Population Medicine and Public Health, Ministry of Education, Chinese Academy of Medical Science & Peking Union Medical CollegeChongqing Municipal Center for Disease Control and PreventionChongqing Municipal Center for Disease Control and PreventionPublic Health Emergency Management Innovation Center, State Key Laboratory of Respiratory Health and Multimorbidity, Key Laboratory of Pathogen Infection Prevention and Control (Peking Union Medical College), School of Population Medicine and Public Health, Ministry of Education, Chinese Academy of Medical Science & Peking Union Medical CollegePublic Health Emergency Management Innovation Center, State Key Laboratory of Respiratory Health and Multimorbidity, Key Laboratory of Pathogen Infection Prevention and Control (Peking Union Medical College), School of Population Medicine and Public Health, Ministry of Education, Chinese Academy of Medical Science & Peking Union Medical CollegePublic Health Emergency Management Innovation Center, State Key Laboratory of Respiratory Health and Multimorbidity, Key Laboratory of Pathogen Infection Prevention and Control (Peking Union Medical College), School of Population Medicine and Public Health, Ministry of Education, Chinese Academy of Medical Science & Peking Union Medical CollegePublic Health Emergency Management Innovation Center, State Key Laboratory of Respiratory Health and Multimorbidity, Key Laboratory of Pathogen Infection Prevention and Control (Peking Union Medical College), School of Population Medicine and Public Health, Ministry of Education, Chinese Academy of Medical Science & Peking Union Medical CollegePublic Health Emergency Management Innovation Center, State Key Laboratory of Respiratory Health and Multimorbidity, Key Laboratory of Pathogen Infection Prevention and Control (Peking Union Medical College), School of Population Medicine and Public Health, Ministry of Education, Chinese Academy of Medical Science & Peking Union Medical CollegeChongqing Municipal Center for Disease Control and PreventionPublic Health Emergency Management Innovation Center, State Key Laboratory of Respiratory Health and Multimorbidity, Key Laboratory of Pathogen Infection Prevention and Control (Peking Union Medical College), School of Population Medicine and Public Health, Ministry of Education, Chinese Academy of Medical Science & Peking Union Medical CollegeAbstract Background Acute respiratory infections (ARIs) are a leading cause of global morbidity and mortality, with disease severity influenced by factors such as advanced age, underlying comorbidities, and pathogen type. This report analyzed the association between several clinical variables and disease severity. Methods A hospital-based cross-sectional study was conducted from September 2023 to April 2024, with data collected from eight districts in Chongqing, China. The study included 1,638 patients with ARIs, including both severe and mild cases. Severe cases were identified using the qSOFA and APACHE II scores, while demographic and clinical data were obtained via questionnaires and hospital records. Pathogen detection was performed using real-time quantitative PCR. Data analysis was carried out using Stata 17.0, with multiple logistic regression models assessing the associations between clinical factors and disease severity. Results Influenza A was the most prevalent pathogen, detected in 65.1% of severe cases and 32.9% of mild cases (P < 0.001). 42.0% (165/393) of severe cases had viral and bacterial co-infections, compared to 26.8% (334/1,245) of mild cases (P < 0.001). The most common pathogens in co-infections included influenza A and Streptococcus pneumoniae. Severe cases were more common in rural areas (28.8% vs. 18.1%, P < 0.001) and among older adults (≥ 60 years) (28.2% vs. 13.5%, P < 0.001). Clinical symptoms such as fever (61.8% vs. 40.9%, P < 0.001), cough (68.7% vs. 53.2%, P < 0.001), and dyspnea (34.8% vs. 15.1%, P < 0.001) were significantly more prevalent in severe cases. Logistic regression analysis showed that influenza A (OR: 4.52, 95% CI: 3.51–5.85), Streptococcus pneumoniae (OR: 1.54, 95% CI: 1.28–2.15), and pre-existing cardiovascular diseases (OR: 1.96, 95% CI: 1.28–2.99) were significantly associated with the development of severe outcomes. Conclusions This study underscores the complex interplay of factors influencing ARI severity, including pathogen type, co-infections, age, and underlying medical conditions. Early identification of high-risk patients, particularly those with bacterial co-infections and cardiovascular comorbidities, is essential for improving clinical outcomes in ARI patients. Targeted treatment and preventative strategies are needed to mitigate severe disease in vulnerable populations. Clinical trial number Not applicable.https://doi.org/10.1186/s12879-025-11121-zRespiratory infectionsCross-sectional studySeverity |
| spellingShingle | Yunshao Xu Li Qi Jule Yang Yuping Duan Mingyue Jiang Yanxia Sun Yanlin Cao Zeni Wu Wenge Tang Luzhao Feng Factors affecting the severity of respiratory infections: a hospital-based cross-sectional study BMC Infectious Diseases Respiratory infections Cross-sectional study Severity |
| title | Factors affecting the severity of respiratory infections: a hospital-based cross-sectional study |
| title_full | Factors affecting the severity of respiratory infections: a hospital-based cross-sectional study |
| title_fullStr | Factors affecting the severity of respiratory infections: a hospital-based cross-sectional study |
| title_full_unstemmed | Factors affecting the severity of respiratory infections: a hospital-based cross-sectional study |
| title_short | Factors affecting the severity of respiratory infections: a hospital-based cross-sectional study |
| title_sort | factors affecting the severity of respiratory infections a hospital based cross sectional study |
| topic | Respiratory infections Cross-sectional study Severity |
| url | https://doi.org/10.1186/s12879-025-11121-z |
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