Trends of pulmonary fungal infections from 2013 to 2019: an AI-based real-world observational study in Guangzhou, China
Recently, the prevalence trend of pulmonary fungal infection (PFI) has rapidly increased. Changes in the risk factors for, distributions of underlying diseases associated with and clinical characteristics of some individual PFIs have been reported in the past decade. However, data regarding PFIs rem...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2021-01-01
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| Series: | Emerging Microbes and Infections |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/22221751.2021.1894902 |
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| author | Zhengtu Li Yongming Li Yijun Chen Jing Li Shaoqiang Li Chenglong Li Ye Lin Wenhua Jian Jingrong Shi Yangqing Zhan Jing Cheng Jingping Zheng Nanshan Zhong Feng Ye |
| author_facet | Zhengtu Li Yongming Li Yijun Chen Jing Li Shaoqiang Li Chenglong Li Ye Lin Wenhua Jian Jingrong Shi Yangqing Zhan Jing Cheng Jingping Zheng Nanshan Zhong Feng Ye |
| author_sort | Zhengtu Li |
| collection | DOAJ |
| description | Recently, the prevalence trend of pulmonary fungal infection (PFI) has rapidly increased. Changes in the risk factors for, distributions of underlying diseases associated with and clinical characteristics of some individual PFIs have been reported in the past decade. However, data regarding PFIs remain uncertain. This study reports the epidemiological characteristics and trends of PFIs over time in recent years. We applied an automated natural language processing (NLP) system to extract clinically relevant information from the electronic health records (EHRs) of PFI patients at the First Affiliated Hospital of Guangzhou Medical University. Then, a trend analysis was performed. From January 1, 2013, to December 31, 2019, 40,504 inpatients and 219,414 outpatients with respiratory diseases were screened, in which 1368 inpatients and 1313 outpatients with PFI were identified. These patients were from throughout the country, but most patients were from southern China. Upward trends in PFIs were observed in both hospitalized patients and outpatients (P<0.05). The stratification by age showed that the incidence of hospitalized patients aged 14–30 years exhibited the most obvious upward trend, increasing from 9.5 per 1000 patients in 2013 to 88.3 per 1000 patients in 2019. Aspergillosis (56.69%) was the most common PFI, but notably, the incidence rates of Talaromyces marneffei, which used to be considered uncommon, exhibited the most rapid increases. In younger PFI patients, the incidence and trend of PFIs have increased. Infection by previously uncommon pathogens has also gradually increased. Increased attention should be paid to young PFI patients and uncommon PFI pathogen infections. |
| format | Article |
| id | doaj-art-79bc5e07c49744db89698dadad8d5a0c |
| institution | Kabale University |
| issn | 2222-1751 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Emerging Microbes and Infections |
| spelling | doaj-art-79bc5e07c49744db89698dadad8d5a0c2025-08-20T03:52:57ZengTaylor & Francis GroupEmerging Microbes and Infections2222-17512021-01-0110145046010.1080/22221751.2021.1894902Trends of pulmonary fungal infections from 2013 to 2019: an AI-based real-world observational study in Guangzhou, ChinaZhengtu Li0Yongming Li1Yijun Chen2Jing Li3Shaoqiang Li4Chenglong Li5Ye Lin6Wenhua Jian7Jingrong Shi8Yangqing Zhan9Jing Cheng10Jingping Zheng11Nanshan Zhong12Feng Ye13State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of ChinaState Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of ChinaState Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of ChinaGuangzhou Tianpeng Technology Co., Ltd., Guangzhou, People’s Republic of ChinaState Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of ChinaGuangzhou Tianpeng Technology Co., Ltd., Guangzhou, People’s Republic of ChinaState Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of ChinaState Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of ChinaGuangzhou Tianpeng Technology Co., Ltd., Guangzhou, People’s Republic of ChinaState Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of ChinaState Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of ChinaState Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of ChinaState Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of ChinaState Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of ChinaRecently, the prevalence trend of pulmonary fungal infection (PFI) has rapidly increased. Changes in the risk factors for, distributions of underlying diseases associated with and clinical characteristics of some individual PFIs have been reported in the past decade. However, data regarding PFIs remain uncertain. This study reports the epidemiological characteristics and trends of PFIs over time in recent years. We applied an automated natural language processing (NLP) system to extract clinically relevant information from the electronic health records (EHRs) of PFI patients at the First Affiliated Hospital of Guangzhou Medical University. Then, a trend analysis was performed. From January 1, 2013, to December 31, 2019, 40,504 inpatients and 219,414 outpatients with respiratory diseases were screened, in which 1368 inpatients and 1313 outpatients with PFI were identified. These patients were from throughout the country, but most patients were from southern China. Upward trends in PFIs were observed in both hospitalized patients and outpatients (P<0.05). The stratification by age showed that the incidence of hospitalized patients aged 14–30 years exhibited the most obvious upward trend, increasing from 9.5 per 1000 patients in 2013 to 88.3 per 1000 patients in 2019. Aspergillosis (56.69%) was the most common PFI, but notably, the incidence rates of Talaromyces marneffei, which used to be considered uncommon, exhibited the most rapid increases. In younger PFI patients, the incidence and trend of PFIs have increased. Infection by previously uncommon pathogens has also gradually increased. Increased attention should be paid to young PFI patients and uncommon PFI pathogen infections.https://www.tandfonline.com/doi/10.1080/22221751.2021.1894902Epidemiologyincidencetrendsartificial intelligencepulmonary fungal infection |
| spellingShingle | Zhengtu Li Yongming Li Yijun Chen Jing Li Shaoqiang Li Chenglong Li Ye Lin Wenhua Jian Jingrong Shi Yangqing Zhan Jing Cheng Jingping Zheng Nanshan Zhong Feng Ye Trends of pulmonary fungal infections from 2013 to 2019: an AI-based real-world observational study in Guangzhou, China Emerging Microbes and Infections Epidemiology incidence trends artificial intelligence pulmonary fungal infection |
| title | Trends of pulmonary fungal infections from 2013 to 2019: an AI-based real-world observational study in Guangzhou, China |
| title_full | Trends of pulmonary fungal infections from 2013 to 2019: an AI-based real-world observational study in Guangzhou, China |
| title_fullStr | Trends of pulmonary fungal infections from 2013 to 2019: an AI-based real-world observational study in Guangzhou, China |
| title_full_unstemmed | Trends of pulmonary fungal infections from 2013 to 2019: an AI-based real-world observational study in Guangzhou, China |
| title_short | Trends of pulmonary fungal infections from 2013 to 2019: an AI-based real-world observational study in Guangzhou, China |
| title_sort | trends of pulmonary fungal infections from 2013 to 2019 an ai based real world observational study in guangzhou china |
| topic | Epidemiology incidence trends artificial intelligence pulmonary fungal infection |
| url | https://www.tandfonline.com/doi/10.1080/22221751.2021.1894902 |
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