Epidemiological investigation of lower respiratory tract infections during influenza A (H1N1) pdm09 virus pandemic based on targeted next-generation sequencing
BackgroundCo-infection has been a significant contributor to morbidity and mortality in previous influenza pandemics. However, the current influenza A (H1N1) pdm09 virus pandemic, as the first major outbreak following the SARS-CoV-2 pandemic, may differ epidemiologically. Further investigation is ne...
Ausführliche Beschreibung
Autor*in: |
Xiaodan Li [verfasserIn] Yang Liu [verfasserIn] Minzhe Li [verfasserIn] Jing Bian [verfasserIn] Demei Song [verfasserIn] Chaoying Liu [verfasserIn] |
---|
Format: |
E-Artikel |
---|---|
Sprache: |
Englisch |
Erschienen: |
2023 |
---|
Schlagwörter: |
influenza A (H1N1) pdm09 virus |
---|
Übergeordnetes Werk: |
In: Frontiers in Cellular and Infection Microbiology - Frontiers Media S.A., 2016, 13(2023) |
---|---|
Übergeordnetes Werk: |
volume:13 ; year:2023 |
Links: |
---|
DOI / URN: |
10.3389/fcimb.2023.1303456 |
---|
Katalog-ID: |
DOAJ099256797 |
---|
LEADER | 01000naa a22002652 4500 | ||
---|---|---|---|
001 | DOAJ099256797 | ||
003 | DE-627 | ||
005 | 20240414022539.0 | ||
007 | cr uuu---uuuuu | ||
008 | 240414s2023 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.3389/fcimb.2023.1303456 |2 doi | |
035 | |a (DE-627)DOAJ099256797 | ||
035 | |a (DE-599)DOAJe2b06541efca4dd39be05fe2afecf96d | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
050 | 0 | |a QR1-502 | |
100 | 0 | |a Xiaodan Li |e verfasserin |4 aut | |
245 | 1 | 0 | |a Epidemiological investigation of lower respiratory tract infections during influenza A (H1N1) pdm09 virus pandemic based on targeted next-generation sequencing |
264 | 1 | |c 2023 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a Computermedien |b c |2 rdamedia | ||
338 | |a Online-Ressource |b cr |2 rdacarrier | ||
520 | |a BackgroundCo-infection has been a significant contributor to morbidity and mortality in previous influenza pandemics. However, the current influenza A (H1N1) pdm09 virus pandemic, as the first major outbreak following the SARS-CoV-2 pandemic, may differ epidemiologically. Further investigation is necessary to understand the specific features and impact of this influenza A pandemic. Study design: We conducted a retrospective cohort study at a Chinese hospital between January and April 2023, focusing on patients with lower respiratory tract infections. Pathogen detection employed targeted next-generation sequencing (tNGS) on bronchoalveolar lavage fluid (BALF) or sputum samples.ResultsThis study enrolled 167 patients with lower respiratory tract infections, and the overall positivity rate detected through tNGS was around 80%. Among them, 40 patients had influenza A (H1N1) pdm09 virus infection, peaking in March. In these patients, 27.5% had sole infections, and 72.5% had co-infections, commonly with bacteria. The frequently detected pathogens were Aspergillus fumigatus, SARS-CoV-2, and Streptococcus pneumoniae. For non-influenza A virus-infected patients, the co-infection rate was 36.1%, with 42.3% having SARS-CoV-2. Patients with influenza A virus infection were younger, had more females and diabetes cases. Among them, those with sole infections were older, with less fever and asthma but more smoking history. Regarding prognosis, compared to sole influenza A virus infection, co-infected patients demonstrated higher 21-day recovery rates and a higher incidence of heart failure. However, they exhibited lower proportions of respiratory failure, acute kidney failure, septic shock, and hospital stays lasting more than 10 days. Interestingly, patients with non-influenza A virus infection had a significantly lower 21-day recovery rate. Correlation analysis indicated that the 21-day recovery rate was only associated with influenza A (H1N1) pdm09 virus.ConclusionDuring the current pandemic, the influenza A (H1N1) pdm09 virus may have been influenced by the SARS-CoV-2 pandemic and did not exhibit a strong pathogenicity. In fact, patients infected with influenza A virus showed better prognoses compared to those infected with other pathogens. Additionally, tNGS demonstrated excellent detection performance in this study and showed great potential, prompting clinical physicians to consider its use as an auxiliary diagnostic tool. | ||
650 | 4 | |a influenza A (H1N1) pdm09 virus | |
650 | 4 | |a pandemic | |
650 | 4 | |a epidemiology | |
650 | 4 | |a targeted next-generation sequencing | |
650 | 4 | |a prognosis | |
653 | 0 | |a Microbiology | |
700 | 0 | |a Yang Liu |e verfasserin |4 aut | |
700 | 0 | |a Minzhe Li |e verfasserin |4 aut | |
700 | 0 | |a Jing Bian |e verfasserin |4 aut | |
700 | 0 | |a Demei Song |e verfasserin |4 aut | |
700 | 0 | |a Chaoying Liu |e verfasserin |4 aut | |
773 | 0 | 8 | |i In |t Frontiers in Cellular and Infection Microbiology |d Frontiers Media S.A., 2016 |g 13(2023) |w (DE-627)664968554 |w (DE-600)2619676-1 |x 22352988 |7 nnns |
773 | 1 | 8 | |g volume:13 |g year:2023 |
856 | 4 | 0 | |u https://doi.org/10.3389/fcimb.2023.1303456 |z kostenfrei |
856 | 4 | 0 | |u https://doaj.org/article/e2b06541efca4dd39be05fe2afecf96d |z kostenfrei |
856 | 4 | 0 | |u https://www.frontiersin.org/articles/10.3389/fcimb.2023.1303456/full |z kostenfrei |
856 | 4 | 2 | |u https://doaj.org/toc/2235-2988 |y Journal toc |z kostenfrei |
912 | |a GBV_USEFLAG_A | ||
912 | |a SYSFLAG_A | ||
912 | |a GBV_DOAJ | ||
912 | |a GBV_ILN_11 | ||
912 | |a GBV_ILN_20 | ||
912 | |a GBV_ILN_22 | ||
912 | |a GBV_ILN_23 | ||
912 | |a GBV_ILN_24 | ||
912 | |a GBV_ILN_39 | ||
912 | |a GBV_ILN_40 | ||
912 | |a GBV_ILN_60 | ||
912 | |a GBV_ILN_62 | ||
912 | |a GBV_ILN_63 | ||
912 | |a GBV_ILN_65 | ||
912 | |a GBV_ILN_69 | ||
912 | |a GBV_ILN_73 | ||
912 | |a GBV_ILN_74 | ||
912 | |a GBV_ILN_95 | ||
912 | |a GBV_ILN_105 | ||
912 | |a GBV_ILN_110 | ||
912 | |a GBV_ILN_151 | ||
912 | |a GBV_ILN_161 | ||
912 | |a GBV_ILN_170 | ||
912 | |a GBV_ILN_206 | ||
912 | |a GBV_ILN_213 | ||
912 | |a GBV_ILN_230 | ||
912 | |a GBV_ILN_285 | ||
912 | |a GBV_ILN_293 | ||
912 | |a GBV_ILN_602 | ||
912 | |a GBV_ILN_2003 | ||
912 | |a GBV_ILN_2014 | ||
912 | |a GBV_ILN_4012 | ||
912 | |a GBV_ILN_4037 | ||
912 | |a GBV_ILN_4112 | ||
912 | |a GBV_ILN_4125 | ||
912 | |a GBV_ILN_4126 | ||
912 | |a GBV_ILN_4249 | ||
912 | |a GBV_ILN_4305 | ||
912 | |a GBV_ILN_4306 | ||
912 | |a GBV_ILN_4307 | ||
912 | |a GBV_ILN_4313 | ||
912 | |a GBV_ILN_4322 | ||
912 | |a GBV_ILN_4323 | ||
912 | |a GBV_ILN_4324 | ||
912 | |a GBV_ILN_4325 | ||
912 | |a GBV_ILN_4338 | ||
912 | |a GBV_ILN_4367 | ||
912 | |a GBV_ILN_4700 | ||
951 | |a AR | ||
952 | |d 13 |j 2023 |
author_variant |
x l xl y l yl m l ml j b jb d s ds c l cl |
---|---|
matchkey_str |
article:22352988:2023----::pdmooiaivsiainfoersiaoyrcifcindrnifunahnpm9iupneibs |
hierarchy_sort_str |
2023 |
callnumber-subject-code |
QR |
publishDate |
2023 |
allfields |
10.3389/fcimb.2023.1303456 doi (DE-627)DOAJ099256797 (DE-599)DOAJe2b06541efca4dd39be05fe2afecf96d DE-627 ger DE-627 rakwb eng QR1-502 Xiaodan Li verfasserin aut Epidemiological investigation of lower respiratory tract infections during influenza A (H1N1) pdm09 virus pandemic based on targeted next-generation sequencing 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier BackgroundCo-infection has been a significant contributor to morbidity and mortality in previous influenza pandemics. However, the current influenza A (H1N1) pdm09 virus pandemic, as the first major outbreak following the SARS-CoV-2 pandemic, may differ epidemiologically. Further investigation is necessary to understand the specific features and impact of this influenza A pandemic. Study design: We conducted a retrospective cohort study at a Chinese hospital between January and April 2023, focusing on patients with lower respiratory tract infections. Pathogen detection employed targeted next-generation sequencing (tNGS) on bronchoalveolar lavage fluid (BALF) or sputum samples.ResultsThis study enrolled 167 patients with lower respiratory tract infections, and the overall positivity rate detected through tNGS was around 80%. Among them, 40 patients had influenza A (H1N1) pdm09 virus infection, peaking in March. In these patients, 27.5% had sole infections, and 72.5% had co-infections, commonly with bacteria. The frequently detected pathogens were Aspergillus fumigatus, SARS-CoV-2, and Streptococcus pneumoniae. For non-influenza A virus-infected patients, the co-infection rate was 36.1%, with 42.3% having SARS-CoV-2. Patients with influenza A virus infection were younger, had more females and diabetes cases. Among them, those with sole infections were older, with less fever and asthma but more smoking history. Regarding prognosis, compared to sole influenza A virus infection, co-infected patients demonstrated higher 21-day recovery rates and a higher incidence of heart failure. However, they exhibited lower proportions of respiratory failure, acute kidney failure, septic shock, and hospital stays lasting more than 10 days. Interestingly, patients with non-influenza A virus infection had a significantly lower 21-day recovery rate. Correlation analysis indicated that the 21-day recovery rate was only associated with influenza A (H1N1) pdm09 virus.ConclusionDuring the current pandemic, the influenza A (H1N1) pdm09 virus may have been influenced by the SARS-CoV-2 pandemic and did not exhibit a strong pathogenicity. In fact, patients infected with influenza A virus showed better prognoses compared to those infected with other pathogens. Additionally, tNGS demonstrated excellent detection performance in this study and showed great potential, prompting clinical physicians to consider its use as an auxiliary diagnostic tool. influenza A (H1N1) pdm09 virus pandemic epidemiology targeted next-generation sequencing prognosis Microbiology Yang Liu verfasserin aut Minzhe Li verfasserin aut Jing Bian verfasserin aut Demei Song verfasserin aut Chaoying Liu verfasserin aut In Frontiers in Cellular and Infection Microbiology Frontiers Media S.A., 2016 13(2023) (DE-627)664968554 (DE-600)2619676-1 22352988 nnns volume:13 year:2023 https://doi.org/10.3389/fcimb.2023.1303456 kostenfrei https://doaj.org/article/e2b06541efca4dd39be05fe2afecf96d kostenfrei https://www.frontiersin.org/articles/10.3389/fcimb.2023.1303456/full kostenfrei https://doaj.org/toc/2235-2988 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2023 |
spelling |
10.3389/fcimb.2023.1303456 doi (DE-627)DOAJ099256797 (DE-599)DOAJe2b06541efca4dd39be05fe2afecf96d DE-627 ger DE-627 rakwb eng QR1-502 Xiaodan Li verfasserin aut Epidemiological investigation of lower respiratory tract infections during influenza A (H1N1) pdm09 virus pandemic based on targeted next-generation sequencing 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier BackgroundCo-infection has been a significant contributor to morbidity and mortality in previous influenza pandemics. However, the current influenza A (H1N1) pdm09 virus pandemic, as the first major outbreak following the SARS-CoV-2 pandemic, may differ epidemiologically. Further investigation is necessary to understand the specific features and impact of this influenza A pandemic. Study design: We conducted a retrospective cohort study at a Chinese hospital between January and April 2023, focusing on patients with lower respiratory tract infections. Pathogen detection employed targeted next-generation sequencing (tNGS) on bronchoalveolar lavage fluid (BALF) or sputum samples.ResultsThis study enrolled 167 patients with lower respiratory tract infections, and the overall positivity rate detected through tNGS was around 80%. Among them, 40 patients had influenza A (H1N1) pdm09 virus infection, peaking in March. In these patients, 27.5% had sole infections, and 72.5% had co-infections, commonly with bacteria. The frequently detected pathogens were Aspergillus fumigatus, SARS-CoV-2, and Streptococcus pneumoniae. For non-influenza A virus-infected patients, the co-infection rate was 36.1%, with 42.3% having SARS-CoV-2. Patients with influenza A virus infection were younger, had more females and diabetes cases. Among them, those with sole infections were older, with less fever and asthma but more smoking history. Regarding prognosis, compared to sole influenza A virus infection, co-infected patients demonstrated higher 21-day recovery rates and a higher incidence of heart failure. However, they exhibited lower proportions of respiratory failure, acute kidney failure, septic shock, and hospital stays lasting more than 10 days. Interestingly, patients with non-influenza A virus infection had a significantly lower 21-day recovery rate. Correlation analysis indicated that the 21-day recovery rate was only associated with influenza A (H1N1) pdm09 virus.ConclusionDuring the current pandemic, the influenza A (H1N1) pdm09 virus may have been influenced by the SARS-CoV-2 pandemic and did not exhibit a strong pathogenicity. In fact, patients infected with influenza A virus showed better prognoses compared to those infected with other pathogens. Additionally, tNGS demonstrated excellent detection performance in this study and showed great potential, prompting clinical physicians to consider its use as an auxiliary diagnostic tool. influenza A (H1N1) pdm09 virus pandemic epidemiology targeted next-generation sequencing prognosis Microbiology Yang Liu verfasserin aut Minzhe Li verfasserin aut Jing Bian verfasserin aut Demei Song verfasserin aut Chaoying Liu verfasserin aut In Frontiers in Cellular and Infection Microbiology Frontiers Media S.A., 2016 13(2023) (DE-627)664968554 (DE-600)2619676-1 22352988 nnns volume:13 year:2023 https://doi.org/10.3389/fcimb.2023.1303456 kostenfrei https://doaj.org/article/e2b06541efca4dd39be05fe2afecf96d kostenfrei https://www.frontiersin.org/articles/10.3389/fcimb.2023.1303456/full kostenfrei https://doaj.org/toc/2235-2988 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2023 |
allfields_unstemmed |
10.3389/fcimb.2023.1303456 doi (DE-627)DOAJ099256797 (DE-599)DOAJe2b06541efca4dd39be05fe2afecf96d DE-627 ger DE-627 rakwb eng QR1-502 Xiaodan Li verfasserin aut Epidemiological investigation of lower respiratory tract infections during influenza A (H1N1) pdm09 virus pandemic based on targeted next-generation sequencing 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier BackgroundCo-infection has been a significant contributor to morbidity and mortality in previous influenza pandemics. However, the current influenza A (H1N1) pdm09 virus pandemic, as the first major outbreak following the SARS-CoV-2 pandemic, may differ epidemiologically. Further investigation is necessary to understand the specific features and impact of this influenza A pandemic. Study design: We conducted a retrospective cohort study at a Chinese hospital between January and April 2023, focusing on patients with lower respiratory tract infections. Pathogen detection employed targeted next-generation sequencing (tNGS) on bronchoalveolar lavage fluid (BALF) or sputum samples.ResultsThis study enrolled 167 patients with lower respiratory tract infections, and the overall positivity rate detected through tNGS was around 80%. Among them, 40 patients had influenza A (H1N1) pdm09 virus infection, peaking in March. In these patients, 27.5% had sole infections, and 72.5% had co-infections, commonly with bacteria. The frequently detected pathogens were Aspergillus fumigatus, SARS-CoV-2, and Streptococcus pneumoniae. For non-influenza A virus-infected patients, the co-infection rate was 36.1%, with 42.3% having SARS-CoV-2. Patients with influenza A virus infection were younger, had more females and diabetes cases. Among them, those with sole infections were older, with less fever and asthma but more smoking history. Regarding prognosis, compared to sole influenza A virus infection, co-infected patients demonstrated higher 21-day recovery rates and a higher incidence of heart failure. However, they exhibited lower proportions of respiratory failure, acute kidney failure, septic shock, and hospital stays lasting more than 10 days. Interestingly, patients with non-influenza A virus infection had a significantly lower 21-day recovery rate. Correlation analysis indicated that the 21-day recovery rate was only associated with influenza A (H1N1) pdm09 virus.ConclusionDuring the current pandemic, the influenza A (H1N1) pdm09 virus may have been influenced by the SARS-CoV-2 pandemic and did not exhibit a strong pathogenicity. In fact, patients infected with influenza A virus showed better prognoses compared to those infected with other pathogens. Additionally, tNGS demonstrated excellent detection performance in this study and showed great potential, prompting clinical physicians to consider its use as an auxiliary diagnostic tool. influenza A (H1N1) pdm09 virus pandemic epidemiology targeted next-generation sequencing prognosis Microbiology Yang Liu verfasserin aut Minzhe Li verfasserin aut Jing Bian verfasserin aut Demei Song verfasserin aut Chaoying Liu verfasserin aut In Frontiers in Cellular and Infection Microbiology Frontiers Media S.A., 2016 13(2023) (DE-627)664968554 (DE-600)2619676-1 22352988 nnns volume:13 year:2023 https://doi.org/10.3389/fcimb.2023.1303456 kostenfrei https://doaj.org/article/e2b06541efca4dd39be05fe2afecf96d kostenfrei https://www.frontiersin.org/articles/10.3389/fcimb.2023.1303456/full kostenfrei https://doaj.org/toc/2235-2988 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2023 |
allfieldsGer |
10.3389/fcimb.2023.1303456 doi (DE-627)DOAJ099256797 (DE-599)DOAJe2b06541efca4dd39be05fe2afecf96d DE-627 ger DE-627 rakwb eng QR1-502 Xiaodan Li verfasserin aut Epidemiological investigation of lower respiratory tract infections during influenza A (H1N1) pdm09 virus pandemic based on targeted next-generation sequencing 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier BackgroundCo-infection has been a significant contributor to morbidity and mortality in previous influenza pandemics. However, the current influenza A (H1N1) pdm09 virus pandemic, as the first major outbreak following the SARS-CoV-2 pandemic, may differ epidemiologically. Further investigation is necessary to understand the specific features and impact of this influenza A pandemic. Study design: We conducted a retrospective cohort study at a Chinese hospital between January and April 2023, focusing on patients with lower respiratory tract infections. Pathogen detection employed targeted next-generation sequencing (tNGS) on bronchoalveolar lavage fluid (BALF) or sputum samples.ResultsThis study enrolled 167 patients with lower respiratory tract infections, and the overall positivity rate detected through tNGS was around 80%. Among them, 40 patients had influenza A (H1N1) pdm09 virus infection, peaking in March. In these patients, 27.5% had sole infections, and 72.5% had co-infections, commonly with bacteria. The frequently detected pathogens were Aspergillus fumigatus, SARS-CoV-2, and Streptococcus pneumoniae. For non-influenza A virus-infected patients, the co-infection rate was 36.1%, with 42.3% having SARS-CoV-2. Patients with influenza A virus infection were younger, had more females and diabetes cases. Among them, those with sole infections were older, with less fever and asthma but more smoking history. Regarding prognosis, compared to sole influenza A virus infection, co-infected patients demonstrated higher 21-day recovery rates and a higher incidence of heart failure. However, they exhibited lower proportions of respiratory failure, acute kidney failure, septic shock, and hospital stays lasting more than 10 days. Interestingly, patients with non-influenza A virus infection had a significantly lower 21-day recovery rate. Correlation analysis indicated that the 21-day recovery rate was only associated with influenza A (H1N1) pdm09 virus.ConclusionDuring the current pandemic, the influenza A (H1N1) pdm09 virus may have been influenced by the SARS-CoV-2 pandemic and did not exhibit a strong pathogenicity. In fact, patients infected with influenza A virus showed better prognoses compared to those infected with other pathogens. Additionally, tNGS demonstrated excellent detection performance in this study and showed great potential, prompting clinical physicians to consider its use as an auxiliary diagnostic tool. influenza A (H1N1) pdm09 virus pandemic epidemiology targeted next-generation sequencing prognosis Microbiology Yang Liu verfasserin aut Minzhe Li verfasserin aut Jing Bian verfasserin aut Demei Song verfasserin aut Chaoying Liu verfasserin aut In Frontiers in Cellular and Infection Microbiology Frontiers Media S.A., 2016 13(2023) (DE-627)664968554 (DE-600)2619676-1 22352988 nnns volume:13 year:2023 https://doi.org/10.3389/fcimb.2023.1303456 kostenfrei https://doaj.org/article/e2b06541efca4dd39be05fe2afecf96d kostenfrei https://www.frontiersin.org/articles/10.3389/fcimb.2023.1303456/full kostenfrei https://doaj.org/toc/2235-2988 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2023 |
allfieldsSound |
10.3389/fcimb.2023.1303456 doi (DE-627)DOAJ099256797 (DE-599)DOAJe2b06541efca4dd39be05fe2afecf96d DE-627 ger DE-627 rakwb eng QR1-502 Xiaodan Li verfasserin aut Epidemiological investigation of lower respiratory tract infections during influenza A (H1N1) pdm09 virus pandemic based on targeted next-generation sequencing 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier BackgroundCo-infection has been a significant contributor to morbidity and mortality in previous influenza pandemics. However, the current influenza A (H1N1) pdm09 virus pandemic, as the first major outbreak following the SARS-CoV-2 pandemic, may differ epidemiologically. Further investigation is necessary to understand the specific features and impact of this influenza A pandemic. Study design: We conducted a retrospective cohort study at a Chinese hospital between January and April 2023, focusing on patients with lower respiratory tract infections. Pathogen detection employed targeted next-generation sequencing (tNGS) on bronchoalveolar lavage fluid (BALF) or sputum samples.ResultsThis study enrolled 167 patients with lower respiratory tract infections, and the overall positivity rate detected through tNGS was around 80%. Among them, 40 patients had influenza A (H1N1) pdm09 virus infection, peaking in March. In these patients, 27.5% had sole infections, and 72.5% had co-infections, commonly with bacteria. The frequently detected pathogens were Aspergillus fumigatus, SARS-CoV-2, and Streptococcus pneumoniae. For non-influenza A virus-infected patients, the co-infection rate was 36.1%, with 42.3% having SARS-CoV-2. Patients with influenza A virus infection were younger, had more females and diabetes cases. Among them, those with sole infections were older, with less fever and asthma but more smoking history. Regarding prognosis, compared to sole influenza A virus infection, co-infected patients demonstrated higher 21-day recovery rates and a higher incidence of heart failure. However, they exhibited lower proportions of respiratory failure, acute kidney failure, septic shock, and hospital stays lasting more than 10 days. Interestingly, patients with non-influenza A virus infection had a significantly lower 21-day recovery rate. Correlation analysis indicated that the 21-day recovery rate was only associated with influenza A (H1N1) pdm09 virus.ConclusionDuring the current pandemic, the influenza A (H1N1) pdm09 virus may have been influenced by the SARS-CoV-2 pandemic and did not exhibit a strong pathogenicity. In fact, patients infected with influenza A virus showed better prognoses compared to those infected with other pathogens. Additionally, tNGS demonstrated excellent detection performance in this study and showed great potential, prompting clinical physicians to consider its use as an auxiliary diagnostic tool. influenza A (H1N1) pdm09 virus pandemic epidemiology targeted next-generation sequencing prognosis Microbiology Yang Liu verfasserin aut Minzhe Li verfasserin aut Jing Bian verfasserin aut Demei Song verfasserin aut Chaoying Liu verfasserin aut In Frontiers in Cellular and Infection Microbiology Frontiers Media S.A., 2016 13(2023) (DE-627)664968554 (DE-600)2619676-1 22352988 nnns volume:13 year:2023 https://doi.org/10.3389/fcimb.2023.1303456 kostenfrei https://doaj.org/article/e2b06541efca4dd39be05fe2afecf96d kostenfrei https://www.frontiersin.org/articles/10.3389/fcimb.2023.1303456/full kostenfrei https://doaj.org/toc/2235-2988 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2023 |
language |
English |
source |
In Frontiers in Cellular and Infection Microbiology 13(2023) volume:13 year:2023 |
sourceStr |
In Frontiers in Cellular and Infection Microbiology 13(2023) volume:13 year:2023 |
format_phy_str_mv |
Article |
institution |
findex.gbv.de |
topic_facet |
influenza A (H1N1) pdm09 virus pandemic epidemiology targeted next-generation sequencing prognosis Microbiology |
isfreeaccess_bool |
true |
container_title |
Frontiers in Cellular and Infection Microbiology |
authorswithroles_txt_mv |
Xiaodan Li @@aut@@ Yang Liu @@aut@@ Minzhe Li @@aut@@ Jing Bian @@aut@@ Demei Song @@aut@@ Chaoying Liu @@aut@@ |
publishDateDaySort_date |
2023-01-01T00:00:00Z |
hierarchy_top_id |
664968554 |
id |
DOAJ099256797 |
language_de |
englisch |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">DOAJ099256797</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240414022539.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240414s2023 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3389/fcimb.2023.1303456</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ099256797</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJe2b06541efca4dd39be05fe2afecf96d</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">QR1-502</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Xiaodan Li</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Epidemiological investigation of lower respiratory tract infections during influenza A (H1N1) pdm09 virus pandemic based on targeted next-generation sequencing</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">BackgroundCo-infection has been a significant contributor to morbidity and mortality in previous influenza pandemics. However, the current influenza A (H1N1) pdm09 virus pandemic, as the first major outbreak following the SARS-CoV-2 pandemic, may differ epidemiologically. Further investigation is necessary to understand the specific features and impact of this influenza A pandemic. Study design: We conducted a retrospective cohort study at a Chinese hospital between January and April 2023, focusing on patients with lower respiratory tract infections. Pathogen detection employed targeted next-generation sequencing (tNGS) on bronchoalveolar lavage fluid (BALF) or sputum samples.ResultsThis study enrolled 167 patients with lower respiratory tract infections, and the overall positivity rate detected through tNGS was around 80%. Among them, 40 patients had influenza A (H1N1) pdm09 virus infection, peaking in March. In these patients, 27.5% had sole infections, and 72.5% had co-infections, commonly with bacteria. The frequently detected pathogens were Aspergillus fumigatus, SARS-CoV-2, and Streptococcus pneumoniae. For non-influenza A virus-infected patients, the co-infection rate was 36.1%, with 42.3% having SARS-CoV-2. Patients with influenza A virus infection were younger, had more females and diabetes cases. Among them, those with sole infections were older, with less fever and asthma but more smoking history. Regarding prognosis, compared to sole influenza A virus infection, co-infected patients demonstrated higher 21-day recovery rates and a higher incidence of heart failure. However, they exhibited lower proportions of respiratory failure, acute kidney failure, septic shock, and hospital stays lasting more than 10 days. Interestingly, patients with non-influenza A virus infection had a significantly lower 21-day recovery rate. Correlation analysis indicated that the 21-day recovery rate was only associated with influenza A (H1N1) pdm09 virus.ConclusionDuring the current pandemic, the influenza A (H1N1) pdm09 virus may have been influenced by the SARS-CoV-2 pandemic and did not exhibit a strong pathogenicity. In fact, patients infected with influenza A virus showed better prognoses compared to those infected with other pathogens. Additionally, tNGS demonstrated excellent detection performance in this study and showed great potential, prompting clinical physicians to consider its use as an auxiliary diagnostic tool.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">influenza A (H1N1) pdm09 virus</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">pandemic</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">epidemiology</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">targeted next-generation sequencing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">prognosis</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Microbiology</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Yang Liu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Minzhe Li</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Jing Bian</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Demei Song</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Chaoying Liu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Frontiers in Cellular and Infection Microbiology</subfield><subfield code="d">Frontiers Media S.A., 2016</subfield><subfield code="g">13(2023)</subfield><subfield code="w">(DE-627)664968554</subfield><subfield code="w">(DE-600)2619676-1</subfield><subfield code="x">22352988</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:13</subfield><subfield code="g">year:2023</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.3389/fcimb.2023.1303456</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/e2b06541efca4dd39be05fe2afecf96d</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.frontiersin.org/articles/10.3389/fcimb.2023.1303456/full</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2235-2988</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_206</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">13</subfield><subfield code="j">2023</subfield></datafield></record></collection>
|
callnumber-first |
Q - Science |
author |
Xiaodan Li |
spellingShingle |
Xiaodan Li misc QR1-502 misc influenza A (H1N1) pdm09 virus misc pandemic misc epidemiology misc targeted next-generation sequencing misc prognosis misc Microbiology Epidemiological investigation of lower respiratory tract infections during influenza A (H1N1) pdm09 virus pandemic based on targeted next-generation sequencing |
authorStr |
Xiaodan Li |
ppnlink_with_tag_str_mv |
@@773@@(DE-627)664968554 |
format |
electronic Article |
delete_txt_mv |
keep |
author_role |
aut aut aut aut aut aut |
collection |
DOAJ |
remote_str |
true |
callnumber-label |
QR1-502 |
illustrated |
Not Illustrated |
issn |
22352988 |
topic_title |
QR1-502 Epidemiological investigation of lower respiratory tract infections during influenza A (H1N1) pdm09 virus pandemic based on targeted next-generation sequencing influenza A (H1N1) pdm09 virus pandemic epidemiology targeted next-generation sequencing prognosis |
topic |
misc QR1-502 misc influenza A (H1N1) pdm09 virus misc pandemic misc epidemiology misc targeted next-generation sequencing misc prognosis misc Microbiology |
topic_unstemmed |
misc QR1-502 misc influenza A (H1N1) pdm09 virus misc pandemic misc epidemiology misc targeted next-generation sequencing misc prognosis misc Microbiology |
topic_browse |
misc QR1-502 misc influenza A (H1N1) pdm09 virus misc pandemic misc epidemiology misc targeted next-generation sequencing misc prognosis misc Microbiology |
format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
format_main_str_mv |
Text Zeitschrift/Artikel |
carriertype_str_mv |
cr |
hierarchy_parent_title |
Frontiers in Cellular and Infection Microbiology |
hierarchy_parent_id |
664968554 |
hierarchy_top_title |
Frontiers in Cellular and Infection Microbiology |
isfreeaccess_txt |
true |
familylinks_str_mv |
(DE-627)664968554 (DE-600)2619676-1 |
title |
Epidemiological investigation of lower respiratory tract infections during influenza A (H1N1) pdm09 virus pandemic based on targeted next-generation sequencing |
ctrlnum |
(DE-627)DOAJ099256797 (DE-599)DOAJe2b06541efca4dd39be05fe2afecf96d |
title_full |
Epidemiological investigation of lower respiratory tract infections during influenza A (H1N1) pdm09 virus pandemic based on targeted next-generation sequencing |
author_sort |
Xiaodan Li |
journal |
Frontiers in Cellular and Infection Microbiology |
journalStr |
Frontiers in Cellular and Infection Microbiology |
callnumber-first-code |
Q |
lang_code |
eng |
isOA_bool |
true |
recordtype |
marc |
publishDateSort |
2023 |
contenttype_str_mv |
txt |
author_browse |
Xiaodan Li Yang Liu Minzhe Li Jing Bian Demei Song Chaoying Liu |
container_volume |
13 |
class |
QR1-502 |
format_se |
Elektronische Aufsätze |
author-letter |
Xiaodan Li |
doi_str_mv |
10.3389/fcimb.2023.1303456 |
author2-role |
verfasserin |
title_sort |
epidemiological investigation of lower respiratory tract infections during influenza a (h1n1) pdm09 virus pandemic based on targeted next-generation sequencing |
callnumber |
QR1-502 |
title_auth |
Epidemiological investigation of lower respiratory tract infections during influenza A (H1N1) pdm09 virus pandemic based on targeted next-generation sequencing |
abstract |
BackgroundCo-infection has been a significant contributor to morbidity and mortality in previous influenza pandemics. However, the current influenza A (H1N1) pdm09 virus pandemic, as the first major outbreak following the SARS-CoV-2 pandemic, may differ epidemiologically. Further investigation is necessary to understand the specific features and impact of this influenza A pandemic. Study design: We conducted a retrospective cohort study at a Chinese hospital between January and April 2023, focusing on patients with lower respiratory tract infections. Pathogen detection employed targeted next-generation sequencing (tNGS) on bronchoalveolar lavage fluid (BALF) or sputum samples.ResultsThis study enrolled 167 patients with lower respiratory tract infections, and the overall positivity rate detected through tNGS was around 80%. Among them, 40 patients had influenza A (H1N1) pdm09 virus infection, peaking in March. In these patients, 27.5% had sole infections, and 72.5% had co-infections, commonly with bacteria. The frequently detected pathogens were Aspergillus fumigatus, SARS-CoV-2, and Streptococcus pneumoniae. For non-influenza A virus-infected patients, the co-infection rate was 36.1%, with 42.3% having SARS-CoV-2. Patients with influenza A virus infection were younger, had more females and diabetes cases. Among them, those with sole infections were older, with less fever and asthma but more smoking history. Regarding prognosis, compared to sole influenza A virus infection, co-infected patients demonstrated higher 21-day recovery rates and a higher incidence of heart failure. However, they exhibited lower proportions of respiratory failure, acute kidney failure, septic shock, and hospital stays lasting more than 10 days. Interestingly, patients with non-influenza A virus infection had a significantly lower 21-day recovery rate. Correlation analysis indicated that the 21-day recovery rate was only associated with influenza A (H1N1) pdm09 virus.ConclusionDuring the current pandemic, the influenza A (H1N1) pdm09 virus may have been influenced by the SARS-CoV-2 pandemic and did not exhibit a strong pathogenicity. In fact, patients infected with influenza A virus showed better prognoses compared to those infected with other pathogens. Additionally, tNGS demonstrated excellent detection performance in this study and showed great potential, prompting clinical physicians to consider its use as an auxiliary diagnostic tool. |
abstractGer |
BackgroundCo-infection has been a significant contributor to morbidity and mortality in previous influenza pandemics. However, the current influenza A (H1N1) pdm09 virus pandemic, as the first major outbreak following the SARS-CoV-2 pandemic, may differ epidemiologically. Further investigation is necessary to understand the specific features and impact of this influenza A pandemic. Study design: We conducted a retrospective cohort study at a Chinese hospital between January and April 2023, focusing on patients with lower respiratory tract infections. Pathogen detection employed targeted next-generation sequencing (tNGS) on bronchoalveolar lavage fluid (BALF) or sputum samples.ResultsThis study enrolled 167 patients with lower respiratory tract infections, and the overall positivity rate detected through tNGS was around 80%. Among them, 40 patients had influenza A (H1N1) pdm09 virus infection, peaking in March. In these patients, 27.5% had sole infections, and 72.5% had co-infections, commonly with bacteria. The frequently detected pathogens were Aspergillus fumigatus, SARS-CoV-2, and Streptococcus pneumoniae. For non-influenza A virus-infected patients, the co-infection rate was 36.1%, with 42.3% having SARS-CoV-2. Patients with influenza A virus infection were younger, had more females and diabetes cases. Among them, those with sole infections were older, with less fever and asthma but more smoking history. Regarding prognosis, compared to sole influenza A virus infection, co-infected patients demonstrated higher 21-day recovery rates and a higher incidence of heart failure. However, they exhibited lower proportions of respiratory failure, acute kidney failure, septic shock, and hospital stays lasting more than 10 days. Interestingly, patients with non-influenza A virus infection had a significantly lower 21-day recovery rate. Correlation analysis indicated that the 21-day recovery rate was only associated with influenza A (H1N1) pdm09 virus.ConclusionDuring the current pandemic, the influenza A (H1N1) pdm09 virus may have been influenced by the SARS-CoV-2 pandemic and did not exhibit a strong pathogenicity. In fact, patients infected with influenza A virus showed better prognoses compared to those infected with other pathogens. Additionally, tNGS demonstrated excellent detection performance in this study and showed great potential, prompting clinical physicians to consider its use as an auxiliary diagnostic tool. |
abstract_unstemmed |
BackgroundCo-infection has been a significant contributor to morbidity and mortality in previous influenza pandemics. However, the current influenza A (H1N1) pdm09 virus pandemic, as the first major outbreak following the SARS-CoV-2 pandemic, may differ epidemiologically. Further investigation is necessary to understand the specific features and impact of this influenza A pandemic. Study design: We conducted a retrospective cohort study at a Chinese hospital between January and April 2023, focusing on patients with lower respiratory tract infections. Pathogen detection employed targeted next-generation sequencing (tNGS) on bronchoalveolar lavage fluid (BALF) or sputum samples.ResultsThis study enrolled 167 patients with lower respiratory tract infections, and the overall positivity rate detected through tNGS was around 80%. Among them, 40 patients had influenza A (H1N1) pdm09 virus infection, peaking in March. In these patients, 27.5% had sole infections, and 72.5% had co-infections, commonly with bacteria. The frequently detected pathogens were Aspergillus fumigatus, SARS-CoV-2, and Streptococcus pneumoniae. For non-influenza A virus-infected patients, the co-infection rate was 36.1%, with 42.3% having SARS-CoV-2. Patients with influenza A virus infection were younger, had more females and diabetes cases. Among them, those with sole infections were older, with less fever and asthma but more smoking history. Regarding prognosis, compared to sole influenza A virus infection, co-infected patients demonstrated higher 21-day recovery rates and a higher incidence of heart failure. However, they exhibited lower proportions of respiratory failure, acute kidney failure, septic shock, and hospital stays lasting more than 10 days. Interestingly, patients with non-influenza A virus infection had a significantly lower 21-day recovery rate. Correlation analysis indicated that the 21-day recovery rate was only associated with influenza A (H1N1) pdm09 virus.ConclusionDuring the current pandemic, the influenza A (H1N1) pdm09 virus may have been influenced by the SARS-CoV-2 pandemic and did not exhibit a strong pathogenicity. In fact, patients infected with influenza A virus showed better prognoses compared to those infected with other pathogens. Additionally, tNGS demonstrated excellent detection performance in this study and showed great potential, prompting clinical physicians to consider its use as an auxiliary diagnostic tool. |
collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 |
title_short |
Epidemiological investigation of lower respiratory tract infections during influenza A (H1N1) pdm09 virus pandemic based on targeted next-generation sequencing |
url |
https://doi.org/10.3389/fcimb.2023.1303456 https://doaj.org/article/e2b06541efca4dd39be05fe2afecf96d https://www.frontiersin.org/articles/10.3389/fcimb.2023.1303456/full https://doaj.org/toc/2235-2988 |
remote_bool |
true |
author2 |
Yang Liu Minzhe Li Jing Bian Demei Song Chaoying Liu |
author2Str |
Yang Liu Minzhe Li Jing Bian Demei Song Chaoying Liu |
ppnlink |
664968554 |
callnumber-subject |
QR - Microbiology |
mediatype_str_mv |
c |
isOA_txt |
true |
hochschulschrift_bool |
false |
doi_str |
10.3389/fcimb.2023.1303456 |
callnumber-a |
QR1-502 |
up_date |
2024-07-03T21:53:26.397Z |
_version_ |
1803596444627632129 |
fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">DOAJ099256797</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240414022539.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240414s2023 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3389/fcimb.2023.1303456</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ099256797</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJe2b06541efca4dd39be05fe2afecf96d</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">QR1-502</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Xiaodan Li</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Epidemiological investigation of lower respiratory tract infections during influenza A (H1N1) pdm09 virus pandemic based on targeted next-generation sequencing</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">BackgroundCo-infection has been a significant contributor to morbidity and mortality in previous influenza pandemics. However, the current influenza A (H1N1) pdm09 virus pandemic, as the first major outbreak following the SARS-CoV-2 pandemic, may differ epidemiologically. Further investigation is necessary to understand the specific features and impact of this influenza A pandemic. Study design: We conducted a retrospective cohort study at a Chinese hospital between January and April 2023, focusing on patients with lower respiratory tract infections. Pathogen detection employed targeted next-generation sequencing (tNGS) on bronchoalveolar lavage fluid (BALF) or sputum samples.ResultsThis study enrolled 167 patients with lower respiratory tract infections, and the overall positivity rate detected through tNGS was around 80%. Among them, 40 patients had influenza A (H1N1) pdm09 virus infection, peaking in March. In these patients, 27.5% had sole infections, and 72.5% had co-infections, commonly with bacteria. The frequently detected pathogens were Aspergillus fumigatus, SARS-CoV-2, and Streptococcus pneumoniae. For non-influenza A virus-infected patients, the co-infection rate was 36.1%, with 42.3% having SARS-CoV-2. Patients with influenza A virus infection were younger, had more females and diabetes cases. Among them, those with sole infections were older, with less fever and asthma but more smoking history. Regarding prognosis, compared to sole influenza A virus infection, co-infected patients demonstrated higher 21-day recovery rates and a higher incidence of heart failure. However, they exhibited lower proportions of respiratory failure, acute kidney failure, septic shock, and hospital stays lasting more than 10 days. Interestingly, patients with non-influenza A virus infection had a significantly lower 21-day recovery rate. Correlation analysis indicated that the 21-day recovery rate was only associated with influenza A (H1N1) pdm09 virus.ConclusionDuring the current pandemic, the influenza A (H1N1) pdm09 virus may have been influenced by the SARS-CoV-2 pandemic and did not exhibit a strong pathogenicity. In fact, patients infected with influenza A virus showed better prognoses compared to those infected with other pathogens. Additionally, tNGS demonstrated excellent detection performance in this study and showed great potential, prompting clinical physicians to consider its use as an auxiliary diagnostic tool.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">influenza A (H1N1) pdm09 virus</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">pandemic</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">epidemiology</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">targeted next-generation sequencing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">prognosis</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Microbiology</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Yang Liu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Minzhe Li</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Jing Bian</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Demei Song</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Chaoying Liu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Frontiers in Cellular and Infection Microbiology</subfield><subfield code="d">Frontiers Media S.A., 2016</subfield><subfield code="g">13(2023)</subfield><subfield code="w">(DE-627)664968554</subfield><subfield code="w">(DE-600)2619676-1</subfield><subfield code="x">22352988</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:13</subfield><subfield code="g">year:2023</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.3389/fcimb.2023.1303456</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/e2b06541efca4dd39be05fe2afecf96d</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.frontiersin.org/articles/10.3389/fcimb.2023.1303456/full</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2235-2988</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_206</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">13</subfield><subfield code="j">2023</subfield></datafield></record></collection>
|
score |
7.399357 |