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1000 Titel
  • The characteristics and predictive role of lymphocyte subsets in COVID-19 patients
1000 Autor/in
  1. Zhang, Wenjing |
  2. Li, Lei |
  3. Liu, Jihai |
  4. Chen, Li |
  5. Zhou, Fangfang |
  6. Jin, Ting |
  7. Jiang, Lin |
  8. Li, Xiang |
  9. Yang, Ming |
  10. Wang, Hongxiang |
1000 Erscheinungsjahr 2020
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2020-08-03
1000 Erschienen in
1000 Quellenangabe
  • 99:92-99
1000 Copyrightjahr
  • 2020
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1016/j.ijid.2020.06.079 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • OBJECTIVE: To investigate the characteristics and predictive roles of lymphocyte subsets in COVID-19 patients. METHOD: We evaluated lymphocyte subsets and other clinical features of COVID-19 patients, and analyzed their potential impacts on COVID-19 outcomes. RESULTS: 1. Lymphocyte subset counts in the peripheral blood of patients with COVID-19 were significantly reduced, especially in patients with severe disease. 2. In patients with non-severe disease, the time from symptom onset to hospital admission was positively correlated with total T cell counts. 3. Among COVID-19 patients who did not reach the composite endpoint, lymphocyte subset counts were higher than in patients who had reached the composite endpoint. 4. The Kaplan-Meier survival curves showed significant differences in COVID-19 patients, classified by the levels of total, CD8+, and CD4+ T cells at admission. CONCLUSION: Our study showed that total, CD8+, and CD4+ T cell counts in patients with COVID-19 were significantly reduced, especially in patients with severe disease. Lower T lymphocyte subsets were significantly associated with a higher occurrence of composite endpoint events. These subsets may help identify patients with a high risk of composite endpoint events.
1000 Sacherschließung
lokal Coronavirus disease 2019
gnd 1206347392 COVID-19
lokal Lymphocyte subsetsImmune parameters
lokal Pneumonia
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/WmhhbmcsIFdlbmppbmc=|https://frl.publisso.de/adhoc/uri/TGksIExlaQ==|https://frl.publisso.de/adhoc/uri/TGl1LCBKaWhhaQ==|https://frl.publisso.de/adhoc/uri/Q2hlbiwgTGk=|https://frl.publisso.de/adhoc/uri/WmhvdSwgRmFuZ2Zhbmc=|https://frl.publisso.de/adhoc/uri/SmluLCBUaW5n|https://frl.publisso.de/adhoc/uri/SmlhbmcsIExpbg==|https://frl.publisso.de/adhoc/uri/TGksIFhpYW5n|https://frl.publisso.de/adhoc/uri/WWFuZywgTWluZw==|https://frl.publisso.de/adhoc/uri/V2FuZywgSG9uZ3hpYW5n
1000 Label
1000 Förderer
  1. Wuhan Municipal Health Commission |
1000 Fördernummer
  1. WX17Q06
1000 Förderprogramm
  1. -
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Wuhan Municipal Health Commission |
    1000 Förderprogramm -
    1000 Fördernummer WX17Q06
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6424163.rdf
1000 Erstellt am 2020-11-11T08:13:41.528+0100
1000 Erstellt von 21
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1000 Bearbeitet von 218
1000 Zuletzt bearbeitet Fri Oct 01 16:55:15 CEST 2021
1000 Objekt bearb. Fri Oct 01 16:55:15 CEST 2021
1000 Vgl. frl:6424163
1000 Oai Id
  1. oai:frl.publisso.de:frl:6424163 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
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