• Türkçe
    • English
  • English 
    • Türkçe
    • English
  • Login
View Item 
  •   RTEÜ
  • Araştırma Çıktıları | TR-Dizin | WoS | Scopus | PubMed
  • WoS İndeksli Yayınlar Koleksiyonu
  • View Item
  •   RTEÜ
  • Araştırma Çıktıları | TR-Dizin | WoS | Scopus | PubMed
  • WoS İndeksli Yayınlar Koleksiyonu
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Predicting mechanical ventilation, intensive care unit admission, and mortality in COVID-19 patients: Comparison of seven different scoring systems

View/Open

Tam Metin / Full Text (388.0Kb)

Access

info:eu-repo/semantics/openAccess

Date

2024

Author

İlgar, Tuba
Çolak, Sudem Mahmutoğlu
Akyüz, Kübra
Odabaş, Gülsün Çakır
Koç, Süleyman
Özşahin, Aybegüm
Telatar, Ayça
Yavaşi, Özcan

Metadata

Show full item record

Citation

İlgar, T., Çolak, S.M., Akyüz, K. (2024). Predicting Mechanical Ventilation, Intensive Care Unit Admission, and Mortality in COVID-19 Patients: Comparison of Seven Different Scoring Systems. Türk Yoğun Bakım Dergisi, 22(2), 116-121. http://doi.org/10.4274/tybd.galenos.2023.09327

Abstract

Objective: In this study, we investigated whether scoring systems determine coronavirus disease-2019 (COVID-19) severity. Materials and Methods: COVID-19 patients hospitalized between 01.09.2020 and 31.04.2021 were retrospectively assessed. The national early warning score (NEWS), modified early warning score, rapid emergency medicine score, quick sequential organ failure assessment score (q-SOFA), CURB65, MuLBSTA, and ISARIC-4C scores on admission day were calculated. Scoring systems' ability to predict mechanical ventilation (MV) need, intensive care unit (ICU) admission, and 30-day mortality were assessed. Results: A total of 292 patients were included; 137 (46.9%) were female, and the mean age was 62.5 +/- 15.4 years. 69 (23.6%) patients required ICU admission, 45 (15.4%) needed MV, and 49 (16.8%) died within 30 days. No relationship was found between q-SOFA and MV need (p=0.167), but a statistically significant relationship was found between other scoring systems and MV need, ICU admission, and 30-day mortality (p<0.05). ISARIC-4C (optimal cut-off >5.5) and NEWS (optimal cut-off >3.5) had the highest area under the curve in receiver operating characteristic curve analyses, whereas q-SOFA had the lowest. Conclusion: The severity of COVID-19 could be estimated by using these scoring systems, especially ISARIC-4C and NEWS, at the first admission. Thus, mortality and morbidity would be reduced by making the necessary interventions earlier. Keywords: COVID-19, ISARIC-4C, mortality, NEWS, scoring systems

Source

Turkish Journal of Intensive Care

Volume

22

Issue

2

URI

http://doi.org/10.4274/tybd.galenos.2023.09327
https://hdl.handle.net/11436/9206

Collections

  • TF, Cerrahi Tıp Bilimleri Bölümü Koleksiyonu [1216]
  • TF, Dahili Tıp Bilimleri Bölümü Koleksiyonu [1559]
  • WoS İndeksli Yayınlar Koleksiyonu [5260]



DSpace software copyright © 2002-2015  DuraSpace
Contact Us | Send Feedback
Theme by 
@mire NV
 

 




| Instruction | Guide | Contact |

DSpace@RTEÜ

by OpenAIRE
Advanced Search

sherpa/romeo

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsTypeLanguageDepartmentCategoryPublisherAccess TypeInstitution AuthorThis CollectionBy Issue DateAuthorsTitlesSubjectsTypeLanguageDepartmentCategoryPublisherAccess TypeInstitution Author

My Account

LoginRegister

Statistics

View Google Analytics Statistics

DSpace software copyright © 2002-2015  DuraSpace
Contact Us | Send Feedback
Theme by 
@mire NV
 

 


|| Guide|| Instruction || Library || Recep Tayyip Erdoğan University || OAI-PMH ||

Recep Tayyip Erdoğan University, Rize, Turkey
If you find any errors in content, please contact:

Creative Commons License
Recep Tayyip Erdoğan University Institutional Repository is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 Unported License..

DSpace@RTEÜ:


DSpace 6.2

tarafından İdeal DSpace hizmetleri çerçevesinde özelleştirilerek kurulmuştur.