Prediction of mortality in COVID-19 through combing CT severity score with NEWS, qSOFA, or peripheral perfusion index

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dc.authorid0000-0001-8034-0301en_US
dc.authorid0000-0003-0893-6084en_US
dc.authorid0000-0001-6829-7435en_US
dc.authorid0000-0002-3427-5649en_US
dc.authorid0000-0002-5093-7948en_US
dc.authorid0000-0003-3099-6876en_US
dc.authorid0000-0003-0325-886Xen_US
dc.authorid0000-0003-3996-7094en_US
dc.authorid0000-0002-2941-8879en_US
dc.authorid0000-0001-6247-2714en_US
dc.authorscopusid55554222600en_US
dc.authorscopusid57209690197en_US
dc.authorscopusid57203094225en_US
dc.authorscopusid57213614084en_US
dc.authorscopusid57218606079en_US
dc.authorscopusid23567874000en_US
dc.authorscopusid24921413500en_US
dc.authorscopusid49961223200en_US
dc.authorscopusid24179416400en_US
dc.authorscopusid56219360800en_US
dc.authorwosidAAZ-6502-2021en_US
dc.authorwosidGLR-3873-2022en_US
dc.authorwosidGXP-2477-2022en_US
dc.authorwosidCAV-3447-2022en_US
dc.authorwosidAAY-8678-2020en_US
dc.authorwosidA-1913-2019en_US
dc.authorwosidAAJ-6057-2021en_US
dc.authorwosidCPC-2993-2022en_US
dc.authorwosidKTI-7388-2024en_US
dc.authorwosidCGS-5191-2022en_US
dc.contributor.authorAkdur, Gökhan
dc.contributor.authorDaş, Murat
dc.contributor.authorBardakçı, Okan
dc.contributor.authorAkman, Canan
dc.contributor.authorSıddıkoğlu, Duygu
dc.contributor.authorAkdur, Okhan
dc.contributor.authorAkçalı, Alper
dc.contributor.authorErbaş, Mesut
dc.contributor.authorReşorlu, Mustafa
dc.contributor.authorBeyazıt, Yavuz
dc.date.accessioned2024-12-20T07:42:03Z
dc.date.available2024-12-20T07:42:03Z
dc.date.issued2021en_US
dc.departmentFakülteler, Tıp Fakültesi, Cerrahi Tıp Bilimleri Bölümü
dc.departmentFakülteler, Tıp Fakültesi, Dahili Tıp Bilimleri Bölümü
dc.departmentFakülteler, Tıp Fakültesi, Temel Tıp Bilimleri Bölümü
dc.description.abstractIntroduction: The assessment of disease severity and the prediction of clinical outcomes at early disease stages can contribute to decreased mortality in patients with Coronavirus disease 2019 (COVID-19). This study was conducted to develop and validate a multivariable risk prediction model for mortality with using a combination of computed tomography severity score (CT-SS), national early warning score (NEWS), and quick sequential (sepsis-related) organ failure assessment (qSOFA) in COVID-19 patients. Methods: We retrospectively collected medical data from 655 adult COVID-19 patients admitted to our hospital between July and November 2020. Data on demographics, clinical characteristics, and laboratory and radiological findings measured as part of standard care at admission were used to calculate NEWS, qSOFA score, CT-SS, peripheral perfusion index (PPI) and shock index (SI). Logistic regression and Cox proportional hazard models were used to predict mortality, which was our primary outcome. The predictive accuracy of distinct scoring systems was evaluated by the receiver-operating characteristic (ROC) curve analysis. Results: The median age was 50.0 years [333 males (50.8%), 322 females (49.2%)]. Higher NEWS and SI was associated with time-to-death within 90-days, whereas higher age, CT-SS and lower PPI were significantly associated with time-to-death within both 14 days and 90 days in the adjusted Cox regression model. The CT-SS predicted different mortality risk levels within each stratum of NEWS and qSOFA and improved the discrimination of mortality prediction models. Combining CT-SS with NEWS score yielded more accurate 14 days (DBA: −0.048, p = 0.002) and 90 days (DBA: −0.066, p < 0.001) mortality prediction. Conclusion: Combining severity tools such as CT-SS, NEWS and qSOFA improves the accuracy of predicting mortality in patients with COVID-19. Inclusion of these tools in decision strategies might provide early detection of high-risk groups, avoid delayed medical attention, and improve patient outcomes.en_US
dc.identifier.citationAkdur, G., Daş, M., Bardakçı, O., Akman, C., Sıddıkoğlu, D., Akdur, O., Akçalı, A., Erbaş, M., Reşorlu, M., & Beyazit, Y. (2021). Prediction of mortality in COVID-19 through combing CT severity score with NEWS, qSOFA, or peripheral perfusion index. The American Journal of Emergency Medicine, 50, 546–552. https://doi.org/10.1016/j.ajem.2021.08.079en_US
dc.identifier.doi10.1016/j.ajem.2021.08.079
dc.identifier.endpage552en_US
dc.identifier.issn0735-6757
dc.identifier.issn1532-8171
dc.identifier.pmid34547696
dc.identifier.scopus2-s2.0-85115057369
dc.identifier.startpage546en_US
dc.identifier.urihttps://doi.org/10.1016/j.ajem.2021.08.079
dc.identifier.urihttps://hdl.handle.net/20.500.12428/6769
dc.identifier.volume50en_US
dc.identifier.wosWOS:000703865900022
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.institutionauthorAkdur, Gökhan
dc.institutionauthorDaş, Murat
dc.institutionauthorBardakçı, Okan
dc.institutionauthorAkman, Canan
dc.institutionauthorSıddıkoğlu, Duygu
dc.institutionauthorAkdur, Okhan
dc.institutionauthorAkçalı, Alper
dc.institutionauthorErbaş, Mesut
dc.institutionauthorReşorlu, Mustafa
dc.institutionauthorBeyazıt, Yavuz
dc.language.isoen
dc.publisherW.B. Saundersen_US
dc.relation.ispartofAmerican Journal of Emergency Medicineen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectComputed tomographyen_US
dc.subjectCOVID-19en_US
dc.subjectEmergency medicineen_US
dc.subjectMortalityen_US
dc.titlePrediction of mortality in COVID-19 through combing CT severity score with NEWS, qSOFA, or peripheral perfusion index
dc.typeArticle

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