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Traditional Versus Intentionally Created Severity Scores for COVID-19 Prognosis

2026-05Artigo científico Acesso aberto
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dc.contributor.authorMarques, Daniela A.
dc.contributor.authorVon Rekowski, Cristiana P.
dc.contributor.authorCalado, Cecília R.C.
dc.contributor.authorBento, Luís
dc.contributor.authorPinto, Iola
dc.contributor.institutionNOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)
dc.contributor.institutionComprehensive Health Research Centre (CHRC) - pólo NMS
dc.contributor.institutionFaculdade de Ciências e Tecnologia (FCT)
dc.contributor.pblMDPI - Multidisciplinary Digital Publishing Institute
dc.date.accessioned2026-06-22T14:19:01Z
dc.date.available2026-06-22T14:19:01Z
dc.date.issued2026-05
dc.descriptionPublisher Copyright: © 2026 by the authors.
dc.description.abstractTraditional and COVID-19-specific severity scores are applied in intensive care units (ICUs) to guide decision-making and predict mortality. Since traditional severity scores (APACHE II, SAPS II, SAPS 3, and SOFA) were not originally designed for SARS-CoV-2, this study compared their performance with COVID-19–specific models (Shang-COVID and SEIMC), including a novel distinction between early (≤7 days) and late (>7 days) ICU mortality. Adult ICU COVID-19 patients from the first two pandemic waves in Portugal were included (n = 286). Six scores were calculated, and four outcomes assessed: hospital, ICU, early ICU, and late ICU mortality. Discrimination was assessed using ROC curves with AUCs, 95% CIs, and p-values. AUCs were compared using the Delong test (early vs. late ICU mortality and across scores within each wave) and the Hanley & McNeil test (between waves for each score). Traditional scores demonstrated robust mortality prediction. SEIMC performed well for hospital (AUCwave1 = 0.808; AUCwave2 = 0.724) and ICU mortality (AUCwave1 = 0.805; AUCwave2 = 0.706). SEIMC (AUCwave1 = 0.786; AUCwave2 = 0.800) and Shang-COVID (AUCwave1 = 0.617; AUCwave2 = 0.736) showed potential for early mortality prediction but require further validation and recalibration. Overall performance was superior during the first wave, likely reflecting differences in patient characteristics, viral variants, and health measures. Traditional severity scores demonstrated stable robust prediction of ICU and hospital mortality in COVID-19 cases. Disease-specific scores did not significantly outperform established models, though also showed good predictive ability in some contexts, particularly early ICU mortality. These findings highlight the need for continuous validation and recalibration of predictive tools as clinical contexts evolve.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent1435725
dc.identifier.doi10.3390/covid6050083
dc.identifier.issn2673-8112
dc.identifier.otherPURE: 164738069
dc.identifier.otherPURE UUID: 978deef7-aeeb-4594-baba-d09b3f021407
dc.identifier.otherScopus: 105040262933
dc.identifier.urihttp://hdl.handle.net/10362/204001
dc.identifier.urlhttps://www.scopus.com/pages/publications/105040262933
dc.language.isoeng
dc.peerreviewedyes
dc.subjectCOVID-19 waves
dc.subjectearly ICU mortality
dc.subjectICU severity scores
dc.subjectintensive care unit
dc.subjectlate ICU mortality
dc.subjectMedicine (miscellaneous)
dc.subjectImmunology and Microbiology (miscellaneous)
dc.subjectInfectious Diseases
dc.subjectSDG 3 - Good Health and Well-being
dc.titleTraditional Versus Intentionally Created Severity Scores for COVID-19 Prognosisen
dc.title.subtitleEvidence from a Portuguese Cohorten
dc.typejournal article
degois.publication.issue5
degois.publication.titleCOVID
degois.publication.volume6
dspace.entity.typePublication
rcaap.rightsopenAccess

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