Opin vísindi

Development of a prognostic model of COVID-19 severity : a population-based cohort study in Iceland

Development of a prognostic model of COVID-19 severity : a population-based cohort study in Iceland

Title: Development of a prognostic model of COVID-19 severity : a population-based cohort study in Iceland
Author: Eythorsson, Elias
Bjarnadottir, Valgerdur
Runólfsdóttir, Hrafnhildur L.
Helgason, Dadi   orcid.org/0000-0002-0162-366X
Ingvarsson, Ragnar Freyr
Björnsson, Helgi Kristinn
Ólafsdóttir, Lovísa Björk
Bjarnadottir, Solveig
Ágústsson, Arnar Snær
Oskarsdottir, Kristin
... 12 more authors Show all authors
Date: 2022-09-08
Language: English
Scope: 17
University/Institute: Landspitali - The National University Hospital of Iceland
Department: Internal Medicine and Emergency Services
Other departments
Faculty of Medicine
Perioperative Services
Clinical Laboratory Services, Diagnostics and Blood Bank
Series: Diagnostic and prognostic research; 6(1)
ISSN: 2397-7523
DOI: https://doi.org/10.1186/s41512-022-00130-0
Subject: Næringarfræðingar; Smitsjúkdómalæknisfræði; Lungnalæknisfræði; Svæfinga- og gjörgæslulæknisfræði; Nýrnalæknisfræði
URI: https://hdl.handle.net/20.500.11815/4085

Show full item record


Eythorsson , E , Bjarnadottir , V , Runólfsdóttir , H L , Helgason , D , Ingvarsson , R F , Björnsson , H K , Ólafsdóttir , L B , Bjarnadottir , S , Ágústsson , A S , Oskarsdottir , K , Thorvaldsson , H H , Kristjansdottir , G , Björnsson , A H , Emilsdóttir , A R , Ármannsdóttir , B , Guðlaugsson , Ó , Hansdóttir , S , Gottfreðsson , M , Bjarnason , A , Sigurðsson , M I , Indriðason , Ó S & Pálsson , R 2022 , ' Development of a prognostic model of COVID-19 severity : a population-based cohort study in Iceland ' , Diagnostic and prognostic research , vol. 6 , no. 1 , pp. 17 . https://doi.org/10.1186/s41512-022-00130-0


BACKGROUND: The severity of SARS-CoV-2 infection varies from asymptomatic state to severe respiratory failure and the clinical course is difficult to predict. The aim of the study was to develop a prognostic model to predict the severity of COVID-19 in unvaccinated adults at the time of diagnosis. METHODS: All SARS-CoV-2-positive adults in Iceland were prospectively enrolled into a telehealth service at diagnosis. A multivariable proportional-odds logistic regression model was derived from information obtained during the enrollment interview of those diagnosed between February 27 and December 31, 2020 who met the inclusion criteria. Outcomes were defined on an ordinal scale: (1) no need for escalation of care during follow-up; (2) need for urgent care visit; (3) hospitalization; and (4) admission to intensive care unit (ICU) or death. Missing data were multiply imputed using chained equations and the model was internally validated using bootstrapping techniques. Decision curve analysis was performed. RESULTS: The prognostic model was derived from 4756 SARS-CoV-2-positive persons. In total, 375 (7.9%) only required urgent care visits, 188 (4.0%) were hospitalized and 50 (1.1%) were either admitted to ICU or died due to complications of COVID-19. The model included age, sex, body mass index (BMI), current smoking, underlying conditions, and symptoms and clinical severity score at enrollment. On internal validation, the optimism-corrected Nagelkerke's R2 was 23.4% (95%CI, 22.7-24.2), the C-statistic was 0.793 (95%CI, 0.789-0.797) and the calibration slope was 0.97 (95%CI, 0.96-0.98). Outcome-specific indices were for urgent care visit or worse (calibration intercept -0.04 [95%CI, -0.06 to -0.02], Emax 0.014 [95%CI, 0.008-0.020]), hospitalization or worse (calibration intercept -0.06 [95%CI, -0.12 to -0.03], Emax 0.018 [95%CI, 0.010-0.027]), and ICU admission or death (calibration intercept -0.10 [95%CI, -0.15 to -0.04] and Emax 0.027 [95%CI, 0.013-0.041]). CONCLUSION: Our prognostic model can accurately predict the later need for urgent outpatient evaluation, hospitalization, and ICU admission and death among unvaccinated SARS-CoV-2-positive adults in the general population at the time of diagnosis, using information obtained by telephone interview.


© 2022. The Author(s).

Files in this item

This item appears in the following Collection(s)