Your browser doesn't support javascript.
Imaging-based indices combining disease severity and time from disease onset to predict COVID-19 mortality: A cohort study.
Besutti, Giulia; Djuric, Olivera; Ottone, Marta; Monelli, Filippo; Lazzari, Patrizia; Ascari, Francesco; Ligabue, Guido; Guaraldi, Giovanni; Pezzuto, Giuseppe; Bechtold, Petra; Massari, Marco; Lattuada, Ivana; Luppi, Francesco; Galli, Maria Giulia; Pattacini, Pierpaolo; Giorgi Rossi, Paolo.
  • Besutti G; Radiology Department, AUSL-IRCCS di Reggio Emilia, Reggio Emilia, Italy.
  • Djuric O; Epidemiology Unit, AUSL-IRCCS di Reggio Emilia, Reggio Emilia, Italy.
  • Ottone M; Epidemiology Unit, AUSL-IRCCS di Reggio Emilia, Reggio Emilia, Italy.
  • Monelli F; Radiology Department, AUSL-IRCCS di Reggio Emilia, Reggio Emilia, Italy.
  • Lazzari P; Clinical and Experimental Medicine University of Modena and Reggio Emilia, Modena, Italy.
  • Ascari F; Department of Radiology, AOU Policlinico di Modena, University of Modena and Reggio Emilia, Modena, Italy.
  • Ligabue G; Department of Radiology, AOU Policlinico di Modena, University of Modena and Reggio Emilia, Modena, Italy.
  • Guaraldi G; Department of Radiology, AOU Policlinico di Modena, University of Modena and Reggio Emilia, Modena, Italy.
  • Pezzuto G; Department of Infectious Diseases, AOU Policlinico di Modena, University of Modena and Reggio Emilia, Modena, Italy.
  • Bechtold P; Emergency Department, AOU Policlinico di Modena, Modena, Italy.
  • Massari M; Epidemiology and Risk Communication Unit, Department of Public Health, Local Health Unit, Modena, Italy.
  • Lattuada I; Infectious Disease Unit, Arcispedale Santa Maria Nuova, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy.
  • Luppi F; Emergency Department, AUSL-IRCCS di Reggio Emilia, Reggio Emilia, Italy.
  • Galli MG; Emergency Department, AUSL-IRCCS di Reggio Emilia, Reggio Emilia, Italy.
  • Pattacini P; Emergency Department, AUSL-IRCCS di Reggio Emilia, Reggio Emilia, Italy.
  • Giorgi Rossi P; Radiology Department, AUSL-IRCCS di Reggio Emilia, Reggio Emilia, Italy.
PLoS One ; 17(6): e0270111, 2022.
Article in English | MEDLINE | ID: covidwho-1963012
ABSTRACT

BACKGROUND:

COVID-19 prognostic factors include age, sex, comorbidities, laboratory and imaging findings, and time from symptom onset to seeking care.

PURPOSE:

The study aim was to evaluate indices combining disease severity measures and time from disease onset to predict mortality of COVID-19 patients admitted to the emergency department (ED). MATERIALS AND

METHODS:

All consecutive COVID-19 patients who underwent both computed tomography (CT) and chest X-ray (CXR) at ED presentation between 27/02/2020 and 13/03/2020 were included. CT visual score of disease extension and CXR Radiographic Assessment of Lung Edema (RALE) score were collected. The CT- and CXR-based scores, C-reactive protein (CRP), and oxygen saturation levels (sO2) were separately combined with time from symptom onset to ED presentation to obtain severity/time indices. Multivariable regression age- and sex-adjusted models without and with severity/time indices were compared. For CXR-RALE, the models were tested in a validation cohort.

RESULTS:

Of the 308 included patients, 55 (17.9%) died. In multivariable logistic age- and sex-adjusted models for death at 30 days, severity/time indices showed good discrimination ability, higher for imaging than for laboratory measures (AUCCT = 0.92, AUCCXR = 0.90, AUCCRP = 0.88, AUCsO2 = 0.88). AUCCXR was lower in the validation cohort (0.79). The models including severity/time indices performed slightly better than models including measures of disease severity not combined with time and those including the Charlson Comorbidity Index, except for CRP-based models.

CONCLUSION:

Time from symptom onset to ED admission is a strong prognostic factor and provides added value to the interpretation of imaging and laboratory findings at ED presentation.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study Limits: Humans Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2022 Document Type: Article Affiliation country: Journal.pone.0270111

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study Limits: Humans Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2022 Document Type: Article Affiliation country: Journal.pone.0270111