Cargando…

Clinical and imaging characteristics of patients with COVID-19 predicting hospital readmission after emergency department discharge: a single-centre cohort study in Italy

OBJECTIVE: We aimed at identifying baseline predictive factors for emergency department (ED) readmission, with hospitalisation/death, in patients with COVID-19 previously discharged from the ED. We also developed a disease progression velocity index. DESIGN AND SETTING: Retrospective cohort study of...

Descripción completa

Detalles Bibliográficos
Autores principales: Galli, Maria Giulia, Djuric, Olivera, Besutti, Giulia, Ottone, Marta, Amidei, Lucia, Bitton, Lee, Bonilauri, Carlotta, Boracchia, Luca, Campanale, Sergio, Curcio, Vittoria, Lucchesi, Davide Maria Francesco, Mulas, Cesare Salvatore, Santi, Francesca, Ferrari, Anna Maria, Giorgi Rossi, Paolo, Luppi, Francesco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8987209/
https://www.ncbi.nlm.nih.gov/pubmed/35387808
http://dx.doi.org/10.1136/bmjopen-2021-052665
_version_ 1784682690171109376
author Galli, Maria Giulia
Djuric, Olivera
Besutti, Giulia
Ottone, Marta
Amidei, Lucia
Bitton, Lee
Bonilauri, Carlotta
Boracchia, Luca
Campanale, Sergio
Curcio, Vittoria
Lucchesi, Davide Maria Francesco
Mulas, Cesare Salvatore
Santi, Francesca
Ferrari, Anna Maria
Giorgi Rossi, Paolo
Luppi, Francesco
author_facet Galli, Maria Giulia
Djuric, Olivera
Besutti, Giulia
Ottone, Marta
Amidei, Lucia
Bitton, Lee
Bonilauri, Carlotta
Boracchia, Luca
Campanale, Sergio
Curcio, Vittoria
Lucchesi, Davide Maria Francesco
Mulas, Cesare Salvatore
Santi, Francesca
Ferrari, Anna Maria
Giorgi Rossi, Paolo
Luppi, Francesco
author_sort Galli, Maria Giulia
collection PubMed
description OBJECTIVE: We aimed at identifying baseline predictive factors for emergency department (ED) readmission, with hospitalisation/death, in patients with COVID-19 previously discharged from the ED. We also developed a disease progression velocity index. DESIGN AND SETTING: Retrospective cohort study of prospectively collected data. The charts of consecutive patients with COVID-19 discharged from the Reggio Emilia (Italy) ED (2 March 2 to 31 March 2020) were retrospectively examined. Clinical, laboratory and CT findings at first ED admission were tested as predictive factors using multivariable logistic models. We divided CT extension by days from symptom onset to build a synthetic velocity index. PARTICIPANTS: 450 patients discharged from the ED with diagnosis of COVID-19. MAIN OUTCOME MEASURE: ED readmission within 14 days, followed by hospitalisation/death. RESULTS: Of the discharged patients, 84 (18.7%) were readmitted to the ED, 61 (13.6%) were hospitalised and 10 (2.2%) died. Age (OR=1.05; 95% CI 1.03 to 1.08), Charlson Comorbidity Index 3 versus 0 (OR=11.61; 95% CI 1.76 to 76.58), days from symptom onset (OR for 1-day increase=0.81; 95% CI 0.73 to 0.90) and CT extension (OR for 1% increase=1.03; 95% CI 1.01 to 1.06) were associated in a multivariable model for readmission with hospitalisation/death. A 2-day lag velocity index was a strong predictor (OR for unit increase=1.21, 95% CI 1.08 to 1.36); the model including this index resulted in less information loss. CONCLUSIONS: A velocity index combining CT extension and days from symptom onset predicts disease progression in patients with COVID-19. For example, a 20% CT extension 3 days after symptom onset has the same risk as does 50% after 10 days.
format Online
Article
Text
id pubmed-8987209
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher BMJ Publishing Group
record_format MEDLINE/PubMed
spelling pubmed-89872092022-04-07 Clinical and imaging characteristics of patients with COVID-19 predicting hospital readmission after emergency department discharge: a single-centre cohort study in Italy Galli, Maria Giulia Djuric, Olivera Besutti, Giulia Ottone, Marta Amidei, Lucia Bitton, Lee Bonilauri, Carlotta Boracchia, Luca Campanale, Sergio Curcio, Vittoria Lucchesi, Davide Maria Francesco Mulas, Cesare Salvatore Santi, Francesca Ferrari, Anna Maria Giorgi Rossi, Paolo Luppi, Francesco BMJ Open Emergency Medicine OBJECTIVE: We aimed at identifying baseline predictive factors for emergency department (ED) readmission, with hospitalisation/death, in patients with COVID-19 previously discharged from the ED. We also developed a disease progression velocity index. DESIGN AND SETTING: Retrospective cohort study of prospectively collected data. The charts of consecutive patients with COVID-19 discharged from the Reggio Emilia (Italy) ED (2 March 2 to 31 March 2020) were retrospectively examined. Clinical, laboratory and CT findings at first ED admission were tested as predictive factors using multivariable logistic models. We divided CT extension by days from symptom onset to build a synthetic velocity index. PARTICIPANTS: 450 patients discharged from the ED with diagnosis of COVID-19. MAIN OUTCOME MEASURE: ED readmission within 14 days, followed by hospitalisation/death. RESULTS: Of the discharged patients, 84 (18.7%) were readmitted to the ED, 61 (13.6%) were hospitalised and 10 (2.2%) died. Age (OR=1.05; 95% CI 1.03 to 1.08), Charlson Comorbidity Index 3 versus 0 (OR=11.61; 95% CI 1.76 to 76.58), days from symptom onset (OR for 1-day increase=0.81; 95% CI 0.73 to 0.90) and CT extension (OR for 1% increase=1.03; 95% CI 1.01 to 1.06) were associated in a multivariable model for readmission with hospitalisation/death. A 2-day lag velocity index was a strong predictor (OR for unit increase=1.21, 95% CI 1.08 to 1.36); the model including this index resulted in less information loss. CONCLUSIONS: A velocity index combining CT extension and days from symptom onset predicts disease progression in patients with COVID-19. For example, a 20% CT extension 3 days after symptom onset has the same risk as does 50% after 10 days. BMJ Publishing Group 2022-04-05 /pmc/articles/PMC8987209/ /pubmed/35387808 http://dx.doi.org/10.1136/bmjopen-2021-052665 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Emergency Medicine
Galli, Maria Giulia
Djuric, Olivera
Besutti, Giulia
Ottone, Marta
Amidei, Lucia
Bitton, Lee
Bonilauri, Carlotta
Boracchia, Luca
Campanale, Sergio
Curcio, Vittoria
Lucchesi, Davide Maria Francesco
Mulas, Cesare Salvatore
Santi, Francesca
Ferrari, Anna Maria
Giorgi Rossi, Paolo
Luppi, Francesco
Clinical and imaging characteristics of patients with COVID-19 predicting hospital readmission after emergency department discharge: a single-centre cohort study in Italy
title Clinical and imaging characteristics of patients with COVID-19 predicting hospital readmission after emergency department discharge: a single-centre cohort study in Italy
title_full Clinical and imaging characteristics of patients with COVID-19 predicting hospital readmission after emergency department discharge: a single-centre cohort study in Italy
title_fullStr Clinical and imaging characteristics of patients with COVID-19 predicting hospital readmission after emergency department discharge: a single-centre cohort study in Italy
title_full_unstemmed Clinical and imaging characteristics of patients with COVID-19 predicting hospital readmission after emergency department discharge: a single-centre cohort study in Italy
title_short Clinical and imaging characteristics of patients with COVID-19 predicting hospital readmission after emergency department discharge: a single-centre cohort study in Italy
title_sort clinical and imaging characteristics of patients with covid-19 predicting hospital readmission after emergency department discharge: a single-centre cohort study in italy
topic Emergency Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8987209/
https://www.ncbi.nlm.nih.gov/pubmed/35387808
http://dx.doi.org/10.1136/bmjopen-2021-052665
work_keys_str_mv AT gallimariagiulia clinicalandimagingcharacteristicsofpatientswithcovid19predictinghospitalreadmissionafteremergencydepartmentdischargeasinglecentrecohortstudyinitaly
AT djuricolivera clinicalandimagingcharacteristicsofpatientswithcovid19predictinghospitalreadmissionafteremergencydepartmentdischargeasinglecentrecohortstudyinitaly
AT besuttigiulia clinicalandimagingcharacteristicsofpatientswithcovid19predictinghospitalreadmissionafteremergencydepartmentdischargeasinglecentrecohortstudyinitaly
AT ottonemarta clinicalandimagingcharacteristicsofpatientswithcovid19predictinghospitalreadmissionafteremergencydepartmentdischargeasinglecentrecohortstudyinitaly
AT amideilucia clinicalandimagingcharacteristicsofpatientswithcovid19predictinghospitalreadmissionafteremergencydepartmentdischargeasinglecentrecohortstudyinitaly
AT bittonlee clinicalandimagingcharacteristicsofpatientswithcovid19predictinghospitalreadmissionafteremergencydepartmentdischargeasinglecentrecohortstudyinitaly
AT bonilauricarlotta clinicalandimagingcharacteristicsofpatientswithcovid19predictinghospitalreadmissionafteremergencydepartmentdischargeasinglecentrecohortstudyinitaly
AT boracchialuca clinicalandimagingcharacteristicsofpatientswithcovid19predictinghospitalreadmissionafteremergencydepartmentdischargeasinglecentrecohortstudyinitaly
AT campanalesergio clinicalandimagingcharacteristicsofpatientswithcovid19predictinghospitalreadmissionafteremergencydepartmentdischargeasinglecentrecohortstudyinitaly
AT curciovittoria clinicalandimagingcharacteristicsofpatientswithcovid19predictinghospitalreadmissionafteremergencydepartmentdischargeasinglecentrecohortstudyinitaly
AT lucchesidavidemariafrancesco clinicalandimagingcharacteristicsofpatientswithcovid19predictinghospitalreadmissionafteremergencydepartmentdischargeasinglecentrecohortstudyinitaly
AT mulascesaresalvatore clinicalandimagingcharacteristicsofpatientswithcovid19predictinghospitalreadmissionafteremergencydepartmentdischargeasinglecentrecohortstudyinitaly
AT santifrancesca clinicalandimagingcharacteristicsofpatientswithcovid19predictinghospitalreadmissionafteremergencydepartmentdischargeasinglecentrecohortstudyinitaly
AT ferrariannamaria clinicalandimagingcharacteristicsofpatientswithcovid19predictinghospitalreadmissionafteremergencydepartmentdischargeasinglecentrecohortstudyinitaly
AT giorgirossipaolo clinicalandimagingcharacteristicsofpatientswithcovid19predictinghospitalreadmissionafteremergencydepartmentdischargeasinglecentrecohortstudyinitaly
AT luppifrancesco clinicalandimagingcharacteristicsofpatientswithcovid19predictinghospitalreadmissionafteremergencydepartmentdischargeasinglecentrecohortstudyinitaly
AT clinicalandimagingcharacteristicsofpatientswithcovid19predictinghospitalreadmissionafteremergencydepartmentdischargeasinglecentrecohortstudyinitaly