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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...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2022
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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 |
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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 |
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