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Intensive care unit readmission and unexpected death after emergency general surgery

BACKGROUND: Intensive care unit (ICU) readmission and unexpected death are closely associated with increased length of hospitalization and total mortality. However, data about readmission or unexpected death after discharge from ICU in patients who have undergone emergency general surgery (EGS) is v...

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Autores principales: Guo, Ran, Cui, Na
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10023911/
https://www.ncbi.nlm.nih.gov/pubmed/36942248
http://dx.doi.org/10.1016/j.heliyon.2023.e14278
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author Guo, Ran
Cui, Na
author_facet Guo, Ran
Cui, Na
author_sort Guo, Ran
collection PubMed
description BACKGROUND: Intensive care unit (ICU) readmission and unexpected death are closely associated with increased length of hospitalization and total mortality. However, data about readmission or unexpected death after discharge from ICU in patients who have undergone emergency general surgery (EGS) is very limited. METHODS: In total, 1133 patients who underwent EGS were identified in the Multiparameter Intelligent Monitoring in Intensive Care IV (MIMIC-IV) database. Of these 1133 patients, 124 underwent readmission into the ICU or death unexpectedly after their initial discharge. The clinical characteristics of the patients were investigated. A logistic regression model was implemented for the analysis of the independent risk factors associated with ICU readmission or unexpected death. A nomogram model was established to predict the risk of ICU readmission or unexpected death within 72 h after EGS. RESULTS: Peripheral vascular disease and atrial fibrillation, vasopressor requirement, a higher respiratory rate or heart rate, a lower pulse oxygen saturation or a platelet count of <150 K/μL and a relatively low Glasgow coma scale score in the last 24 h before ICU discharge were independent risk factors for ICU readmission or death within 72 h. The nomogram had moderate accuracy with an area under the curve of 0.852, which had a stronger prediction power than the Stability and Workload Index for Transfer (SWIFT) score, a classic prediction model for ICU readmission risk. CONCLUSIONS: In critically ill patients who undergo EGS, ICU readmission or unexpected death within 72 h can be predicted using a nomogram model based on eight parameters including physiological and laboratory test values in the last 24 h before discharge and comorbidities. ICU physicians should prudently assess patients to make effective discharge decisions.
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spelling pubmed-100239112023-03-19 Intensive care unit readmission and unexpected death after emergency general surgery Guo, Ran Cui, Na Heliyon Research Article BACKGROUND: Intensive care unit (ICU) readmission and unexpected death are closely associated with increased length of hospitalization and total mortality. However, data about readmission or unexpected death after discharge from ICU in patients who have undergone emergency general surgery (EGS) is very limited. METHODS: In total, 1133 patients who underwent EGS were identified in the Multiparameter Intelligent Monitoring in Intensive Care IV (MIMIC-IV) database. Of these 1133 patients, 124 underwent readmission into the ICU or death unexpectedly after their initial discharge. The clinical characteristics of the patients were investigated. A logistic regression model was implemented for the analysis of the independent risk factors associated with ICU readmission or unexpected death. A nomogram model was established to predict the risk of ICU readmission or unexpected death within 72 h after EGS. RESULTS: Peripheral vascular disease and atrial fibrillation, vasopressor requirement, a higher respiratory rate or heart rate, a lower pulse oxygen saturation or a platelet count of <150 K/μL and a relatively low Glasgow coma scale score in the last 24 h before ICU discharge were independent risk factors for ICU readmission or death within 72 h. The nomogram had moderate accuracy with an area under the curve of 0.852, which had a stronger prediction power than the Stability and Workload Index for Transfer (SWIFT) score, a classic prediction model for ICU readmission risk. CONCLUSIONS: In critically ill patients who undergo EGS, ICU readmission or unexpected death within 72 h can be predicted using a nomogram model based on eight parameters including physiological and laboratory test values in the last 24 h before discharge and comorbidities. ICU physicians should prudently assess patients to make effective discharge decisions. Elsevier 2023-03-09 /pmc/articles/PMC10023911/ /pubmed/36942248 http://dx.doi.org/10.1016/j.heliyon.2023.e14278 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Guo, Ran
Cui, Na
Intensive care unit readmission and unexpected death after emergency general surgery
title Intensive care unit readmission and unexpected death after emergency general surgery
title_full Intensive care unit readmission and unexpected death after emergency general surgery
title_fullStr Intensive care unit readmission and unexpected death after emergency general surgery
title_full_unstemmed Intensive care unit readmission and unexpected death after emergency general surgery
title_short Intensive care unit readmission and unexpected death after emergency general surgery
title_sort intensive care unit readmission and unexpected death after emergency general surgery
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10023911/
https://www.ncbi.nlm.nih.gov/pubmed/36942248
http://dx.doi.org/10.1016/j.heliyon.2023.e14278
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