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Prediction model of emergency mortality risk in patients with acute upper gastrointestinal bleeding: a retrospective study

BACKGROUND: Upper gastrointestinal bleeding is a common presentation in emergency departments and carries significant morbidity worldwide. It is paramount that treating physicians have access to tools that can effectively evaluate the patient risk, allowing quick and effective treatments to ultimate...

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Autores principales: Chen, Lan, Zheng, Han, Wang, Saibin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8236237/
https://www.ncbi.nlm.nih.gov/pubmed/34221734
http://dx.doi.org/10.7717/peerj.11656
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author Chen, Lan
Zheng, Han
Wang, Saibin
author_facet Chen, Lan
Zheng, Han
Wang, Saibin
author_sort Chen, Lan
collection PubMed
description BACKGROUND: Upper gastrointestinal bleeding is a common presentation in emergency departments and carries significant morbidity worldwide. It is paramount that treating physicians have access to tools that can effectively evaluate the patient risk, allowing quick and effective treatments to ultimately improve their prognosis. This study aims to establish a mortality risk assessment model for patients with acute upper gastrointestinal bleeding at an emergency department. METHODS: A total of 991 patients presenting with acute upper gastrointestinal bleeding between July 2016 and June 2019 were enrolled in this retrospective single-center cohort study. Patient demographics, parameters assessed at admission, laboratory test, and clinical interventions were extracted. We used the least absolute shrinkage and selection operator regression to identify predictors for establishing a nomogram for death in the emergency department or within 24 h after leaving the emergency department and a corresponding nomogram. The area under the curve of the model was calculated. A bootstrap resampling method was used to internal validation, and decision curve analysis was applied for evaluate the clinical utility of the model. We also compared our predictive model with other prognostic models, such as AIMS65, Glasgow-Blatchford bleeding score, modified Glasgow-Blatchford bleeding score, and Pre-Endoscopic Rockall Score. RESULTS: Among 991 patients, 41 (4.14%) died in the emergency department or within 24 h after leaving the emergency department. Five non-zero coefficient variables (transfusion of plasma, D-dimer, albumin, potassium, age) were filtered by the least absolute shrinkage and selection operator regression analysis and used to establish a predictive model. The area under the curve for the model was 0.847 (95% confidence interval [0.794–0.900]), which is higher than that of previous models for mortality of patients with acute upper gastrointestinal bleeding. The decision curve analysis indicated the clinical usefulness of the model. CONCLUSIONS: The nomogram based on transfusion of plasma, D-dimer, albumin, potassium, and age effectively assessed the prognosis of patients with acute upper gastrointestinal bleeding presenting at the emergency department.
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spelling pubmed-82362372021-07-02 Prediction model of emergency mortality risk in patients with acute upper gastrointestinal bleeding: a retrospective study Chen, Lan Zheng, Han Wang, Saibin PeerJ Emergency and Critical Care BACKGROUND: Upper gastrointestinal bleeding is a common presentation in emergency departments and carries significant morbidity worldwide. It is paramount that treating physicians have access to tools that can effectively evaluate the patient risk, allowing quick and effective treatments to ultimately improve their prognosis. This study aims to establish a mortality risk assessment model for patients with acute upper gastrointestinal bleeding at an emergency department. METHODS: A total of 991 patients presenting with acute upper gastrointestinal bleeding between July 2016 and June 2019 were enrolled in this retrospective single-center cohort study. Patient demographics, parameters assessed at admission, laboratory test, and clinical interventions were extracted. We used the least absolute shrinkage and selection operator regression to identify predictors for establishing a nomogram for death in the emergency department or within 24 h after leaving the emergency department and a corresponding nomogram. The area under the curve of the model was calculated. A bootstrap resampling method was used to internal validation, and decision curve analysis was applied for evaluate the clinical utility of the model. We also compared our predictive model with other prognostic models, such as AIMS65, Glasgow-Blatchford bleeding score, modified Glasgow-Blatchford bleeding score, and Pre-Endoscopic Rockall Score. RESULTS: Among 991 patients, 41 (4.14%) died in the emergency department or within 24 h after leaving the emergency department. Five non-zero coefficient variables (transfusion of plasma, D-dimer, albumin, potassium, age) were filtered by the least absolute shrinkage and selection operator regression analysis and used to establish a predictive model. The area under the curve for the model was 0.847 (95% confidence interval [0.794–0.900]), which is higher than that of previous models for mortality of patients with acute upper gastrointestinal bleeding. The decision curve analysis indicated the clinical usefulness of the model. CONCLUSIONS: The nomogram based on transfusion of plasma, D-dimer, albumin, potassium, and age effectively assessed the prognosis of patients with acute upper gastrointestinal bleeding presenting at the emergency department. PeerJ Inc. 2021-06-24 /pmc/articles/PMC8236237/ /pubmed/34221734 http://dx.doi.org/10.7717/peerj.11656 Text en © 2021 Chen et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Emergency and Critical Care
Chen, Lan
Zheng, Han
Wang, Saibin
Prediction model of emergency mortality risk in patients with acute upper gastrointestinal bleeding: a retrospective study
title Prediction model of emergency mortality risk in patients with acute upper gastrointestinal bleeding: a retrospective study
title_full Prediction model of emergency mortality risk in patients with acute upper gastrointestinal bleeding: a retrospective study
title_fullStr Prediction model of emergency mortality risk in patients with acute upper gastrointestinal bleeding: a retrospective study
title_full_unstemmed Prediction model of emergency mortality risk in patients with acute upper gastrointestinal bleeding: a retrospective study
title_short Prediction model of emergency mortality risk in patients with acute upper gastrointestinal bleeding: a retrospective study
title_sort prediction model of emergency mortality risk in patients with acute upper gastrointestinal bleeding: a retrospective study
topic Emergency and Critical Care
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8236237/
https://www.ncbi.nlm.nih.gov/pubmed/34221734
http://dx.doi.org/10.7717/peerj.11656
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