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A nomogram to predict arterial bleeding in patients with pelvic fractures after blunt trauma: a retrospective cohort study

BACKGROUND: Pelvic bone fractures are one of the biggest challenges faced by trauma surgeons. Especially, the presence of bleeding and hemodynamic instability features is associated with high morbidity and mortality in patients with pelvic fractures. However, prediction of the occurrence of arterial...

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Autores principales: Kim, Myoung Jun, Lee, Jae Gil, Kim, Eun Hwa, Lee, Seung Hwan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7869209/
https://www.ncbi.nlm.nih.gov/pubmed/33557886
http://dx.doi.org/10.1186/s13018-021-02247-2
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author Kim, Myoung Jun
Lee, Jae Gil
Kim, Eun Hwa
Lee, Seung Hwan
author_facet Kim, Myoung Jun
Lee, Jae Gil
Kim, Eun Hwa
Lee, Seung Hwan
author_sort Kim, Myoung Jun
collection PubMed
description BACKGROUND: Pelvic bone fractures are one of the biggest challenges faced by trauma surgeons. Especially, the presence of bleeding and hemodynamic instability features is associated with high morbidity and mortality in patients with pelvic fractures. However, prediction of the occurrence of arterial bleeding causing massive hemorrhage in patients with pelvic fractures is difficult. Therefore, the aim of this study was to develop a nomogram to predict arterial bleeding in patients with pelvic bone fractures after blunt trauma. METHODS: The medical records of 1404 trauma patients treated between January 2013 and August 2017 were retrospectively reviewed. Patients older than 15 years with a pelvic fracture due to blunt trauma were enrolled (n = 148). The pelvic fracture pattern on anteroposterior radiography was classified according to the Orthopedic Trauma Association/Arbeitsgemeinschaft fur Osteosynthesefragen (OTA/AO) system. Multivariable logistic regression modeling was used to determine the independent risk factors for arterial bleeding. A nomogram was constructed based on the identified risk factors. RESULTS: The most common pelvic fracture pattern was type A (58.8%), followed by types B (34.5%) and C (6.7%). Of the 148 patients, 28 (18.9%) showed pelvic arterial bleeding on contrast-enhanced computed tomography or angiography, or in the operative findings. The independent risk factors for arterial bleeding were a type B or C pelvic fracture pattern, body temperature < 36 °C, and serum lactate level > 3.4 mmol/L. A nomogram was developed using these three parameters, along with a systolic blood pressure < 90 mmHg. The area under the receiver operating characteristic curve of the predictive model for discrimination was 0.8579. The maximal Youden index was 0.1527, corresponding to a cutoff value of 68.65 points, which was considered the optimal cutoff value for predicting the occurrence of arterial bleeding in patients with pelvic bone fractures. CONCLUSIONS: The developed nomogram, which was based on the initial clinical findings identifying risk factors for arterial bleeding, is expected to be helpful in rapidly establishing a treatment plan and improving the prognosis for patients with pelvic bone fractures. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13018-021-02247-2.
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spelling pubmed-78692092021-02-08 A nomogram to predict arterial bleeding in patients with pelvic fractures after blunt trauma: a retrospective cohort study Kim, Myoung Jun Lee, Jae Gil Kim, Eun Hwa Lee, Seung Hwan J Orthop Surg Res Research Article BACKGROUND: Pelvic bone fractures are one of the biggest challenges faced by trauma surgeons. Especially, the presence of bleeding and hemodynamic instability features is associated with high morbidity and mortality in patients with pelvic fractures. However, prediction of the occurrence of arterial bleeding causing massive hemorrhage in patients with pelvic fractures is difficult. Therefore, the aim of this study was to develop a nomogram to predict arterial bleeding in patients with pelvic bone fractures after blunt trauma. METHODS: The medical records of 1404 trauma patients treated between January 2013 and August 2017 were retrospectively reviewed. Patients older than 15 years with a pelvic fracture due to blunt trauma were enrolled (n = 148). The pelvic fracture pattern on anteroposterior radiography was classified according to the Orthopedic Trauma Association/Arbeitsgemeinschaft fur Osteosynthesefragen (OTA/AO) system. Multivariable logistic regression modeling was used to determine the independent risk factors for arterial bleeding. A nomogram was constructed based on the identified risk factors. RESULTS: The most common pelvic fracture pattern was type A (58.8%), followed by types B (34.5%) and C (6.7%). Of the 148 patients, 28 (18.9%) showed pelvic arterial bleeding on contrast-enhanced computed tomography or angiography, or in the operative findings. The independent risk factors for arterial bleeding were a type B or C pelvic fracture pattern, body temperature < 36 °C, and serum lactate level > 3.4 mmol/L. A nomogram was developed using these three parameters, along with a systolic blood pressure < 90 mmHg. The area under the receiver operating characteristic curve of the predictive model for discrimination was 0.8579. The maximal Youden index was 0.1527, corresponding to a cutoff value of 68.65 points, which was considered the optimal cutoff value for predicting the occurrence of arterial bleeding in patients with pelvic bone fractures. CONCLUSIONS: The developed nomogram, which was based on the initial clinical findings identifying risk factors for arterial bleeding, is expected to be helpful in rapidly establishing a treatment plan and improving the prognosis for patients with pelvic bone fractures. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13018-021-02247-2. BioMed Central 2021-02-08 /pmc/articles/PMC7869209/ /pubmed/33557886 http://dx.doi.org/10.1186/s13018-021-02247-2 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Kim, Myoung Jun
Lee, Jae Gil
Kim, Eun Hwa
Lee, Seung Hwan
A nomogram to predict arterial bleeding in patients with pelvic fractures after blunt trauma: a retrospective cohort study
title A nomogram to predict arterial bleeding in patients with pelvic fractures after blunt trauma: a retrospective cohort study
title_full A nomogram to predict arterial bleeding in patients with pelvic fractures after blunt trauma: a retrospective cohort study
title_fullStr A nomogram to predict arterial bleeding in patients with pelvic fractures after blunt trauma: a retrospective cohort study
title_full_unstemmed A nomogram to predict arterial bleeding in patients with pelvic fractures after blunt trauma: a retrospective cohort study
title_short A nomogram to predict arterial bleeding in patients with pelvic fractures after blunt trauma: a retrospective cohort study
title_sort nomogram to predict arterial bleeding in patients with pelvic fractures after blunt trauma: a retrospective cohort study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7869209/
https://www.ncbi.nlm.nih.gov/pubmed/33557886
http://dx.doi.org/10.1186/s13018-021-02247-2
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