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Venous thromboembolism risk assessment of surgical patients in Southwest China using real-world data: establishment and evaluation of an improved venous thromboembolism risk model

BACKGROUND: Venous thromboembolism (VTE) risk assessment in surgical patients is important for the appropriate diagnosis and treatment of patients. The commonly used Caprini model is limited by its inadequate ability to discriminate between risk stratums on the surgical population in southwest China...

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Autores principales: Wang, Peng, Wang, Yao, Yuan, Zhaoying, Wang, Fei, Wang, Hongqian, Li, Ying, Wang, Chengliang, Li, Linfeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8895056/
https://www.ncbi.nlm.nih.gov/pubmed/35246122
http://dx.doi.org/10.1186/s12911-022-01795-9
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author Wang, Peng
Wang, Yao
Yuan, Zhaoying
Wang, Fei
Wang, Hongqian
Li, Ying
Wang, Chengliang
Li, Linfeng
author_facet Wang, Peng
Wang, Yao
Yuan, Zhaoying
Wang, Fei
Wang, Hongqian
Li, Ying
Wang, Chengliang
Li, Linfeng
author_sort Wang, Peng
collection PubMed
description BACKGROUND: Venous thromboembolism (VTE) risk assessment in surgical patients is important for the appropriate diagnosis and treatment of patients. The commonly used Caprini model is limited by its inadequate ability to discriminate between risk stratums on the surgical population in southwest China and lengthy risk factors. The purpose of this study was to establish an improved VTE risk assessment model that is accurate and simple. METHODS: This study is based on the clinical data from 81,505 surgical patients hospitalized in the Southwest Hospital of China between January 1, 2019 and June 18, 2021. Among the population, 559 patients developed VTE. An improved VTE risk assessment model, SW-model, was established through Logistic Regression, with comparisons to both Caprini and Random Forest. RESULTS: The SW-model incorporated eight risk factors. The area under the curve (AUC) of SW-model (0.807 [0.758, 0.853], 0.804 [0.765, 0.840]), are significantly superior (p = 0.001 and p = 0.044) to those of the Caprini (0.705 [0.652, 0.757], 0.758 [0.719, 0795]) on two test sets, but inferior (p < 0.001 and p = 0.002) to Random Forest (0.854 [0.814, 0.890], 0.839 [0.806, 0.868]). In decision curve analysis, within threshold range from 0.015 to 0.04, the DCA curves of the SW-model are superior to Caprini and two default strategies. CONCLUSIONS: The SW-model demonstrated a higher discriminative capability to distinguish VTE positive in surgical patients compared with the Caprini model. Compared to Random Forest, Logistic Regression based SW-model provided interpretability which is essential in guarantee the procedure of risk assessment transparent to clinicians. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-022-01795-9.
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spelling pubmed-88950562022-03-04 Venous thromboembolism risk assessment of surgical patients in Southwest China using real-world data: establishment and evaluation of an improved venous thromboembolism risk model Wang, Peng Wang, Yao Yuan, Zhaoying Wang, Fei Wang, Hongqian Li, Ying Wang, Chengliang Li, Linfeng BMC Med Inform Decis Mak Research BACKGROUND: Venous thromboembolism (VTE) risk assessment in surgical patients is important for the appropriate diagnosis and treatment of patients. The commonly used Caprini model is limited by its inadequate ability to discriminate between risk stratums on the surgical population in southwest China and lengthy risk factors. The purpose of this study was to establish an improved VTE risk assessment model that is accurate and simple. METHODS: This study is based on the clinical data from 81,505 surgical patients hospitalized in the Southwest Hospital of China between January 1, 2019 and June 18, 2021. Among the population, 559 patients developed VTE. An improved VTE risk assessment model, SW-model, was established through Logistic Regression, with comparisons to both Caprini and Random Forest. RESULTS: The SW-model incorporated eight risk factors. The area under the curve (AUC) of SW-model (0.807 [0.758, 0.853], 0.804 [0.765, 0.840]), are significantly superior (p = 0.001 and p = 0.044) to those of the Caprini (0.705 [0.652, 0.757], 0.758 [0.719, 0795]) on two test sets, but inferior (p < 0.001 and p = 0.002) to Random Forest (0.854 [0.814, 0.890], 0.839 [0.806, 0.868]). In decision curve analysis, within threshold range from 0.015 to 0.04, the DCA curves of the SW-model are superior to Caprini and two default strategies. CONCLUSIONS: The SW-model demonstrated a higher discriminative capability to distinguish VTE positive in surgical patients compared with the Caprini model. Compared to Random Forest, Logistic Regression based SW-model provided interpretability which is essential in guarantee the procedure of risk assessment transparent to clinicians. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-022-01795-9. BioMed Central 2022-03-04 /pmc/articles/PMC8895056/ /pubmed/35246122 http://dx.doi.org/10.1186/s12911-022-01795-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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
Wang, Peng
Wang, Yao
Yuan, Zhaoying
Wang, Fei
Wang, Hongqian
Li, Ying
Wang, Chengliang
Li, Linfeng
Venous thromboembolism risk assessment of surgical patients in Southwest China using real-world data: establishment and evaluation of an improved venous thromboembolism risk model
title Venous thromboembolism risk assessment of surgical patients in Southwest China using real-world data: establishment and evaluation of an improved venous thromboembolism risk model
title_full Venous thromboembolism risk assessment of surgical patients in Southwest China using real-world data: establishment and evaluation of an improved venous thromboembolism risk model
title_fullStr Venous thromboembolism risk assessment of surgical patients in Southwest China using real-world data: establishment and evaluation of an improved venous thromboembolism risk model
title_full_unstemmed Venous thromboembolism risk assessment of surgical patients in Southwest China using real-world data: establishment and evaluation of an improved venous thromboembolism risk model
title_short Venous thromboembolism risk assessment of surgical patients in Southwest China using real-world data: establishment and evaluation of an improved venous thromboembolism risk model
title_sort venous thromboembolism risk assessment of surgical patients in southwest china using real-world data: establishment and evaluation of an improved venous thromboembolism risk model
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8895056/
https://www.ncbi.nlm.nih.gov/pubmed/35246122
http://dx.doi.org/10.1186/s12911-022-01795-9
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