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A prospective marker for the prediction of postoperative deep venous thrombosis: Neutrophil extracellular traps

Deep venous thrombosis (DVT) is a common medical complication in patients with lumbar fractures. The current study aimed to investigate the predictive value of neutrophil extracellular traps (NETs) in postoperative DVT formation in patients with lumbar fractures and to develop a nomogram relating cl...

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Autores principales: Li, Yin, Jiang, Qinyi, Zhou, Xiaohua, Wu, Mengyuan, Chen, Jian, Liu, Hao, Dai, Siming, Zheng, Ziyang, Zhao, Xuan, Zhang, Chenxi, Shi, Zhuoying, Zhang, Haitao, Gu, Jinyu, Huang, Zhenfei, Yin, Guoyong, Zhao, Shujie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9709260/
https://www.ncbi.nlm.nih.gov/pubmed/36467414
http://dx.doi.org/10.3389/fcell.2022.1071550
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author Li, Yin
Jiang, Qinyi
Zhou, Xiaohua
Wu, Mengyuan
Chen, Jian
Liu, Hao
Dai, Siming
Zheng, Ziyang
Zhao, Xuan
Zhang, Chenxi
Shi, Zhuoying
Zhang, Haitao
Gu, Jinyu
Huang, Zhenfei
Yin, Guoyong
Zhao, Shujie
author_facet Li, Yin
Jiang, Qinyi
Zhou, Xiaohua
Wu, Mengyuan
Chen, Jian
Liu, Hao
Dai, Siming
Zheng, Ziyang
Zhao, Xuan
Zhang, Chenxi
Shi, Zhuoying
Zhang, Haitao
Gu, Jinyu
Huang, Zhenfei
Yin, Guoyong
Zhao, Shujie
author_sort Li, Yin
collection PubMed
description Deep venous thrombosis (DVT) is a common medical complication in patients with lumbar fractures. The current study aimed to investigate the predictive value of neutrophil extracellular traps (NETs) in postoperative DVT formation in patients with lumbar fractures and to develop a nomogram relating clinical admission information for prediction. Patients who underwent open reduction and pedicle screw internal fixation in the treatment of single-segment lumbar fracture in the Department of Spine Surgery, the First Affiliated Hospital of Nanjing Medical University, from December 2020 to June 2022 were enrolled in this study. Baseline data and laboratory results were collected from enrollees, and the primary study endpoint event was the occurrence of DVT in patients after surgery. Multivariable logistic regression analysis was used to identify risk factors associated with higher odds of DVT after surgery. A nomogram was constructed using the results of the multivariable model. The calibration plot and receiver operating characteristics (ROC) curve were used to show the satisfactory predictive capacity of the model. Of these 393 patients who did not have DVT preoperatively, 79 patients developed it postoperatively, and 314 did not, respectively. Multivariate analysis showed that higher body mass index (BMI) (BMI between 24 and 28: RR = 1.661, 95% CI = 0.891–3.094; BMI ≤28: RR = 5.625, 95% CI = 2.590–12.217; reference: BMI <24), neutrophils (RR = 1.157, 95% CI 1.042–1.285), D-dimer (RR = 1.098, 95% CI 1.000–1.206), and citrullinated histone H3 (CitH3) (RR = 1.043, 95% CI 1.026–1.060) were independent risk factors for postoperative DVT. Using the multivariable analysis, we then constructed a nomogram to predict DVT, which was found to have an area under the curve of 0.757 (95% CI = 0.693–0.820). Calibration plots also showed the satisfied discrimination and calibration of the nomogram. In conclusion, patients with lumbar fractures with postoperative DVT had higher levels of NETs in the circulation preoperatively compared to those without postoperative DVT. Furthermore, based on BMI, D-dimer, neutrophils, and CitH3, we developed a predictive model to predict postoperative DVT incidence in these patients.
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spelling pubmed-97092602022-12-01 A prospective marker for the prediction of postoperative deep venous thrombosis: Neutrophil extracellular traps Li, Yin Jiang, Qinyi Zhou, Xiaohua Wu, Mengyuan Chen, Jian Liu, Hao Dai, Siming Zheng, Ziyang Zhao, Xuan Zhang, Chenxi Shi, Zhuoying Zhang, Haitao Gu, Jinyu Huang, Zhenfei Yin, Guoyong Zhao, Shujie Front Cell Dev Biol Cell and Developmental Biology Deep venous thrombosis (DVT) is a common medical complication in patients with lumbar fractures. The current study aimed to investigate the predictive value of neutrophil extracellular traps (NETs) in postoperative DVT formation in patients with lumbar fractures and to develop a nomogram relating clinical admission information for prediction. Patients who underwent open reduction and pedicle screw internal fixation in the treatment of single-segment lumbar fracture in the Department of Spine Surgery, the First Affiliated Hospital of Nanjing Medical University, from December 2020 to June 2022 were enrolled in this study. Baseline data and laboratory results were collected from enrollees, and the primary study endpoint event was the occurrence of DVT in patients after surgery. Multivariable logistic regression analysis was used to identify risk factors associated with higher odds of DVT after surgery. A nomogram was constructed using the results of the multivariable model. The calibration plot and receiver operating characteristics (ROC) curve were used to show the satisfactory predictive capacity of the model. Of these 393 patients who did not have DVT preoperatively, 79 patients developed it postoperatively, and 314 did not, respectively. Multivariate analysis showed that higher body mass index (BMI) (BMI between 24 and 28: RR = 1.661, 95% CI = 0.891–3.094; BMI ≤28: RR = 5.625, 95% CI = 2.590–12.217; reference: BMI <24), neutrophils (RR = 1.157, 95% CI 1.042–1.285), D-dimer (RR = 1.098, 95% CI 1.000–1.206), and citrullinated histone H3 (CitH3) (RR = 1.043, 95% CI 1.026–1.060) were independent risk factors for postoperative DVT. Using the multivariable analysis, we then constructed a nomogram to predict DVT, which was found to have an area under the curve of 0.757 (95% CI = 0.693–0.820). Calibration plots also showed the satisfied discrimination and calibration of the nomogram. In conclusion, patients with lumbar fractures with postoperative DVT had higher levels of NETs in the circulation preoperatively compared to those without postoperative DVT. Furthermore, based on BMI, D-dimer, neutrophils, and CitH3, we developed a predictive model to predict postoperative DVT incidence in these patients. Frontiers Media S.A. 2022-11-16 /pmc/articles/PMC9709260/ /pubmed/36467414 http://dx.doi.org/10.3389/fcell.2022.1071550 Text en Copyright © 2022 Li, Jiang, Zhou, Wu, Chen, Liu, Dai, Zheng, Zhao, Zhang, Shi, Zhang, Gu, Huang, Yin and Zhao. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cell and Developmental Biology
Li, Yin
Jiang, Qinyi
Zhou, Xiaohua
Wu, Mengyuan
Chen, Jian
Liu, Hao
Dai, Siming
Zheng, Ziyang
Zhao, Xuan
Zhang, Chenxi
Shi, Zhuoying
Zhang, Haitao
Gu, Jinyu
Huang, Zhenfei
Yin, Guoyong
Zhao, Shujie
A prospective marker for the prediction of postoperative deep venous thrombosis: Neutrophil extracellular traps
title A prospective marker for the prediction of postoperative deep venous thrombosis: Neutrophil extracellular traps
title_full A prospective marker for the prediction of postoperative deep venous thrombosis: Neutrophil extracellular traps
title_fullStr A prospective marker for the prediction of postoperative deep venous thrombosis: Neutrophil extracellular traps
title_full_unstemmed A prospective marker for the prediction of postoperative deep venous thrombosis: Neutrophil extracellular traps
title_short A prospective marker for the prediction of postoperative deep venous thrombosis: Neutrophil extracellular traps
title_sort prospective marker for the prediction of postoperative deep venous thrombosis: neutrophil extracellular traps
topic Cell and Developmental Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9709260/
https://www.ncbi.nlm.nih.gov/pubmed/36467414
http://dx.doi.org/10.3389/fcell.2022.1071550
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