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Predicting deep surgical site infection in patients receiving open posterior instrumented thoracolumbar surgery: A-DOUBLE-SSI risk score – a large retrospective multicenter cohort study in China

BACKGROUND: To develop a practical prediction model to predict the risk of deep surgical site infection (SSI) in patients receiving open posterior instrumented thoracolumbar surgery. METHODS: Data of 3419 patients in four hospitals from 1 January 2012 to 30 December 2021 were evaluated. The authors...

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Autores principales: Cheng, Lei, Liu, Jiesheng, Lian, Liyi, Duan, Wanru, Guan, Jian, Wang, Kai, Liu, Zhenlei, Wang, Xingwen, Wang, Zuowei, Wu, Hao, Chen, Zan, Wang, Jianzhen, Jian, Fengzeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10442129/
https://www.ncbi.nlm.nih.gov/pubmed/37204435
http://dx.doi.org/10.1097/JS9.0000000000000461
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author Cheng, Lei
Liu, Jiesheng
Lian, Liyi
Duan, Wanru
Guan, Jian
Wang, Kai
Liu, Zhenlei
Wang, Xingwen
Wang, Zuowei
Wu, Hao
Chen, Zan
Wang, Jianzhen
Jian, Fengzeng
author_facet Cheng, Lei
Liu, Jiesheng
Lian, Liyi
Duan, Wanru
Guan, Jian
Wang, Kai
Liu, Zhenlei
Wang, Xingwen
Wang, Zuowei
Wu, Hao
Chen, Zan
Wang, Jianzhen
Jian, Fengzeng
author_sort Cheng, Lei
collection PubMed
description BACKGROUND: To develop a practical prediction model to predict the risk of deep surgical site infection (SSI) in patients receiving open posterior instrumented thoracolumbar surgery. METHODS: Data of 3419 patients in four hospitals from 1 January 2012 to 30 December 2021 were evaluated. The authors used clinical knowledge-driven, data-driven, and decision tree model to identify predictive variables of deep SSI. Forty-three candidate variables were collected, including 5 demographics, 29 preoperative, 5 intraoperative, and 4 postoperative variables. According to model performance and clinical practicability, the best model was chosen to develop a risk score. Internal validation was performed by using bootstrapping methods. RESULTS: After open posterior instrumented thoracolumbar surgery, 158 patients (4.6%) developed deep SSI. The clinical knowledge-driven model yielded 12 predictors of deep SSI, while the data-driven and decision tree model produced 11 and 6 predictors, respectively. A knowledge-driven model, which had the best C-statistics [0.81 (95% CI: 0.78–0.85)] and superior calibration, was chosen due to its favorable model performance and clinical practicality. Moreover, 12 variables were identified in the clinical knowledge-driven model, including age, BMI, diabetes, steroid use, albumin, duration of operation, blood loss, instrumented segments, powdered vancomycin administration, duration of drainage, postoperative cerebrospinal fluid leakage, and early postoperative activities. In bootstrap internal validation, the knowledge-driven model still showed optimal C-statistics (0.79, 95% CI: 0.75–0.83) and calibration. Based on these identified predictors, a risk score for deep SSI incidence was created: the A-DOUBLE-SSI (Age, D [Diabetes, Drainage], O [duration of Operation, vancOmycin], albUmin, B [BMI, Blood loss], cerebrospinal fluid Leakage, Early activities, Steroid use, and Segmental Instrumentation) risk score. Based on the A-DOUBLE-SSI score system, the incidence of deep SSI increased in a graded fashion from 1.06% (A-DOUBLE-SSIs score ≤8) to 40.6% (A-DOUBLE-SSIs score>15). CONCLUSIONS: The authors developed a novel and practical model, the A-DOUBLE-SSIs risk score, that integrated easily accessible demographics, preoperative, intraoperative, and postoperative variables and could be used to predict individual risk of deep SSI in patients receiving open posterior instrumented thoracolumbar surgery.
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spelling pubmed-104421292023-08-22 Predicting deep surgical site infection in patients receiving open posterior instrumented thoracolumbar surgery: A-DOUBLE-SSI risk score – a large retrospective multicenter cohort study in China Cheng, Lei Liu, Jiesheng Lian, Liyi Duan, Wanru Guan, Jian Wang, Kai Liu, Zhenlei Wang, Xingwen Wang, Zuowei Wu, Hao Chen, Zan Wang, Jianzhen Jian, Fengzeng Int J Surg Original Research BACKGROUND: To develop a practical prediction model to predict the risk of deep surgical site infection (SSI) in patients receiving open posterior instrumented thoracolumbar surgery. METHODS: Data of 3419 patients in four hospitals from 1 January 2012 to 30 December 2021 were evaluated. The authors used clinical knowledge-driven, data-driven, and decision tree model to identify predictive variables of deep SSI. Forty-three candidate variables were collected, including 5 demographics, 29 preoperative, 5 intraoperative, and 4 postoperative variables. According to model performance and clinical practicability, the best model was chosen to develop a risk score. Internal validation was performed by using bootstrapping methods. RESULTS: After open posterior instrumented thoracolumbar surgery, 158 patients (4.6%) developed deep SSI. The clinical knowledge-driven model yielded 12 predictors of deep SSI, while the data-driven and decision tree model produced 11 and 6 predictors, respectively. A knowledge-driven model, which had the best C-statistics [0.81 (95% CI: 0.78–0.85)] and superior calibration, was chosen due to its favorable model performance and clinical practicality. Moreover, 12 variables were identified in the clinical knowledge-driven model, including age, BMI, diabetes, steroid use, albumin, duration of operation, blood loss, instrumented segments, powdered vancomycin administration, duration of drainage, postoperative cerebrospinal fluid leakage, and early postoperative activities. In bootstrap internal validation, the knowledge-driven model still showed optimal C-statistics (0.79, 95% CI: 0.75–0.83) and calibration. Based on these identified predictors, a risk score for deep SSI incidence was created: the A-DOUBLE-SSI (Age, D [Diabetes, Drainage], O [duration of Operation, vancOmycin], albUmin, B [BMI, Blood loss], cerebrospinal fluid Leakage, Early activities, Steroid use, and Segmental Instrumentation) risk score. Based on the A-DOUBLE-SSI score system, the incidence of deep SSI increased in a graded fashion from 1.06% (A-DOUBLE-SSIs score ≤8) to 40.6% (A-DOUBLE-SSIs score>15). CONCLUSIONS: The authors developed a novel and practical model, the A-DOUBLE-SSIs risk score, that integrated easily accessible demographics, preoperative, intraoperative, and postoperative variables and could be used to predict individual risk of deep SSI in patients receiving open posterior instrumented thoracolumbar surgery. Lippincott Williams & Wilkins 2023-05-18 /pmc/articles/PMC10442129/ /pubmed/37204435 http://dx.doi.org/10.1097/JS9.0000000000000461 Text en Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/)
spellingShingle Original Research
Cheng, Lei
Liu, Jiesheng
Lian, Liyi
Duan, Wanru
Guan, Jian
Wang, Kai
Liu, Zhenlei
Wang, Xingwen
Wang, Zuowei
Wu, Hao
Chen, Zan
Wang, Jianzhen
Jian, Fengzeng
Predicting deep surgical site infection in patients receiving open posterior instrumented thoracolumbar surgery: A-DOUBLE-SSI risk score – a large retrospective multicenter cohort study in China
title Predicting deep surgical site infection in patients receiving open posterior instrumented thoracolumbar surgery: A-DOUBLE-SSI risk score – a large retrospective multicenter cohort study in China
title_full Predicting deep surgical site infection in patients receiving open posterior instrumented thoracolumbar surgery: A-DOUBLE-SSI risk score – a large retrospective multicenter cohort study in China
title_fullStr Predicting deep surgical site infection in patients receiving open posterior instrumented thoracolumbar surgery: A-DOUBLE-SSI risk score – a large retrospective multicenter cohort study in China
title_full_unstemmed Predicting deep surgical site infection in patients receiving open posterior instrumented thoracolumbar surgery: A-DOUBLE-SSI risk score – a large retrospective multicenter cohort study in China
title_short Predicting deep surgical site infection in patients receiving open posterior instrumented thoracolumbar surgery: A-DOUBLE-SSI risk score – a large retrospective multicenter cohort study in China
title_sort predicting deep surgical site infection in patients receiving open posterior instrumented thoracolumbar surgery: a-double-ssi risk score – a large retrospective multicenter cohort study in china
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10442129/
https://www.ncbi.nlm.nih.gov/pubmed/37204435
http://dx.doi.org/10.1097/JS9.0000000000000461
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