Development and validation of a novel risk assessment model to estimate the probability of pulmonary embolism in postoperative patients

Abstract Pulmonary embolism (PE) is a leading cause of mortality in postoperative patients. Numerous PE prevention clinical practice guidelines are available but not consistently implemented. This study aimed to develop and validate a novel risk assessment model to assess the risk of PE in postopera...

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Autores principales:	Mao-feng Wang, Fei-xiang Li, Lan-fang Feng, Chao-nan Zhu, Shuang-yan Fang, Cai-min Su, Qiong-fang Yang, Qiao-ying Ji, Wei-min Li
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/ecf759f55f03434f9d44ee81d1198c08
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spelling	oai:doaj.org-article:ecf759f55f03434f9d44ee81d1198c082021-12-02T19:12:28ZDevelopment and validation of a novel risk assessment model to estimate the probability of pulmonary embolism in postoperative patients10.1038/s41598-021-97638-02045-2322https://doaj.org/article/ecf759f55f03434f9d44ee81d1198c082021-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-97638-0https://doaj.org/toc/2045-2322Abstract Pulmonary embolism (PE) is a leading cause of mortality in postoperative patients. Numerous PE prevention clinical practice guidelines are available but not consistently implemented. This study aimed to develop and validate a novel risk assessment model to assess the risk of PE in postoperative patients. Patients who underwent Grade IV surgery between September 2012 and January 2020 (n = 26,536) at the Affiliated Dongyang Hospital of Wenzhou Medical University were enrolled in our study. PE was confirmed by an identified filling defect in the pulmonary artery system in CT pulmonary angiography. The PE incidence was evaluated before discharge. All preoperative data containing clinical and laboratory variables were extracted for each participant. A novel risk assessment model (RAM) for PE was developed with multivariate regression analysis. The discrimination ability of the RAM was evaluated by the area under the receiver operating characteristic curve, and model calibration was assessed by the Hosmer–Lemeshow statistic. We included 53 clinical and laboratory variables in this study. Among them, 296 postoperative patients developed PE before discharge, and the incidence rate was 1.04%. The distribution of variables between the training group and the validation group was balanced. After using multivariate stepwise regression, only variable age (OR 1.070 [1.054–1.087], P < 0.001), drinking (OR 0.477 [0.304–0.749], P = 0.001), malignant tumor (OR 2.552 [1.745–3.731], P < 0.001), anticoagulant (OR 3.719 [2.281–6.062], P < 0.001), lymphocyte percentage (OR 2.773 [2.342–3.285], P < 0.001), neutrophil percentage (OR 10.703 [8.337–13.739], P < 0.001), red blood cell (OR 1.872 [1.384–2.532], P < 0.001), total bilirubin (OR 1.038 [1.012–1.064], P < 0.001), direct bilirubin (OR 0.850 [0.779–0.928], P < 0.001), prothrombin time (OR 0.768 [0.636–0.926], P < 0.001) and fibrinogen (OR 0.772 [0.651–0.915], P < 0.001) were selected and significantly associated with PE. The final model included four variables: neutrophil percentage, age, malignant tumor and lymphocyte percentage. The AUC of the model was 0.949 (95% CI 0.932–0.966). The risk prediction model still showed good calibration, with reasonable agreement between the observed and predicted PE outcomes in the validation set (AUC 0.958). The information on sensitivity, specificity and predictive values according to cutoff points of the score in the training set suggested a threshold of 0.012 as the optimal cutoff value to define high-risk individuals. We developed a new approach to select hazard factors for PE in postoperative patients. This tool provided a consistent, accurate, and effective method for risk assessment. This finding may help decision-makers weigh the risk of PE and appropriately select PE prevention strategies.Mao-feng WangFei-xiang LiLan-fang FengChao-nan ZhuShuang-yan FangCai-min SuQiong-fang YangQiao-ying JiWei-min LiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Mao-feng Wang Fei-xiang Li Lan-fang Feng Chao-nan Zhu Shuang-yan Fang Cai-min Su Qiong-fang Yang Qiao-ying Ji Wei-min Li Development and validation of a novel risk assessment model to estimate the probability of pulmonary embolism in postoperative patients
description	Abstract Pulmonary embolism (PE) is a leading cause of mortality in postoperative patients. Numerous PE prevention clinical practice guidelines are available but not consistently implemented. This study aimed to develop and validate a novel risk assessment model to assess the risk of PE in postoperative patients. Patients who underwent Grade IV surgery between September 2012 and January 2020 (n = 26,536) at the Affiliated Dongyang Hospital of Wenzhou Medical University were enrolled in our study. PE was confirmed by an identified filling defect in the pulmonary artery system in CT pulmonary angiography. The PE incidence was evaluated before discharge. All preoperative data containing clinical and laboratory variables were extracted for each participant. A novel risk assessment model (RAM) for PE was developed with multivariate regression analysis. The discrimination ability of the RAM was evaluated by the area under the receiver operating characteristic curve, and model calibration was assessed by the Hosmer–Lemeshow statistic. We included 53 clinical and laboratory variables in this study. Among them, 296 postoperative patients developed PE before discharge, and the incidence rate was 1.04%. The distribution of variables between the training group and the validation group was balanced. After using multivariate stepwise regression, only variable age (OR 1.070 [1.054–1.087], P < 0.001), drinking (OR 0.477 [0.304–0.749], P = 0.001), malignant tumor (OR 2.552 [1.745–3.731], P < 0.001), anticoagulant (OR 3.719 [2.281–6.062], P < 0.001), lymphocyte percentage (OR 2.773 [2.342–3.285], P < 0.001), neutrophil percentage (OR 10.703 [8.337–13.739], P < 0.001), red blood cell (OR 1.872 [1.384–2.532], P < 0.001), total bilirubin (OR 1.038 [1.012–1.064], P < 0.001), direct bilirubin (OR 0.850 [0.779–0.928], P < 0.001), prothrombin time (OR 0.768 [0.636–0.926], P < 0.001) and fibrinogen (OR 0.772 [0.651–0.915], P < 0.001) were selected and significantly associated with PE. The final model included four variables: neutrophil percentage, age, malignant tumor and lymphocyte percentage. The AUC of the model was 0.949 (95% CI 0.932–0.966). The risk prediction model still showed good calibration, with reasonable agreement between the observed and predicted PE outcomes in the validation set (AUC 0.958). The information on sensitivity, specificity and predictive values according to cutoff points of the score in the training set suggested a threshold of 0.012 as the optimal cutoff value to define high-risk individuals. We developed a new approach to select hazard factors for PE in postoperative patients. This tool provided a consistent, accurate, and effective method for risk assessment. This finding may help decision-makers weigh the risk of PE and appropriately select PE prevention strategies.
format	article
author	Mao-feng Wang Fei-xiang Li Lan-fang Feng Chao-nan Zhu Shuang-yan Fang Cai-min Su Qiong-fang Yang Qiao-ying Ji Wei-min Li
author_facet	Mao-feng Wang Fei-xiang Li Lan-fang Feng Chao-nan Zhu Shuang-yan Fang Cai-min Su Qiong-fang Yang Qiao-ying Ji Wei-min Li
author_sort	Mao-feng Wang
title	Development and validation of a novel risk assessment model to estimate the probability of pulmonary embolism in postoperative patients
title_short	Development and validation of a novel risk assessment model to estimate the probability of pulmonary embolism in postoperative patients
title_full	Development and validation of a novel risk assessment model to estimate the probability of pulmonary embolism in postoperative patients
title_fullStr	Development and validation of a novel risk assessment model to estimate the probability of pulmonary embolism in postoperative patients
title_full_unstemmed	Development and validation of a novel risk assessment model to estimate the probability of pulmonary embolism in postoperative patients
title_sort	development and validation of a novel risk assessment model to estimate the probability of pulmonary embolism in postoperative patients
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/ecf759f55f03434f9d44ee81d1198c08
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Development and validation of a novel risk assessment model to estimate the probability of pulmonary embolism in postoperative patients

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