Developing a Nomogram-Based Scoring Tool to Estimate the Risk of Pulmonary Embolism

Qiao Zhou,* Xing-Yu Xiong,* Zong-An Liang Department of Respiratory and Critical Care Medicine, West China Hospital of Sichuan University, Chengdu, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zong-An Liang, Email liangza@scu.edu.cn...

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Main Authors: Zhou Q, Xiong XY, Liang ZA
Format: Article
Language:English
Published: Dove Medical Press 2022-04-01
Series:International Journal of General Medicine
Subjects:
Online Access:https://www.dovepress.com/developing-a-nomogram-based-scoring-tool-to-estimate-the-risk-of-pulmo-peer-reviewed-fulltext-article-IJGM
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author Zhou Q
Xiong XY
Liang ZA
author_facet Zhou Q
Xiong XY
Liang ZA
author_sort Zhou Q
collection DOAJ
description Qiao Zhou,&ast; Xing-Yu Xiong,&ast; Zong-An Liang Department of Respiratory and Critical Care Medicine, West China Hospital of Sichuan University, Chengdu, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Zong-An Liang, Email liangza@scu.edu.cnBackground: Pulmonary embolisms (PEs) are clinically challenging because of their high morbidity and mortality. This study aimed to develop a scoring tool for predicting PEs to improve their clinical management.Methods: Clinical, laboratory, and imaging parameters were retrospectively collected from suspected PE patients who had cough or chest pain and were hospitalized in West China Hospital of Sichuan University from May 2015 to April 2020. The final diagnosis of PE was defined based on findings from computed tomographic pulmonary angiography (CTPA). In this study, patients were randomly divided 2:1 into derivation and validation cohorts, which were used to create and validate, respectively, a nomogram. Model performance was estimated with the area under the receiver operating characteristic curve and a calibration curve.Results: Our study incorporated data on more than 100 features from 1480 patients (811 non-PE, 669 PE). The nomogram was constructed using important predictive features including D-dimer, APTT, FDP, platelet count, sodium, albumin and cholesterol and achieved AUC values of 0.692 with the derivation cohort (95% CI 0.688– 0.696, P < 0.01) and 0.688 with the validation cohort (95% CI 0.653– 0.723, P < 0.01). The calibration curve showed good agreement between the probability predicted by the nomogram and the actual probability.Conclusion: In this study, we successfully developed a nomogram that can predict the risk of PE, which can not only improve the clinical management of PE patients but also decrease unnecessary CTPA scans and their adverse effects.Keywords: pulmonary embolism, clinical management, nomogram, risk-scoring tool
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spelling doaj.art-788337b3fad84928a5546e471d734aca2022-12-22T03:13:59ZengDove Medical PressInternational Journal of General Medicine1178-70742022-04-01Volume 153687369774211Developing a Nomogram-Based Scoring Tool to Estimate the Risk of Pulmonary EmbolismZhou QXiong XYLiang ZAQiao Zhou,&ast; Xing-Yu Xiong,&ast; Zong-An Liang Department of Respiratory and Critical Care Medicine, West China Hospital of Sichuan University, Chengdu, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Zong-An Liang, Email liangza@scu.edu.cnBackground: Pulmonary embolisms (PEs) are clinically challenging because of their high morbidity and mortality. This study aimed to develop a scoring tool for predicting PEs to improve their clinical management.Methods: Clinical, laboratory, and imaging parameters were retrospectively collected from suspected PE patients who had cough or chest pain and were hospitalized in West China Hospital of Sichuan University from May 2015 to April 2020. The final diagnosis of PE was defined based on findings from computed tomographic pulmonary angiography (CTPA). In this study, patients were randomly divided 2:1 into derivation and validation cohorts, which were used to create and validate, respectively, a nomogram. Model performance was estimated with the area under the receiver operating characteristic curve and a calibration curve.Results: Our study incorporated data on more than 100 features from 1480 patients (811 non-PE, 669 PE). The nomogram was constructed using important predictive features including D-dimer, APTT, FDP, platelet count, sodium, albumin and cholesterol and achieved AUC values of 0.692 with the derivation cohort (95% CI 0.688– 0.696, P < 0.01) and 0.688 with the validation cohort (95% CI 0.653– 0.723, P < 0.01). The calibration curve showed good agreement between the probability predicted by the nomogram and the actual probability.Conclusion: In this study, we successfully developed a nomogram that can predict the risk of PE, which can not only improve the clinical management of PE patients but also decrease unnecessary CTPA scans and their adverse effects.Keywords: pulmonary embolism, clinical management, nomogram, risk-scoring toolhttps://www.dovepress.com/developing-a-nomogram-based-scoring-tool-to-estimate-the-risk-of-pulmo-peer-reviewed-fulltext-article-IJGMpulmonary embolismclinical managementnomogramrisk-scoring tool
spellingShingle Zhou Q
Xiong XY
Liang ZA
Developing a Nomogram-Based Scoring Tool to Estimate the Risk of Pulmonary Embolism
International Journal of General Medicine
pulmonary embolism
clinical management
nomogram
risk-scoring tool
title Developing a Nomogram-Based Scoring Tool to Estimate the Risk of Pulmonary Embolism
title_full Developing a Nomogram-Based Scoring Tool to Estimate the Risk of Pulmonary Embolism
title_fullStr Developing a Nomogram-Based Scoring Tool to Estimate the Risk of Pulmonary Embolism
title_full_unstemmed Developing a Nomogram-Based Scoring Tool to Estimate the Risk of Pulmonary Embolism
title_short Developing a Nomogram-Based Scoring Tool to Estimate the Risk of Pulmonary Embolism
title_sort developing a nomogram based scoring tool to estimate the risk of pulmonary embolism
topic pulmonary embolism
clinical management
nomogram
risk-scoring tool
url https://www.dovepress.com/developing-a-nomogram-based-scoring-tool-to-estimate-the-risk-of-pulmo-peer-reviewed-fulltext-article-IJGM
work_keys_str_mv AT zhouq developinganomogrambasedscoringtooltoestimatetheriskofpulmonaryembolism
AT xiongxy developinganomogrambasedscoringtooltoestimatetheriskofpulmonaryembolism
AT liangza developinganomogrambasedscoringtooltoestimatetheriskofpulmonaryembolism