A Nomogram for Predicting the Risk of Pulmonary Hypertension for Patients with Chronic Obstructive Pulmonary Disease
Ning Wang,1,2 Zhenjiang Guo,3 Xiaowei Gong,1 Shiwei Kang,1 Zhaobo Cui,2 Yadong Yuan1 1Department of Respiratory and Critical Care Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, People’s Republic of China; 2Department of Respiratory and Critical Care Medicine, Hengshui Peopl...
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| Format: | Article |
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Dove Medical Press
2022-06-01
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| Series: | International Journal of General Medicine |
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| Online Access: | https://www.dovepress.com/a-nomogram-for-predicting-the-risk-of-pulmonary-hypertension-for-patie-peer-reviewed-fulltext-article-IJGM |
| _version_ | 1811240872091582464 |
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| author | Wang N Guo Z Gong X Kang S Cui Z Yuan Y |
| author_facet | Wang N Guo Z Gong X Kang S Cui Z Yuan Y |
| author_sort | Wang N |
| collection | DOAJ |
| description | Ning Wang,1,2 Zhenjiang Guo,3 Xiaowei Gong,1 Shiwei Kang,1 Zhaobo Cui,2 Yadong Yuan1 1Department of Respiratory and Critical Care Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, People’s Republic of China; 2Department of Respiratory and Critical Care Medicine, Hengshui People’s Hospital, Hengshui, People’s Republic of China; 3Department of Gastrointestinal Surgery, Hengshui People’s Hospital, Hengshui, People’s Republic of ChinaCorrespondence: Yadong Yuan, Department of Respiratory and Critical Care Medicine, The Second Hospital of Hebei Medical University, No. 215 Heping West Road, Shijiazhuang, Hebei, 050000, People’s Republic of China, Tel/Fax +86-311-66003989, Email yuanyd1108@163.comBackground: Pulmonary hypertension (PH) is a life-threatening complication of chronic obstructive pulmonary disease (COPD). Timely diagnosis of PH in COPD patients is vital to achieve proper treatment; however, there is no algorithm to identify those at high risk. We aimed to develop a predictive model for PH in patients with COPD that provides individualized risk estimates.Methods: A total of 527 patients with COPD who were admitted to our hospital between May 2019 and December 2020 were retrospectively enrolled in this study. Using echocardiographic results as a standard, patients were stratified into a moderate- or high-PH probability group and a low-PH probability group. They were randomly grouped into either the training set (n = 368 patients) or validation set (n = 159 patients) in a ratio of 7:3. We utilized the least absolute shrinkage and selection operator (LASSO) regression model to select the feature variables. The characteristic variables selected in the LASSO regression were analyzed using multivariable logistic regression to construct the predictive model. The predictive model was displayed using a nomogram. We used the receiver operating characteristic curve, calibration curve, and clinical decision curve analysis (DCA) to evaluate model performance, and internal validation was assessed.Results: The predictive factors included in the prediction model were Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage, emphysema, PaCO2, NT-pro-BNP, red blood cell (RBC) distribution width-standard deviation (RDW-SD), and neutrophil/lymphocyte ratio (NLR). The predictive model yielded an area under the curve (AUC) of 0.770 (95% confidence interval [CI], 0.719– 0.820); in the internal validation, the AUC was 0.741 (95% CI, 0.659– 0.823). The predictive model was well calibrated, and the DCA showed that the proposed nomogram had strong clinical applicability.Conclusion: This study showed that a simple nomogram could be used to calculate the risk of PH in patients with COPD which can be useful for the individualized clinical management of COPD patients who may be occur with PH. Further studies need to be confirmed by larger sample sizes and validated in the stable COPD population.Keywords: chronic obstructive pulmonary disease, pulmonary hypertension, nomogram, LASSO regression |
| first_indexed | 2024-04-12T13:27:32Z |
| format | Article |
| id | doaj.art-aa478017a9024d98887dd2bcbd3ee198 |
| institution | Directory Open Access Journal |
| issn | 1178-7074 |
| language | English |
| last_indexed | 2024-04-12T13:27:32Z |
| publishDate | 2022-06-01 |
| publisher | Dove Medical Press |
| record_format | Article |
| series | International Journal of General Medicine |
| spelling | doaj.art-aa478017a9024d98887dd2bcbd3ee1982022-12-22T03:31:16ZengDove Medical PressInternational Journal of General Medicine1178-70742022-06-01Volume 155751576276105A Nomogram for Predicting the Risk of Pulmonary Hypertension for Patients with Chronic Obstructive Pulmonary DiseaseWang NGuo ZGong XKang SCui ZYuan YNing Wang,1,2 Zhenjiang Guo,3 Xiaowei Gong,1 Shiwei Kang,1 Zhaobo Cui,2 Yadong Yuan1 1Department of Respiratory and Critical Care Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, People’s Republic of China; 2Department of Respiratory and Critical Care Medicine, Hengshui People’s Hospital, Hengshui, People’s Republic of China; 3Department of Gastrointestinal Surgery, Hengshui People’s Hospital, Hengshui, People’s Republic of ChinaCorrespondence: Yadong Yuan, Department of Respiratory and Critical Care Medicine, The Second Hospital of Hebei Medical University, No. 215 Heping West Road, Shijiazhuang, Hebei, 050000, People’s Republic of China, Tel/Fax +86-311-66003989, Email yuanyd1108@163.comBackground: Pulmonary hypertension (PH) is a life-threatening complication of chronic obstructive pulmonary disease (COPD). Timely diagnosis of PH in COPD patients is vital to achieve proper treatment; however, there is no algorithm to identify those at high risk. We aimed to develop a predictive model for PH in patients with COPD that provides individualized risk estimates.Methods: A total of 527 patients with COPD who were admitted to our hospital between May 2019 and December 2020 were retrospectively enrolled in this study. Using echocardiographic results as a standard, patients were stratified into a moderate- or high-PH probability group and a low-PH probability group. They were randomly grouped into either the training set (n = 368 patients) or validation set (n = 159 patients) in a ratio of 7:3. We utilized the least absolute shrinkage and selection operator (LASSO) regression model to select the feature variables. The characteristic variables selected in the LASSO regression were analyzed using multivariable logistic regression to construct the predictive model. The predictive model was displayed using a nomogram. We used the receiver operating characteristic curve, calibration curve, and clinical decision curve analysis (DCA) to evaluate model performance, and internal validation was assessed.Results: The predictive factors included in the prediction model were Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage, emphysema, PaCO2, NT-pro-BNP, red blood cell (RBC) distribution width-standard deviation (RDW-SD), and neutrophil/lymphocyte ratio (NLR). The predictive model yielded an area under the curve (AUC) of 0.770 (95% confidence interval [CI], 0.719– 0.820); in the internal validation, the AUC was 0.741 (95% CI, 0.659– 0.823). The predictive model was well calibrated, and the DCA showed that the proposed nomogram had strong clinical applicability.Conclusion: This study showed that a simple nomogram could be used to calculate the risk of PH in patients with COPD which can be useful for the individualized clinical management of COPD patients who may be occur with PH. Further studies need to be confirmed by larger sample sizes and validated in the stable COPD population.Keywords: chronic obstructive pulmonary disease, pulmonary hypertension, nomogram, LASSO regressionhttps://www.dovepress.com/a-nomogram-for-predicting-the-risk-of-pulmonary-hypertension-for-patie-peer-reviewed-fulltext-article-IJGMchronic obstructive pulmonary diseasepulmonary hypertensionnomogramlasso regression |
| spellingShingle | Wang N Guo Z Gong X Kang S Cui Z Yuan Y A Nomogram for Predicting the Risk of Pulmonary Hypertension for Patients with Chronic Obstructive Pulmonary Disease International Journal of General Medicine chronic obstructive pulmonary disease pulmonary hypertension nomogram lasso regression |
| title | A Nomogram for Predicting the Risk of Pulmonary Hypertension for Patients with Chronic Obstructive Pulmonary Disease |
| title_full | A Nomogram for Predicting the Risk of Pulmonary Hypertension for Patients with Chronic Obstructive Pulmonary Disease |
| title_fullStr | A Nomogram for Predicting the Risk of Pulmonary Hypertension for Patients with Chronic Obstructive Pulmonary Disease |
| title_full_unstemmed | A Nomogram for Predicting the Risk of Pulmonary Hypertension for Patients with Chronic Obstructive Pulmonary Disease |
| title_short | A Nomogram for Predicting the Risk of Pulmonary Hypertension for Patients with Chronic Obstructive Pulmonary Disease |
| title_sort | nomogram for predicting the risk of pulmonary hypertension for patients with chronic obstructive pulmonary disease |
| topic | chronic obstructive pulmonary disease pulmonary hypertension nomogram lasso regression |
| url | https://www.dovepress.com/a-nomogram-for-predicting-the-risk-of-pulmonary-hypertension-for-patie-peer-reviewed-fulltext-article-IJGM |
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