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Development and validation of a risk nomogram model for predicting pulmonary hypertension in patients with stage 3–5 chronic kidney disease
OBJECTIVES: The occurrence of pulmonary arterial hypertension (PAH) can greatly affect the prognosis of patients with chronic kidney disease (CKD). We aimed to construct a nomogram to predict the probability of PAH development in patients with stage 3–5 CKD to guide early intervention and to improve...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10105676/ https://www.ncbi.nlm.nih.gov/pubmed/36562902 http://dx.doi.org/10.1007/s11255-022-03431-x |
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author | Hu, Yue Wang, Xiaotong Xiao, Shengjue Wu, Huimin Huan, Chunyan Xu, Tao Guo, Minjia Liu, Ailin Jiang, Xiaoyao Wang, Jia Zhu, Hong Pan, Defeng |
author_facet | Hu, Yue Wang, Xiaotong Xiao, Shengjue Wu, Huimin Huan, Chunyan Xu, Tao Guo, Minjia Liu, Ailin Jiang, Xiaoyao Wang, Jia Zhu, Hong Pan, Defeng |
author_sort | Hu, Yue |
collection | PubMed |
description | OBJECTIVES: The occurrence of pulmonary arterial hypertension (PAH) can greatly affect the prognosis of patients with chronic kidney disease (CKD). We aimed to construct a nomogram to predict the probability of PAH development in patients with stage 3–5 CKD to guide early intervention and to improve prognosis. METHODS: From August 2018 to December 2021, we collected the data of 1258 patients with stage 3–5 CKD hospitalized at the Affiliated Hospital of Xuzhou Medical University as a training set and 389 patients hospitalized at Zhongda Hospital as a validation set. These patients were divided into PAH and N-PAH groups with pulmonary arterial systolic pressure ≥ 35 mmHg as the cutoff. The results of univariate and multivariate logistic regression analyses were used to establish the nomogram. Then, areas under the receiver operating characteristic curve (AUC-ROCs), a calibration plot, and decision curve analysis (DCA) were used to validate the nomogram. RESULTS: The nomogram included nine variables: age, diabetes mellitus, hemoglobin, platelet count, serum creatinine, left ventricular end-diastolic diameter, left atrial diameter, main pulmonary artery diameter and left ventricular ejection fraction. The AUC-ROCs of the training set and validation set were 0.801 (95% confidence interval (CI) 0.771–0.830) and 0.760 (95% CI 0.699–0.818), respectively, which showed good discriminative ability of the nomogram. The calibration diagram showed good agreement between the predicted and observed results. DCA also demonstrated that the nomogram could be clinically useful. CONCLUSION: The evaluation of the nomogram model for predicting PAH in patients with CKD based on risk factors showed its ideal efficacy. Thus, the nomogram can be used to screen for patients at high risk for PAH and has guiding value for the subsequent formulation of prevention strategies and clinical treatment. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11255-022-03431-x. |
format | Online Article Text |
id | pubmed-10105676 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-101056762023-04-17 Development and validation of a risk nomogram model for predicting pulmonary hypertension in patients with stage 3–5 chronic kidney disease Hu, Yue Wang, Xiaotong Xiao, Shengjue Wu, Huimin Huan, Chunyan Xu, Tao Guo, Minjia Liu, Ailin Jiang, Xiaoyao Wang, Jia Zhu, Hong Pan, Defeng Int Urol Nephrol Nephrology - Original Paper OBJECTIVES: The occurrence of pulmonary arterial hypertension (PAH) can greatly affect the prognosis of patients with chronic kidney disease (CKD). We aimed to construct a nomogram to predict the probability of PAH development in patients with stage 3–5 CKD to guide early intervention and to improve prognosis. METHODS: From August 2018 to December 2021, we collected the data of 1258 patients with stage 3–5 CKD hospitalized at the Affiliated Hospital of Xuzhou Medical University as a training set and 389 patients hospitalized at Zhongda Hospital as a validation set. These patients were divided into PAH and N-PAH groups with pulmonary arterial systolic pressure ≥ 35 mmHg as the cutoff. The results of univariate and multivariate logistic regression analyses were used to establish the nomogram. Then, areas under the receiver operating characteristic curve (AUC-ROCs), a calibration plot, and decision curve analysis (DCA) were used to validate the nomogram. RESULTS: The nomogram included nine variables: age, diabetes mellitus, hemoglobin, platelet count, serum creatinine, left ventricular end-diastolic diameter, left atrial diameter, main pulmonary artery diameter and left ventricular ejection fraction. The AUC-ROCs of the training set and validation set were 0.801 (95% confidence interval (CI) 0.771–0.830) and 0.760 (95% CI 0.699–0.818), respectively, which showed good discriminative ability of the nomogram. The calibration diagram showed good agreement between the predicted and observed results. DCA also demonstrated that the nomogram could be clinically useful. CONCLUSION: The evaluation of the nomogram model for predicting PAH in patients with CKD based on risk factors showed its ideal efficacy. Thus, the nomogram can be used to screen for patients at high risk for PAH and has guiding value for the subsequent formulation of prevention strategies and clinical treatment. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11255-022-03431-x. Springer Netherlands 2022-12-23 2023 /pmc/articles/PMC10105676/ /pubmed/36562902 http://dx.doi.org/10.1007/s11255-022-03431-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Nephrology - Original Paper Hu, Yue Wang, Xiaotong Xiao, Shengjue Wu, Huimin Huan, Chunyan Xu, Tao Guo, Minjia Liu, Ailin Jiang, Xiaoyao Wang, Jia Zhu, Hong Pan, Defeng Development and validation of a risk nomogram model for predicting pulmonary hypertension in patients with stage 3–5 chronic kidney disease |
title | Development and validation of a risk nomogram model for predicting pulmonary hypertension in patients with stage 3–5 chronic kidney disease |
title_full | Development and validation of a risk nomogram model for predicting pulmonary hypertension in patients with stage 3–5 chronic kidney disease |
title_fullStr | Development and validation of a risk nomogram model for predicting pulmonary hypertension in patients with stage 3–5 chronic kidney disease |
title_full_unstemmed | Development and validation of a risk nomogram model for predicting pulmonary hypertension in patients with stage 3–5 chronic kidney disease |
title_short | Development and validation of a risk nomogram model for predicting pulmonary hypertension in patients with stage 3–5 chronic kidney disease |
title_sort | development and validation of a risk nomogram model for predicting pulmonary hypertension in patients with stage 3–5 chronic kidney disease |
topic | Nephrology - Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10105676/ https://www.ncbi.nlm.nih.gov/pubmed/36562902 http://dx.doi.org/10.1007/s11255-022-03431-x |
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