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Predictive model of diabetes mellitus in patients with idiopathic inflammatory myopathies
OBJECTIVES: Cardiovascular diseases are the common cause of death in patients with idiopathic inflammatory myopathies (IIMs). Diabetes mellitus was associated with higher cardiovascular mortality, but few studies focused on the risk of diabetes mellitus in IIMs patients. Our study is aimed at develo...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10150103/ https://www.ncbi.nlm.nih.gov/pubmed/37139334 http://dx.doi.org/10.3389/fendo.2023.1118620 |
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author | Nie, Qiong Qin, Li Yan, Wei Luo, Qiang Ying, Tao Wang, Han Wu, Jing |
author_facet | Nie, Qiong Qin, Li Yan, Wei Luo, Qiang Ying, Tao Wang, Han Wu, Jing |
author_sort | Nie, Qiong |
collection | PubMed |
description | OBJECTIVES: Cardiovascular diseases are the common cause of death in patients with idiopathic inflammatory myopathies (IIMs). Diabetes mellitus was associated with higher cardiovascular mortality, but few studies focused on the risk of diabetes mellitus in IIMs patients. Our study is aimed at developing a predictive model of diabetes mellitus in IIMs patients. METHODS: A total of 354 patients were included in this study, of whom 35 (9.9%) were diagnosed as new-onset diabetes mellitus. The predictive nomogram was drawn based on the features selected by least absolute shrinkage and selection operator (LASSO) regression, univariate logistic regression, multivariable logistic regression, and clinical relationship. The discriminative capacity of the nomogram was assessed by C-index, calibration plot, and clinical usefulness. The predictive model was verified by the bootstrapping validation. RESULTS: The nomogram mainly included predictors such as age, gender, hypertension, uric acid, and serum creatinine. This predictive model demonstrated good discrimination and calibration in primary cohort (C-index=0.762, 95% CI: 0.677-0.847) and validation cohort (C-index=0.725). Decision curve analysis indicated that this predictive model was clinically useful. CONCLUSIONS: Clinicians can assess the risk of diabetes mellitus in IIMs patients by using this prediction model, and preventive measures should be taken early for high-risk patients, ultimately reducing the adverse cardiovascular prognosis. |
format | Online Article Text |
id | pubmed-10150103 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-101501032023-05-02 Predictive model of diabetes mellitus in patients with idiopathic inflammatory myopathies Nie, Qiong Qin, Li Yan, Wei Luo, Qiang Ying, Tao Wang, Han Wu, Jing Front Endocrinol (Lausanne) Endocrinology OBJECTIVES: Cardiovascular diseases are the common cause of death in patients with idiopathic inflammatory myopathies (IIMs). Diabetes mellitus was associated with higher cardiovascular mortality, but few studies focused on the risk of diabetes mellitus in IIMs patients. Our study is aimed at developing a predictive model of diabetes mellitus in IIMs patients. METHODS: A total of 354 patients were included in this study, of whom 35 (9.9%) were diagnosed as new-onset diabetes mellitus. The predictive nomogram was drawn based on the features selected by least absolute shrinkage and selection operator (LASSO) regression, univariate logistic regression, multivariable logistic regression, and clinical relationship. The discriminative capacity of the nomogram was assessed by C-index, calibration plot, and clinical usefulness. The predictive model was verified by the bootstrapping validation. RESULTS: The nomogram mainly included predictors such as age, gender, hypertension, uric acid, and serum creatinine. This predictive model demonstrated good discrimination and calibration in primary cohort (C-index=0.762, 95% CI: 0.677-0.847) and validation cohort (C-index=0.725). Decision curve analysis indicated that this predictive model was clinically useful. CONCLUSIONS: Clinicians can assess the risk of diabetes mellitus in IIMs patients by using this prediction model, and preventive measures should be taken early for high-risk patients, ultimately reducing the adverse cardiovascular prognosis. Frontiers Media S.A. 2023-04-17 /pmc/articles/PMC10150103/ /pubmed/37139334 http://dx.doi.org/10.3389/fendo.2023.1118620 Text en Copyright © 2023 Nie, Qin, Yan, Luo, Ying, Wang and Wu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Endocrinology Nie, Qiong Qin, Li Yan, Wei Luo, Qiang Ying, Tao Wang, Han Wu, Jing Predictive model of diabetes mellitus in patients with idiopathic inflammatory myopathies |
title | Predictive model of diabetes mellitus in patients with idiopathic inflammatory myopathies |
title_full | Predictive model of diabetes mellitus in patients with idiopathic inflammatory myopathies |
title_fullStr | Predictive model of diabetes mellitus in patients with idiopathic inflammatory myopathies |
title_full_unstemmed | Predictive model of diabetes mellitus in patients with idiopathic inflammatory myopathies |
title_short | Predictive model of diabetes mellitus in patients with idiopathic inflammatory myopathies |
title_sort | predictive model of diabetes mellitus in patients with idiopathic inflammatory myopathies |
topic | Endocrinology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10150103/ https://www.ncbi.nlm.nih.gov/pubmed/37139334 http://dx.doi.org/10.3389/fendo.2023.1118620 |
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