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Nomograms for Predicting Coexisting Cardiovascular Disease and Prognosis in Chronic Obstructive Pulmonary Disease: A Study Based on NHANES Data

Canadian respiratory journal, 2022, Vol.2022, p.1-13 [Peer Reviewed Journal]

Copyright © 2022 Yuanjie Qiu et al. ;Copyright © 2022 Yuanjie Qiu et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0 ;Copyright © 2022 Yuanjie Qiu et al. 2022 ;ISSN: 1198-2241 ;EISSN: 1916-7245 ;DOI: 10.1155/2022/5618376 ;PMID: 35721788

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  • Title:
    Nomograms for Predicting Coexisting Cardiovascular Disease and Prognosis in Chronic Obstructive Pulmonary Disease: A Study Based on NHANES Data
  • Author: Qiu, Yuanjie ; Wang, Yan ; Shen, Nirui ; Wang, Qingting ; Chai, Limin ; Wang, Jian ; Zhang, Qianqian ; Chen, Yuqian ; Liu, Jin ; Li, Danyang ; Chen, Huan ; Li, Manxiang
  • Corlateanu, Alexandru ; Alexandru Corlateanu
  • Subjects: Body mass index ; Cardiovascular disease ; Chronic illnesses ; Chronic obstructive pulmonary disease ; Comorbidity ; Mortality ; Nomograms
  • Is Part Of: Canadian respiratory journal, 2022, Vol.2022, p.1-13
  • Description: Background. Chronic obstructive pulmonary disease (COPD) is a common chronic disease. Progression is further exacerbated by the coexistence of cardiovascular disease (CVD). We aim to construct a diagnostic nomogram for predicting the risk of coexisting CVD and a prognostic nomogram for predicting long-term survival in COPD. Methods. The 540 eligible participants selected from the NHANES 2005–2010 were included in this study. Logistic regression analysis was used to construct a diagnostic nomogram for the diagnosis of coexisting CVD in COPD. Cox regression analyses were used to construct a prognostic nomogram for COPD. A risk stratification system was developed based on the total score generated from the prognostic nomogram. We used C-index and ROC curves to evaluate the discriminant ability of the newly built nomograms. The models were also validated utilizing calibration curves. Survival curves were made using the Kaplan–Meier method and compared by the Log-rank test. Results. Logistic regression analysis showed that gender, age, neutrophil, RDW, LDH, and HbA1c were independent predictors of coexisting CVD and were included in the diagnostic model. Cox regression analysis indicated that CVD, gender, age, BMI, RDW, albumin, LDH, creatinine, and NLR were independent predictors of COPD prognosis and were incorporated into the prognostic model. The C-index and ROC curves revealed the good discrimination abilities of the models. And the calibration curves implied that the predicted values by the nomograms were in good agreement with the actual observed values. In addition, we found that coexisting with CVD had a worse prognosis compared to those without CVD, and the prognosis of the low-risk group was better than that of the high-risk group in COPD. Conclusions. The nomograms we developed can help clinicians and patients to identify COPD coexisting CVD early and predict the 5-year and 10-year survival rates of COPD patients, which has some clinical practical values.
  • Publisher: Oakville: Hindawi
  • Language: English;French
  • Identifier: ISSN: 1198-2241
    EISSN: 1916-7245
    DOI: 10.1155/2022/5618376
    PMID: 35721788
  • Source: GFMER Free Medical Journals
    PubMed Central
    ProQuest Central
    DOAJ Directory of Open Access Journals
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