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  • Title: Construction and validation of nomogram prediction model for risk of acute heart failure in patients with acute exacerbation of chronic obstructive pulmonary disease.
    Author: Yan LN, Chen M, Wei H, Ma HR.
    Journal: Medicine (Baltimore); 2024 Jan 05; 103(1):e36840. PubMed ID: 38181256.
    Abstract:
    To investigate the influencing factors of in-hospital acute heart failure (AHF) in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD), and to construct and validate a risk prediction nomogram model. Three Hundred Thirty patients with AECOPD admitted to our hospital from June 2020 to June 2023 were retrospectively analyzed as a training set for the construction of the model. Three Hundred Twenty-five AECOPD patients admitted to the Second People's Hospital of Hefei from 2006 to June 2023 were also collected as the validation set for the validation of the model. A nomogram model was constructed to predict the risk of nosocomial AHF in patients with AECOPD, and C-index and receiver operating characteristic curve were drawn to assess the predictive predictive efficacy of the model. Model fit was evaluated by Hosmer-Lemeshow test, calibration curve was drawn to evaluate the calibration of the model; decision curve was drawn to analyze the net benefit rate of this nomogram model. Multivariate logistic regression analysis indicated that body mass index, mmRC grade, neutrophils, lymphocytes, hemoglobin, creatinine, PO2, PCO2, and Homocysteine were independent risk factors for in-hospital AHF in patients with AECOPD. To construct a nomogram model for risk prediction of in-hospital AHF in patients with AECOPD. The C-index of the training set was 0.949 (95% CI: 0.91-0.961); the C-index of the validation set was 0.936 (95% CI: 0.911-0.961) suggesting good model discrimination. The receiver operating characteristic curve calculated area under curve for the training set was 0.949 (95% CI: 0.928-0.97); area under curve for the validation set was 0.936 (95% CI: 0.91-0.961) suggesting good model accuracy. The results of Hosmer-Lemeshoe goodness-of-fit test and calibration curve analysis showed that the calibration curve of this nomogram model was close to the ideal curve. The clinical decision curve also showed good clinical net benefit of the nomogram model. Body mass index, mmRC grade, neutrophils, lymphocytes, hemoglobin, creatinine, PO2, PCO2, and Homocysteine are risk factors for in-hospital AHF in AECOPD patients, and nomogram models constructed based on the above factors have some predictive value for in-hospital AHF in AECOPD patients. It is also vital for nursing staff to strengthen nursing care.
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