Clinical characteristics and prognosis prediction in patients with AECOPD and type 2 diabetes mellitus: A multicenter observational study
- PMID: 40114423
- PMCID: PMC11926837
- DOI: 10.1177/14799731251325251
Clinical characteristics and prognosis prediction in patients with AECOPD and type 2 diabetes mellitus: A multicenter observational study
Abstract
ObjectivesDiabetes is a common comorbidity in COPD population. This study aimed to explore the impacts of T2DM on clinical characteristics and outcomes of patients with exacerbation of COPD, as well as develop a specified prognostic model for these patients.MethodsAECOPD patients were enrolled from a prospective, noninterventional, multicenter cohort study. Propensity score matching with a 1:2 ratio was performed to compare the characteristics and prognosis between patients with and without T2DM. Predictors for short-term mortality were determined by logistic regression analysis and a prediction nomogram were established and further validated in another cohort.ResultsA total of 1804 AECOPD patients with T2DM and 3608 matched patients without T2DM were included. AECOPD patients with T2DM presented with worse disease profile and prognosis. Eight independent predictors for short-term mortality were determined, including advanced age, disturbance of consciousness, chronic cardiac disease, low blood pressure, high heart rate, elevated neutrophil, urea nitrogen and random blood glucose. A prognostic nomogram was established with an AUC of 0.878 (95%CI: 0.842-0.915) in derivation cohort and 0.834 (95% CI: 0.767-0.901) in validation cohort, which was superior to DECAF (0.647 [95%CI: 0.535-0.760]) and BAP-65 score (0.758 [95%CI: 0.666-0.850]). The calibration curve and decision curve analysis also indicated its accuracy and applicability. Besides, a web calculator based on the nomogram was constructed to simplify the use of prognostic nomogram in clinical practice.ConclusionsComorbid diabetes is significantly associated with severe disease profile and worse prognosis in AECOPD population. Our nomogram may help to facilitate early risk assessment and proper decision-making among patients with AECOPD and T2DM.
Keywords: AECOPD; Type 2 diabetes mellitus; prognostic model.
Conflict of interest statement
Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
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References
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- Wang C, Xu J, Yang L, et al. Prevalence and risk factors of chronic obstructive pulmonary disease in China (the China Pulmonary Health [CPH] study): a national cross-sectional study. Lancet 2018; 391(10131): 1706–1717. - PubMed
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