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Observational Study
. 2025 Jan-Dec:22:14799731251325251.
doi: 10.1177/14799731251325251. Epub 2025 Mar 20.

Clinical characteristics and prognosis prediction in patients with AECOPD and type 2 diabetes mellitus: A multicenter observational study

Affiliations
Observational Study

Clinical characteristics and prognosis prediction in patients with AECOPD and type 2 diabetes mellitus: A multicenter observational study

Xiaoqian Li et al. Chron Respir Dis. 2025 Jan-Dec.

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.

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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.

Figures

Figure 1.
Figure 1.
Patient inclusion flowchart. (A) Derivation cohort. (B) Validation cohort. AECOPD, acute exacerbation of chronic obstructive pulmonary disease; T2DM, type 2 diabetes mellitus.
Figure 2.
Figure 2.
Independent risk factors for 60-day mortality among AECOPD patients with T2DM in the multivariate logistic regression analysis. Blood pressure <90/60mmHg: systolic blood pressure <90 mmHg or/and diastolic blood pressure <60 mmHg. AECOPD, acute exacerbation of chronic obstructive pulmonary disease; T2DM, type 2 diabetes mellitus; BUN, blood urea nitrogen; OR, odds ratio; CI, confidence interval; Ref, reference.
Figure 3.
Figure 3.
The nomogram for 60-day mortality among AECOPD patients with T2DM. Blood pressure <90/60mmHg: systolic blood pressure <90 mmHg or/and diastolic blood pressure <60 mmHg. AECOPD, acute exacerbation of chronic obstructive pulmonary disease; T2DM, type 2 diabetes mellitus; BUN, blood urea nitrogen.
Figure 4.
Figure 4.
ROC curves for 60-day mortality among AECOPD patients with T2DM. (a) ROC curve of nomogram in the derivation cohort. (b) ROC curves of nomogram and DECAF in the validation cohort. ROC, receiver operating characteristic; AECOPD, acute exacerbation of chronic obstructive pulmonary disease; T2DM, type 2 diabetes mellitus.

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