A nomogram based on nutritional status and A(2)DS(2) score for predicting stroke-associated pneumonia in acute ischemic stroke patients with type 2 diabetes mellitus: A retrospective study

BACKGROUND: Stroke-associated pneumonia (SAP) commonly complicates acute ischemic stroke (AIS) and significantly worsens outcomes. Type 2 diabetes mellitus (T2DM) may contribute to malnutrition, impair innate immunity function, and increase the probability of SAP occurrence in AIS patients. We aimed to determine early predictors of SAP in AIS patients with T2DM and to construct a nomogram specifically for predicting SAP in this population by combining the A(2)DS(2) score with available nutrition-related parameters. METHODS: A total of 1,330 consecutive AIS patients with T2DM were retrospectively recruited. The patients were randomly allocated to the training (n = 887) and validation groups (n = 443). Univariate and multivariate binary logistic regression analyses were applied to determine the predictors of SAP in the training group. A nomogram was established according to the identified predictors. The areas under the receiver operating characteristic curve (AUROC) and calibration plots were performed to access the predictive values of the nomogram. The decision curve was applied to evaluate the net benefits of the nomogram. RESULTS: The incidence of SAP was 9% and 9.7% in the training and validation groups, respectively. The results revealed that the A(2)DS(2) score, stroke classification, Geriatric Nutritional Risk Index, hemoglobin, and fast blood glucose were independent predictors for SAP. A novel nomogram, A(2)DS(2)-Nutrition, was constructed based on these five predictors. The AUROC for A(2)DS(2)-Nutrition (0.820, 95% CI: 0.794–0.845) was higher than the A(2)DS(2) score (0.691, 95% CI: 0.660–0.722) in the training group. Similarly, it showed a better predictive performance than the A(2)DS(2) score [AUROC = 0.864 (95% CI: 0.828–0.894) vs. AUROC = 0.763 (95% CI: 0.720–0.801)] in the validation group. These results were well calibrated in the two groups. Moreover, the decision curve revealed that the A(2)DS(2)-Nutrition provided an additional net benefit to the AIS patients with T2DM compared to the A(2)DS(2) score in both groups. CONCLUSION: The A(2)DS(2) score, stroke classification, Geriatric Nutritional Risk Index, hemoglobin, and fast blood glucose were independent predictors for SAP in AIS patients with T2DM. Thus, the proposed A(2)DS(2)-Nutrition may be a simple and reliable prediction model for SAP occurrence in AIS patients with T2DM.