Association between type 2 diabetes mellitus and Klebsiella pneumoniae colonization: construction of nomogram model.

Objective: To investigate the association between the basic and clinical characteristics of patients with type 2 diabetes mellitus (T2DM) and their susceptibility to Klebsiella pneumoniae colonization (KPC). Additionally, a clinical prediction model was developed to identify high-risk patients for KPC.

Methods: Data from 486 T2DM patients who visited Shanghai Fifth People's Hospital from December 2020 to December 2022 were retrospectively collected. Patients were classified into the KPC group and normal group based on their Klebsiella pneumoniae test results. Differences between the two groups were analyzed using t-test and chi-square test. Logistic regression was performed to identify factors influencing KPC susceptibility in T2DM patients, with odds ratios (ORs) calculated. A clinical prediction model was constructed using a nomogram and evaluated through the area under the receiver operating characteristic (ROC) curve (AUC), Hosmer-Lemeshow test, calibration curve, and decision curve analysis (DCA).

Results: Of the 486 T2DM patients, 124 were found to have KPC, with a colonization rate of 25.51%. Logistic regression analysis revealed that hospitalization within the past six months, elevated white blood cell count, decreased hemoglobin, and elevated ferritin levels were independent risk factors for KPC. Thyroid and liver function indicators were also associated with KPC susceptibility. The clinical prediction model achieved an AUC of 0.74 (95% CI: 0.68-0.80). The calibration curve indicated no significant differences between observed and predicted values, suggesting that the model effectively identifies high-risk KPC patients.

Conclusion: T2DM patients are at an increased risk of secondary KPC. Identifying key risk factors for KPC in T2DM patients has significant clinical implications for early identification, targeted interventions, and individualized treatment strategies.