OBJECTIVE  To explore the risk factors of hospital-associated infection in patients undergoing intracerebral hematoma evacuation, and to construct and evaluate a nomogram prediction model.

METHODS  A retrospective analysis was conducted on the clinical data of 231 patients who underwent intracerebral hematoma evacuation at Gansu Provincial Hospital from Jan. 2020 to Dec. 2024. These patients were divided into an infection group (n=86) and a non-infection group (n=145) based on whether they developed hospital-associated infection. A multivariate logistic regression model was used to analyze the risk factors for hospital-associated infection. Based on the results of the multivariate analysis, a nomogram risk prediction model was constructed, and its performance was evaluated with receiver operating characteristic (ROC) curve, Bootstrap method, Hosmer-Lemeshow goodness-of-fit test and decision curve analysis (DCA) curve.

RESULTS  Among 231 patients, the hospital-associated infection rate was 37.23% (86/231), with a cumulative infection of 91 cases. Lower respiratory tract infection accounted for the highest proportion (89.01%). Operation duration (OR=1.005, 95% CI: 1.002−1.009, P=0.003), central venous catheterization duration (OR=1.092, 95% CI: 1.029−1.159, P=0.004) and duration of ventricular drainage (OR=1.136, 95% CI: 1.006−1.282, P=0.040) were identified as risk factors for hospital-associated infection in patients undergoing intracerebral hematoma evacuation (P＜0.05). Based on the aforementioned independent risk factors, a nomogram model was constructed. The calibration curve demonstrated good consistency between the predicted and actual outcomes with a mean absolute error of 0.032. Bootstrap method validation indicated a mean absolute error of 0.048 for the calibration curve, indicating good model stability. The Hosmer-Lemeshow goodness-of-fit test suggested good model fit (χ²=8.010, P=0.424), indicating a good fit between the calibration curve and the ideal curve. The ROC curve showed an area under the curve of 0.900 (95% CI: 0.865－0.945), indicating good discriminatory power of the model. The DCA curve indicated that the model had high clinical net benefit when the high-risk threshold probability ranged from 0.08 to 0.88, making it valuable for practical application.

CONCLUSIONS  The hospital-associated infection rate after intracerebral hematoma evacuation is relatively high. Operation duration, central venous catheterization duration and ventricular drainage duration are risk factors for hospital-associated infection. The nomogram model constructed in this study demonstrates good prediction performance and can provide a reference for early identification of high-risk patients and the development of individualized prevention and control strategies in clinical practice.