Analysis of influencing factors and construction of nomogram prediction model for blood flow infection in patients with severe cerebral hemorrhage
10.3760/cma.j.cn115455-20240903-00767
- VernacularTitle:重症脑出血患者血流感染发生的影响因素分析及列线图预测模型构建
- Author:
Haiyan WU
1
;
Mo XIANG
1
Author Information
1. 海南省人民医院（海南医科大学附属海南医院）神经外科，海口 570311
- Publication Type:Journal Article
- Keywords:
Cerebral hemorrhage;
Blood flow infection;
Influence factor;
Nomograms
- From:
Chinese Journal of Postgraduates of Medicine
2025;48(4):298-304
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze the influencing factors of blood flow infection in patients with severe cerebral hemorrhage and construct a nomogram prediction model.Methods:Clinical data of 300 patients with severe cerebral hemorrhage admitted to the Hainan Provincial People′s Hospital from January 2020 to December 2022 were collected by retrospective study. According to the occurrence of bloodstream infection during hospitalization, they were divided into infected group (22 cases) and uninfected group (278 cases). Multivariate Logistic regression was used to analyze the influencing factors of the occurrence of blood flow infection in patients with severe cerebral hemorrhage, and a nomogram model was constructed to predict the occurrence of blood flow infection in patients with severe cerebral hemorrhage. The correction curve was used for internal verification, and the prediction efficiency was evaluated by decision curve.Results:The proportion of patients with diabetes, femoral vein catheterization, and catheterization time>7 d in the infected group was higher than that in the uninfected group group: 45.45% (10/22) vs. 20.14 % (56/278), 68.18% (15/22) vs. 32.37% (90/278), 63.64% (14/ 22) vs. 40.29% (112/278), and the serum albumin level was lower than that in the uninfected group: (37.20 ± 6.02) g/L vs. (42.12 ± 4.46) g/L, with statistical significant differences ( P<0.05). Multivariate Logistic regression analysis showed that diabetes, femoral vein catheterization, and catheterization time>7 d were risk factors for blood flow infection in patients with severe cerebral hemorrhage, and high serum albumin level was a protective factor for blood flow infection in patients with severe cerebral hemorrhage ( P<0.05). The nomogram model was constructed with diabetes, catheter placement site, catheter placement time, and serum albumin as predictors. The calibration curve of this model for predicting blood flow infection in patients with severe intracerebral hemorrhage approached the ideal curve (C-index: 0.865, 95% CI: 0.774 to 0.956). The result of decision curve analysis showed that when the risk threshold was > 0.08, the clinical net benefit provided by the nomogram model was higher than that of diabetes, catheter placement site, catheter placement time and serum albumin. Conclusions:Combined with diabetes, femoral vein catheterization, catheterization time>7 d, serum albumin are the influencing factors of blood flow infection in patients with severe cerebral hemorrhage. The nomogram model based on the above factors can be used to identify high-risk patients with blood flow infection.
