LIU Shuo, WU Juan. Risk factors and visual prediction model for lower respiratory tract infection in patients with aneurysmal subarachnoid hemorrhage in emergency care unit[J]. Chinese Journal of Nosocomiology. DOI: 10.11816/cn.ni.2025-250386
Citation: LIU Shuo, WU Juan. Risk factors and visual prediction model for lower respiratory tract infection in patients with aneurysmal subarachnoid hemorrhage in emergency care unit[J]. Chinese Journal of Nosocomiology. DOI: 10.11816/cn.ni.2025-250386

Risk factors and visual prediction model for lower respiratory tract infection in patients with aneurysmal subarachnoid hemorrhage in emergency care unit

  • OBJECTIVE To explore the risk factors for lower respiratory tract infection (LRTI) in patients with aneurysmal subarachnoid hemorrhage (aSAH) in the emergency care unit and to establish a nomogram model for LRTI in patients with aSAH.
    METHODS A total of 327 patients with aSAH admitted to the First Affiliated Hospital with Nanjing Medical University from Feb. 2020 to Jul. 2023 were enrolled as study subjects. Based on the presence of LRTI in patients with aSAH, they were divided into an LRTI group (n=79) and a no-LRTI group (n=248). Lasso analysis was used to screen predictive factors for LRTI in patients with aSAH. Logistic regression was employed to identify risk factors for LRTI in patients with aSAH. The R software version 4.2.3 was utilized to develop and validate a nomogram model for LRTI in patients with aSAH.
    RESULTS Logistic regression analysis revealed that the location of the responsible aneurysm in the posterior circulation (OR=2.568), Hunt-Hess grading (grades Ⅲ-Ⅳ) (OR=3.576), use of glucocorticoids (OR=2.983), invasive procedures (OR=3.190), history of chronic lung diseases (OR=3.214), disturbance of consciousness (OR=2.631) and diabetes (OR=2.419) were risk factors for LRTI in patients with aSAH (P < 0.05). Interaction analysis showed an additive interaction existed between diabetes and the use of glucocorticoids on the risk of LRTI in patients with aSAH. The area under the receiver operating characteristic (ROC) curve of the nomogram model for LRTI in patients with aSAH was 0.756 (95% CI: 0.691-0.821), and the calibration curve demonstrated good agreement between predicted and actual values. Decision curve analysis indicated that the nomogram provided good net benefit for predicting LRTI in patients with aSAH when the threshold probability ranged from 6% to 84%.
    CONCLUSIONS The nomogram model established based on seven risk factors, including location of the responsible aneurysm in the posterior circulation, Hunt-Hess grades Ⅲ-Ⅳ, use of glucocorticoids, invasive procedures, history of chronic lung disease, disturbance of consciousness and diabetes, can effectively predict the risk of LRTI in patients with aSAH.
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