The nomogram to predict the occurrence of sepsis-associated encephalopathy in elderly patients in the intensive care units: A retrospective cohort study - Zhao, Qing; Xiao, Jianguo; Liu, Xiaoli; Liu, Hui (Frontiers in Neurology, 2023)
Background: Sepsis-associated encephalopathy (SAE) is a critical and common problem in septic elderly patients, which is still short of efficient predictive tools. This study aims to screen the risk factors and establish an useful predictive nomogram for SAE in septic elderly patients in the intensive care unit (ICU). Patients and Methods: Elderly patients (age ≥ 65) with sepsis were selected from Medical Information Mart for Intensive Care (MIMIC)-IV database. Data of demographics and laboratory exmination were collected on the first day of admission to ICU. SAE was defined by 2 critetia at the presence of sepsis, ①Glasgow Coma Score (GCS) < 15, or ② delirium. Difference of demographics and laboratory tests were caculated between SAE and non-SAE groups. Participants were randomly distributed into a training set and a validation set without replacement at a ratio of 6:4. The predictive nomogram was constructed in the training set by logistic regression analysis and then validated. The predictive capability of the nomogram was demonstrated by receiver operating characteristic (ROC) analysis and calibration curve analysis. Results: 22361 patients were selected, and in which 2809 patients (12.7%) died in hospital. 37.1% patients (8290 persons) had SAE. In-hospital mortality in SAE group was higher than that in non-SAE group (18.8% vs. 8.9%, p < 0.001). Based on the results of logistical regression analysis, the nomogram intergrating age, Na+, sequential organ failure assessment score (SOFA), heart rate and body temperature was constructed. Area under curve (AUC) of the nomogram was 80.2% in the training set and 80.9% in the validation set. Calibration curve analysis showed a good predictive capacity of the nomogram. Conclusion: SAE is an independent risk of in-hospital mortality in elderly patients in the intensive care unit. The nomogram has an excellent predictive capability of SAE and helps in clinical practice.