Model for predicting mortality in patients with traumatic brain injury

Chronic critical illness is characterized by extremely severe course of disease and significantly increases the burden on healthcare and social security systems. In these conditions, prediction of clinical outcomes becomes a priority task for specialists. Objective. To develop a nomogram predicting the probability of death within 14, 21, 28, 42 days in chronic critical illness after traumatic brain injury. Material and methods. A retrospective single-center cohort study was performed. The Russian Intensive Care Dataset (RICD) was used to develop the nomogram. This database includes information on hospitalizations to the Federal Research Clinical Center of Intensive Care Medicine and Rehabilitology between 2017 and 2023. We extracted clinical data of patients for the first 48 hours after admission (anamnestic data, laboratory parameters, scores), demographic data and outcomes (in-hospital mortality, length of hospital-stay, mechanical ventilation, infusion of vasoactive drugs). Results. The study included 324 patients (23 (7.1%) fatal cases). According to univariate and multivariate analysis, we identified and included 3 parameters into the nomogram predicting the probability of mortality: absolute neutrophil count, albumin concentration and chronic kidney disease. AUC was 0.696 (95% CI 0.590; 0.796). Conclusion. Original nomogram involving absolute neutrophil count, albumin concentration and chronic kidney disease allows for mid-term prediction of mortality in chronic critical illness following traumatic brain injury.