Predicting Unplanned Readmissions to the Intensive Care Unit in the Trauma Population.

Area of Science:

• Trauma surgery
• Critical care medicine
• Health services research

Background:

• Unplanned readmission to the intensive care unit (UR-ICU) in trauma patients is a significant concern, associated with increased length of stay, morbidity, and mortality.
• Identifying predictors of UR-ICU is crucial for improving patient outcomes and optimizing resource allocation in trauma care.

Purpose of the Study:

• To identify independent predictors of UR-ICU in trauma patients.
• To develop a nomogram for estimating the probability of UR-ICU and assist in discharge decision-making.

Main Methods:

• Retrospective case-control study at a Level I trauma center (January 2019 - December 2021).
• Matched 175 patients with UR-ICU to 175 patients without readmission (NR-ICU).
• Utilized univariate and multivariable binary linear regression and nomogram construction.

Main Results:

• UR-ICU patients had a significantly higher mortality rate (22.29%) compared to NR-ICU patients (6.29%).
• Seven independent predictors for UR-ICU were identified: shock, intracranial surgery, low hematocrit, sedation before discharge, active infection treatment, leukocytosis, and COPD.
• A nomogram was developed to predict UR-ICU probability.

Conclusions:

• UR-ICU in trauma is associated with poor outcomes and increased mortality.
• Shock, intracranial surgery, anemia, sedation, infection, leukocytosis, and COPD are significant risk factors.
• A predictive nomogram can aid in assessing patient readiness for ICU discharge.