Physiologic state severity classification as an indicator of posttrauma cytokine response

Area of Science:

• Critical Care Medicine
• Trauma Surgery
• Immunology

Background:

• Critically ill trauma patients exhibit complex physiological responses.
• Predicting patient outcomes and cytokine profiles in trauma is challenging.
• Existing classifications may not fully capture the dynamic physiological states.

Purpose of the Study:

• To develop and validate a Physiologic State Severity Classification (PSSC) for critically ill posttrauma patients.
• To correlate PSSC states with cytokine response, sepsis, ARDS, and probability of death (Pdeath).
• To assess the predictive value of PSSC for patient survival and mortality.

Main Methods:

• Clustering of 17 cardiorespiratory variables to define PSSC states: A-State (normal stress), B-State (metabolic insufficiency), C2-State (respiratory insufficiency).
• Bayesian analysis to determine probability of death (Pdeath) based on PSSC states.
• Analysis of 416 studies from 60 multiple trauma patients, including cytokine levels and clinical outcomes (sepsis, ARDS, survival).

Main Results:

• PSSC states were significantly correlated with the incidence and plasma levels of cytokines.
• Survivors predominantly exhibited A-State and B-State, while non-survivors were predominantly in B-State and C2-State.
• Higher Pdeath values were observed in patients with sepsis and sepsis-adult respiratory distress syndrome (s-ARDS), particularly in C2-State.

Conclusions:

• The PSSC effectively classifies physiological states in critically ill trauma patients.
• PSSC states are valuable predictors of cytokine response, sepsis, ARDS, and mortality.
• This classification system offers a novel approach to risk stratification and outcome prediction in trauma care.