Exploring phenotype-based ventilator parameter optimization to mitigate postoperative pulmonary complications: a...

Area of Science:

• Anesthesiology and Critical Care Medicine
• Respiratory Physiology
• Surgical Outcomes Research

Background:

• Postoperative pulmonary complications (PPCs) are a significant cause of morbidity and mortality after surgery.
• Individualized mechanical ventilation strategies are crucial for optimizing patient outcomes.
• Identifying specific ventilator settings for different patient groups remains a challenge.

Purpose of the Study:

• To determine the optimal tidal volume (V_T) and positive end-expiratory pressure (PEEP) for reducing the incidence and severity of PPCs.
• To stratify patients into phenotypes based on preoperative characteristics to guide ventilator management.
• To identify V_T and PEEP settings associated with the best outcomes for each identified phenotype.

Main Methods:

• Retrospective observational cohort study of 34,910 adult patients undergoing surgery with mechanical ventilation.
• Least absolute shrinkage and selection operator (LASSO) regression to identify key preoperative predictors.
• Classification and regression tree (CART) analysis to define patient phenotypes.
• Logistic regression and ROC curve analysis to determine optimal V_T and PEEP for each phenotype.

Main Results:

• Seven distinct patient phenotypes were identified using CART analysis.
• The probability of developing PPCs varied widely across phenotypes (3.51% to 68.57%).
• Optimal V_T (7-8 ml/kg predicted body weight) and PEEP (6-8 cmH₂O) were identified for minimizing PPCs and severity across all phenotypes.

Conclusions:

• A narrow range of V_T and PEEP settings is associated with the lowest incidence and severity of PPCs.
• These optimal settings appear consistent across different patient phenotypes, despite their varied risk profiles.
• This finding suggests a potential universal approach to mechanical ventilation in the perioperative period.