Application of risk prediction model to evaluate the effect of mechanical ventilation on postoperative pulmonary complications in thoracic surgery

Adopting pulmonary protective ventilation strategies--such as low tidal volume, appropriate PEEP, and recruitment maneuvers--significantly reduces the risk of PPCs in patients undergoing thoracic surgery. Machine learning algorithms like XGBoost may assist in identifying high-risk patients and tailoring individualized ventilation management. Further applications of multicenter big data and real-time monitoring technologies may help optimize mechanical ventilation strategies and improve patient outcomes.