The purpose of this study is to develop a high-performance machine learning model combining dynamic baroreflex sensitivity (BRS) metrics and multi-dimensional static clinical features to predict the risk of post-induction hypotension (PIH) in elderly patients undergoing elective non-cardiac surgery under general anesthesia.
Aged over 65 years;
Scheduled for elective non-cardiac surgery;
American Society of Anesthesiologists (ASA) physical status classification I-III;
Planned for general anesthesia with endotracheal intubation;
Severe peripheral vascular diseases;
Secondary hypertension;
Presence of physical tremors (e.g., Parkinson's disease) preventing stable recording;
Inability to accurately measure upper limb blood pressure;