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;
Patients scheduled for elective operations
Cohort
Prospective
Not listed
Incidence of Post-Induction Hypotension (PIH)
Defined as a systolic blood pressure (SBP) \<90 mmHg , a mean arterial pressure (MAP) \<65 mmHg, or a decrease in MAP exceeding 30% from baseline measurements.
1. Early Intraoperative Hypotension Rate
Defined as a systolic blood pressure (SBP) \<90 mmHg , a mean arterial pressure (MAP) \<65 mmHg, or a decrease in MAP exceeding 30% from baseline measurements.
Postoperative Complication
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