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Machine Learning Model Based on Baroreflex Sensitivity for Predicting Post-Induction Hypotension in Elderly Patients

Recruitingn/aAges 65 Years - anyAllPeking Union Medical College Hospital
NCT07618416 on ClinicalTrials.gov ↗
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In plain words

What the trial is, and whether it could suit you

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.

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📋 Eligibility rules (as published)
Inclusion Criteria: * 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; * Patient and legal guardians are capable of understanding the study protocol and willing to provide written informed consent. Exclusion Criteria: * 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; * Pre-existing cardiac arrhythmias (e.g., atrial fibrillation) that render BRS; * Psychiatric disorders or cognitive impairments hindering basic cooperation.
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What it tests

  • Not listed
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Where

1 site
Peking Union Medical College Hospital
Beijing, China
🤝 Taking part is your choice, and you can leave at any time. Only the trial team can confirm you are eligible — always decide together with your own doctor.
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