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

NCT07618416 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 500

Last updated 2026-06-01

No results posted yet for this study

Summary

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.

Conditions

  • Post Induction Hypotension

Sponsors & Collaborators

  • Peking Union Medical College Hospital

    lead OTHER

Eligibility

Min Age
65 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-06-01
Primary Completion
2027-09-30
Completion
2027-12-31

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07618416 on ClinicalTrials.gov