Creation of a deep learning model to predict hypotension after induction of general anesthesia using a biometric screen during awakening - A prospective observational study

Creation of a deep learning model to predict hypotension after induction of general anesthesia using a biometric screen during awakening - A prospective observational study - Creation of a deep learning model to predict hypotension after induction of general anesthesia using a biometric screen during awakening - A prospective observational study

Status

Recruiting

Phases

Unknown

Study type

Observational

Source

JPRN

Registry ID

JPRN-UMIN000044894

Enrollment

100

Registered

2021-07-20

Start date

2021-07-21

Completion date

Unknown

Last updated

2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Surgical cases undergoing general anesthesia

Interventions

None listed

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: Surgical cases undergoing general anesthesia in the operating room of Yamagata University Hospital will be included. Among them, cases in which arterial pressure measurement is performed prior to induction of general anesthesia will be considered eligible cases.

Exclusion criteria

Exclusion criteria: Patients who have been sedated prior to induction of general anesthesia. Patients undergoing tracheal intubation prior to induction of general anesthesia. Patients with contraindications to propofol or remimazolam. Patients who did not give their consent to participate in the study. Patients with aortic aneurysms or cerebral aneurysms that require management to prevent excessive blood pressure fluctuations.

Design outcomes

Primary

Measure	Time frame
Accuracy of Deep Learning Model Using Biometric Images Before General Anesthesia Induction for Predicting Blood Pressure Decline after General Anesthesia Induction	—

Countries

Japan

Contacts

Public Contactkenya yarimizu

Yamagata University Medical School Hospital Department of Anesthesia

yarimizu.kenya@gmail.com0236331122

Outcome results