Development of a Deep Learning Model Using Spectroscopic Arterial Pressure Waveform to Predict Hypotension after General Anesthesia Induction - A Retrospective Observational Study-

Development of a Deep Learning Model Using Spectroscopic Arterial Pressure Waveform to Predict Hypotension after General Anesthesia Induction - A Retrospective Observational Study- - Development of a Deep Learning Model Using Spectroscopic Arterial Pressure Waveform to Predict Hypotension after General Anesthesia Induction - A Retrospective Observational Study-

Status

Recruiting

Phases

Unknown

Study type

Observational

Source

JPRN

Registry ID

JPRN-UMIN000044732

Enrollment

200

Registered

2021-07-02

Start date

2021-07-02

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

Cases in which general anesthesia is performed

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 in this study. From those cases, we will select those in which spectroscopic arterial pressure measurement was performed prior to the induction of general anesthesia.

Exclusion criteria

Exclusion criteria: Patients with general anesthesia administered before induction of general anesthesia Patients with tracheal intubation administered before induction of general anesthesia

Design outcomes

Primary

Measure	Time frame
Prediction of hypotension after induction of general anesthesia from angiographic arterial pressure waveform before induction of general anesthesia	—

Countries

Japan

Contacts

Public ContactKenya Yarimizu

Yamagata University Medical School Hospital Anesthesiology

yarimizu.kenya@gmail.com0236331122

Outcome results