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A multicenter clinical study of machine learning to predict endotracheal intubation response under general anesthesia

A multicenter clinical study of machine learning to predict endotracheal intubation response under general anesthesia

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2300074700
Enrollment
Unknown
Registered
2023-08-14
Start date
2023-08-15
Completion date
Unknown
Last updated
2023-08-21

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

Conditions

intubation response

Interventions

Elective surgical patients requiring transoral/nasal tracheal intubation during general anesthesia:none

Sponsors

Shanghai Changzheng Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
No minimum to 100 Years

Inclusion criteria

Inclusion criteria: Elective surgical patients requiring transoral/nasal tracheal intubation during general anesthesia

Exclusion criteria

Exclusion criteria: 1) Emergency surgery; 2) pregnant and lactating women; 3) patients with implanted pacemakers; 4) patients with full stomachs; 5) Patients in shock; 6) Patients who refused to participate in this study Clinical

Design outcomes

Primary

MeasureTime frame
Accuracy of response to endotracheal intubation in general anesthesia;—

Countries

China

Contacts

Public ContactWenyun Yu

Shanghai Changzheng Hospital

xuwenyun@smmu.edu.cn+86 181 1636 4800

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026