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AI could help anesthesiologists spot tricky airways

NCT ID NCT06626204

What the study statuses mean

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Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing
Running, but no longer taking on new participants.
Completed This study
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Jun 27, 2026 · Last updated Jun 27, 2026

Summary

This completed study tested an artificial intelligence system that analyzes mouth images to predict whether a patient will have a difficult airway during surgery. Researchers enrolled 475 adults undergoing general anesthesia in China. The goal was to see if the AI could be more accurate and consistent than traditional methods like the Mallampati test. The study focused on comparing the AI's predictions with standard assessments.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

Active substance
intelligent airway assessment system using deep learning
What this could lead to
If successful, this could lead to a more reliable, automated way to predict difficult airways, potentially reducing complications during anesthesia.
What could go wrong
This is a completed exploratory study, not a treatment trial. The AI system may not outperform current methods in real-world settings, and results may not apply to all populations.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

475 people

The number who actually took part.

Started

Sep 2024

Finished

Jan 2025

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

Patients scheduled for elective general anesthesia with endotracheal intubation.

Ages

18 years and older

Sex

Anyone

Healthy volunteers

Accepted

You do not need to have the condition being studied to take part.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: * Age ≥18 years, with no gender restrictions; * Subjects who are scheduled to undergo elective general anesthesia and require endotracheal intubation; * Subjects classified as American Society of Anesthesiologists Physical Status (ASA-PS) Class I, II, and III; * Volunteers who are willing to participate in this clinical trial and have signed the Informed Consent Form. Exclusion Criteria: * Subjects with known airway deformities, tumors, or other structural abnormalities that may affect airway assessment; * Subjects with psychiatric disorders or other conditions that prevent cooperation; * Pregnant or lactating women; * Subjects who have participated in other interventional clinical trials within 1 month prior to the start of this trial; * Subjects deemed inappropriate to participate in this clinical trial by the investigator.

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As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Contacts and locations

Locations

  • First Affiliated Hospital of Chongqing Medical University

    Chongqing, Chongqing Municipality, 400016, China

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