Establishment of Airway Database for Surgical Patients

Status Not yet recruiting

Clinical Trial Summary

Difficult airway is a major reason of anesthesia related injuries with latent life threatening complications. Foresee difficult airway in the preoperative period is vital for the patient's safety. The aim of this study is to develop a computer algorithm that can detect whether the patient is a difficult airway based on photographs form six aspects. This method will be decreased potential complication related to difficult airway and increased patient safety.

Clinical Trial Description

Introduction:

The primary purpose of the study is to develop a computer algorithm that can detect whether the patient is a difficult airway based on photographs from six different aspects.

Methods:

This study is divided into two parts. In the first part, we collected the patients' airway assessment score who underwent general anesthesia with endotracheal intubation assessed by an experienced attending anesthesiologists before and after intubation. Evaluation of airway score after tracheal intubation as the gold standard for airway assessment. Digital photographs of the face of each patient in frontal neutral view and in profile neutrals were obtained. Details of the photographs, each corresponding to a facial motion: (1) Frontal, neutral. (2) Frontal, mouth open. (3)Frontal, extreme mouth open and tongue out. (4)Frontal, extreme upper lip bite (5)Profile, neutral. (6) Profile, neutral, maximum head back. The patient's photographs and the airway evaluation score after intubation were input to the computer to train the computer. In the second part, the trained computer was used to evaluate the airway score of the new patient compared with that of the patient after intubation, and calculated the sensitivity. ;

Study Design

Related Conditions & MeSH terms

Clinical Trial Details

NCT number	NCT03125837
Study type	Observational
Source	Second Affiliated Hospital, School of Medicine, Zhejiang University
Contact
Status	Not yet recruiting
Phase	N/A
Start date	May 2017
Completion date	May 2022

View Details

See also
Status	Clinical Trial	Phase
Completed	`NCT04589078` - Polyp REcognition Assisted by a Device Interactive Characterization Tool - The PREDICT Study
Completed	`NCT03857438` - Correlation of Audiovisual Features With Clinical Variables and Neurocognitive Functions in Bipolar Disorder, Mania
Completed	`NCT04735055` - Artificial Intelligence Prediction for the Severity of Acute Pancreatitis
Not yet recruiting	`NCT05452993` - Screening for Diabetic Retinopathy in Pharmacies With Artificial Intelligence Enhanced Retinophotography	N/A
Not yet recruiting	`NCT04337229` - Evaluation of Comfort Behavior Levels of Newborns With Artificial Intelligence Techniques	N/A
Completed	`NCT05687318` - A Clinical Trial of the Effectiveness and Safety of Software Assisting Diagnose the Intestinal Polyp Digestive Endoscopy by Analysis of Colonoscopy Medical Images From Electronic Digestive Endoscopy Equipment	N/A
Recruiting	`NCT06051682` - Optimization of the Diagnosis of Bone Fractures in Patients Treated in the Emergency Department by Using Artificial Intelligence for Reading Radiological Images in Comparison With Traditional Reading by the Emergency Doctor.	N/A
Not yet recruiting	`NCT06039917` - Effect of the Automatic Surveillance System on Surveillance Rate of Patients With Gastric Premalignant Lesions	N/A
Not yet recruiting	`NCT06362629` - AI App for Management of Atopic Dermatitis	N/A
Recruiting	`NCT06164002` - A I in the Prediction of Clinical Performance, Marginal Fit and Fracture Resistance of Vertical Versus Horizontal Margin Designs Fabricated With 2 Ceramic Materials	N/A
Recruiting	`NCT06059378` - Real-life Implementation of an AI-based Optical Diagnosis	N/A
Completed	`NCT05517889` - Repeatability and Stability of Healthy Skin Features on OCT
Completed	`NCT05006092` - Surveillance Modified by Artificial Intelligence in Endoscopy (SMARTIE)	N/A
Completed	`NCT04816981` - AI-EBUS-Elastography for LN Staging	N/A
Recruiting	`NCT04535466` - Diagnosis Predictive Modle for Dense Density Breast Tissue Based on Radiomics
Enrolling by invitation	`NCT04719117` - Retrograde Cholangiopancreatography AI Assisted System Validation on Effectiveness and Safety
Completed	`NCT04399590` - Comparing the Number of False Activations Between Two Artificial Intelligence CADe Systems: the NOISE Study
Recruiting	`NCT04126265` - Artificial Intelligence-assisted Colonoscopy for Detection of Colon Polyps	N/A
Recruiting	`NCT06255808` - Development of Assist Tool for Breast Examination Using the Principle of Ultrasonic Sensor
Recruiting	`NCT04131530` - Automatic Evaluation of Inflammation Activity in Ulcerative Colitis Using pCLE With Artificial Intelligence