Pre-anesthesia Imaging-based Respiratory Assessment and Analysis

Clinical Decision Support System Clinical Trial

Official title:

Pre-anesthesia Imaging-based Respiratory Assessment and Analysis

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT06270797
• Other study ID #: KMUHIRB-E(I)-20230184
• Status: Recruiting
• Start date: March 1, 2024
• Est. completion date: December 31, 2026

Study information

• Verified date: December 2023
• Source: Kaohsiung Medical University Chung-Ho Memorial Hospital
• Contact: Tz Ping Gau, MD
• Phone: +886912060962
• Email: u9401066[@]gap.kmu.edu.tw
• Is FDA regulated: No
• Study type: Observational [Patient Registry]

Clinical Trial Summary

This study is to establish a preoperative respiratory imaging assessment database and develop a difficult intubation risk prediction model and further risk analysis. We attempt to construct it into a pre-anesthesia intubation risk assessment software as the clinical decision support system.

Description:

Anesthesia respiratory assessment is an important issue for anesthesiologists to evaluate the respiratory status and airway management of patients before surgery. The American Society of Anesthesiologists (ASA) updated its guidelines in 2022, emphasizing the importance of comprehensive respiratory assessment in the guidelines. Various risk factors have been proposed in past literature for discussion, and corresponding to these risk factors, there is currently no single factor that can predict difficult intubation completely. Existing investigations into difficult intubation factors mostly focus on high-risk populations, including patients with morbid obesity, where significant differences have been identified but not developed into predictive models. With the rapid development of AI-related technologies in recent years, numerous image-related AI frameworks have been proposed. In recent years, attempts have been made to combine various clinical risk factors using machine learning methods to create automated prediction models for difficult intubation. However, their effectiveness has not met expectations, reflecting the significant clinical problem of difficulty in prediction that remains unresolved. This study is an observational study aimed at analyzing and establishing patient image data, refining various data engineering techniques, and optimizing existing prediction model frameworks to enhance their medical value. Additionally, the focus of this project will be on establishing more prediction models to improve existing clinical decision support systems.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 30000
• Est. completion date: December 31, 2026
• Est. primary completion date: December 31, 2026
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years to 85 Years

Eligibility

Inclusion Criteria:

• Patients undergoing general anesthesia
• Patients who can undergo pre-anesthetic consultation and airway examination.

Exclusion Criteria:

• Patients unable to undergo pre-anesthetic consultation and airway examination.
• Patients requiring emergency surgery.
• Vulnerable populations.

Related Conditions & MeSH terms

• Clinical Decision Support System

Intervention

Procedure:
• intubation for general anesthesia
routine intubation for general anesthesia

Locations

Country	Name	City	State
Taiwan	Kaohsiung Medical University Chung-Ho Memorial Hospital	Kaohsiung	Sanmin Dist

Sponsors (1)

Lead Sponsor	Collaborator
Kaohsiung Medical University Chung-Ho Memorial Hospital

Country where clinical trial is conducted

Taiwan, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	A pre-anesthesia evaluation	The examination includes airway assessment and dental evaluation.	pre-anesthetic consultation about 20 min
Primary	Perform non-invasive imaging capture.	The capture involves non-invasive imaging of the patient's facial features through standard basic photography, excluding any additional radiographic imaging examinations.The patient's images will be stored in de-identified form.	pre-anesthetic consultation about 5 min
Primary	difficult intubation prediction	The prediction of difficult intubation from pre-anesthesia evaluation and non-invasive imaging capture	after pre-anesthetic consultation about 5 min
Secondary	time to successfully extubate the nasotracheal tube after anesthesia	early extubation allowable	from the end of surgery to the post-anesthesia care, assessed up to one hour
Secondary	safely discharged from post-anesthesia care unit (postoperative recovery room)	as calculating the time from patient is delivered to postoperative recovery room to be safely discharged from recovery room by using the aldrete scores (activities level, respiration, circulation, conscious level, oxygenation) full back to pre-operative level or ten scores.	2 hours
Secondary	side effects and adverse events	records any abnormal surgical or anesthesia related findings during this admission	intraoperative and postoperative stages, assessed up to 48 hours