Clinical Decision Support System
Conditions
Keywords
knowledge graph, artificial intelligence, Enhanced Recovery After Surgery
Brief 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.
Detailed 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.
Interventions
PROCEDUREintubation for general anesthesia
routine intubation for general anesthesia
Sponsors
Kaohsiung Medical University Chung-Ho Memorial Hospital
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 85 Years
Healthy volunteers
Yes
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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| A pre-anesthesia evaluation | pre-anesthetic consultation about 20 min | The examination includes airway assessment and dental evaluation. |
| Perform non-invasive imaging capture. | pre-anesthetic consultation about 5 min | 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. |
| difficult intubation prediction | after pre-anesthetic consultation about 5 min | The prediction of difficult intubation from pre-anesthesia evaluation and non-invasive imaging capture |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| time to successfully extubate the nasotracheal tube after anesthesia | from the end of surgery to the post-anesthesia care, assessed up to one hour | early extubation allowable |
| safely discharged from post-anesthesia care unit (postoperative recovery room) | 2 hours | 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. |
| side effects and adverse events | intraoperative and postoperative stages, assessed up to 48 hours | records any abnormal surgical or anesthesia related findings during this admission |
Countries
Taiwan
Contacts
Primary ContactTz Ping Gau, MD
Backup ContactKuang-I Cheng, MD,Phd
Outcome results
None listed