Contrast Between Traditional Regression Model and AI in Predicting Prolonged Stay Stay After Head and Neck Tumors

NCT ID: NCT06570486

Last Updated: 2024-08-26

Basic Information

• Recruitment Status: RECRUITING
• Total Enrollment: 700 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2024-03-01
• Study Completion Date: 2025-04-01

Brief Summary

This experiment is an observational study of cohort. By establishing a cohort of patients with head and neck tumors transferred to ICU after surgery, investigators compared the prediction effect of AI and the traditional prediction model on whether patients can be transferred to ICU within 24 hours of head and neck tumors. First retrospective analysis of patients after head and neck tumor surgery, medical records were collected, the test results are divided into training group and validation group according to 7:3, divided into 2 groups according to the patient ICU stay time is greater than 24 hours, the prediction model after the ICU duration of head and neck tumor surgery after more than 24 hours. At the same time, clean the data, train the AI with the data, and compare the effectiveness of both sides with the ROC. After the establishment of prediction model and AI training, the patients included in the cohort were evaluated by prediction model and AI immediately after being transferred to the ICU, predicting the possibility of transferring out of the ICU within 24 hours.

Conditions

Head and Neck Cancer

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: CROSS_SECTIONAL

Study Groups

training group

For training models

No interventions assigned to this group

test group

Used to validate the model

No interventions assigned to this group

Prospective cohort

For the prospective validation of the model

No interventions assigned to this group

Eligibility Criteria

Inclusion Criteria

1. Patients after head and neck tumors;

2. older than 18 years.

Exclusion Criteria

1. Patients transferred to ICU twice after head and neck tumors;

2. Patients with unplanned transfer to the ICU.

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Locations

Sun Yat-sen Memorial Hospital, Sun Yat-sen University

Guangzhou, Guangdong, China

Site Status: RECRUITING

Countries

China

Facility Contacts

Zhengfei Yang

Role: primary

yangzhengfei@vip.163.com

13632370949

Provided Documents

Document Type: Study Protocol

View Document

Document Type: Informed Consent Form

View Document

Other Identifiers

SYSKY-2024-403-01

Identifier Type: -

Identifier Source: org_study_id