Construction of Early Warning Model for Pulmonary Complications Risk of Surgical Patients Based on Multimodal Data Fusion

NCT06057688 | Unknown

• 1 other identifier: ChiCTR2300072424
• Study Type: observational
• Target: 1,770
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this observational study is to establish an intelligent early warning system for acute and critical complications of the respiratory system such as pulmonary embolism and respiratory failure. Based on the electronic case database of the biomedical big data research center and the clinical real-world vital signs big data collected by wearable devices, the hybrid model architecture with multi-channel gated circulation unit neural network and deep neural network as the core is adopted, Mining the time series trends of multiple vital signs and their linkage change characteristics, integrating the structural nursing observation, laboratory examination and other multimodal clinical information to establish a prediction model, so as to improve patient safety, and lay the foundation for the later establishment of a higher-level and more comprehensive artificial intelligence clinical nursing decision support system. Issues addressed in this study

1. 1.The big data of vital signs of patients collected in real-time by wearable devices were used to explore the internal relationship between the change trend of vital signs and postoperative complications (mainly including infection complications, respiratory failure, pulmonary embolism, cardiac arrest). Supplemented with necessary nursing observation, laboratory examination and other information, and use machine learning technology to build a prediction model of postoperative complications.
2. 2.Develop the prediction model into software to provide auxiliary decision support for clinical medical staff, and lay the foundation for the later establishment of a higher-level and more comprehensive AI clinical decision support system.

Conditions

Pulmonary Embolism; Respiratory Failure; Infection Complication; Cardiac Arrest

Outcome Measures

Primary Outcomes (1)

• Unplanned ICU admission

  The patient was unplanned admitted to ICU due to pulmonary complications after operation

  During the whole hospitalization, the average was 7 days

Secondary Outcomes (1)

• Death

  During the whole hospitalization, the average was 7 days

Eligibility Criteria

• Age: 14 Years - 90 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Clinical information of patients in general surgery (gastrointestinal surgery, biliary surgery, pancreatic surgery)

You may qualify if:

• aged from 14 to 90 years; ② Patients undergoing surgery under general anesthesia; ③ Informed consent to participate in this study

You may not qualify if:

• The operation duration is less than 1 hour; ② Patients who cannot wear sensors for vital signs monitoring due to local skin abnormalities; ③ Combined with bilateral axillary surgery; ④ Incomplete bilateral axillary skin

Sponsors & Collaborators

• Renrong Gong: lead

Study Sites (1)

West China Hospital, Sichuan University.

Chengdu, Sichuan, 610041, China

RECRUITING

MeSH Terms

Conditions

Pulmonary Embolism; Respiratory Insufficiency; Heart Arrest

Condition Hierarchy (Ancestors)

Lung Diseases; Respiratory Tract Diseases; Embolism; Embolism and Thrombosis; Vascular Diseases; Cardiovascular Diseases; Respiration Disorders; Heart Diseases

Study Officials

• GONG professor

  West China Hospital

  STUDY DIRECTOR

Central Study Contacts

GONG professor

CONTACT

+862885421887; gongrenrong@wchscu.cn

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Prof.Gongrenrong

Study Record Dates

• First Submitted: August 7, 2023
• First Posted: September 28, 2023
• Study Start: August 1, 2023
• Primary Completion: October 1, 2024
• Study Completion: December 31, 2024
• Last Updated: September 28, 2023

Record last verified: 2023-09

Locations

CN (1)