Pulmonary Embolism Clinical Trial
Official title:
(Professor Gong Renrong) Ward Matron
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. 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. 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.
Status | Recruiting |
Enrollment | 1770 |
Est. completion date | December 31, 2024 |
Est. primary completion date | October 1, 2024 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | 14 Years to 90 Years |
Eligibility | Inclusion Criteria: - aged from 14 to 90 years; ? Patients undergoing surgery under general anesthesia; ? Informed consent to participate in this study Exclusion Criteria: - The operation duration is less than 1 hour; ? Patients who cannot wear sensors for vital signs monitoring due to local skin abnormalities; ? Combined with bilateral axillary surgery; ? Incomplete bilateral axillary skin |
Country | Name | City | State |
---|---|---|---|
China | West China Hospital, Sichuan University. | Chengdu | Sichuan |
Lead Sponsor | Collaborator |
---|---|
Renrong Gong |
China,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | 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 | Death | The patient died after surgery due to pulmonary complications | During the whole hospitalization, the average was 7 days |
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