Data Driven Behavior Intervention and Medical Outcome Evaluation of Patients' Comprehensive Monitoring

Chinese Academy of Medical Sciences & Peking Union Medical College

Status: Unknown

Conditions: Infection; Diabetes; Metabolic Complication; Obesity; Metabolic Disturbance; Metabolic Syndrome

Study type: Observational

Funder types: Other

Identifiers

NCT04966754

JS-2898

Details and patient eligibility

About

During the study, the resuscitation room, general wards and ICU were installed fixed or mobile acquisition devices in the resuscitation room, the emergency department of Peking Union Medical College Hospital, and the collection platform was set up. Patients with acute diseases (infection, diabetes complications, etc.) caused by metabolic syndrome (obesity, diabetes, etc.) were selected after informed consent. All medical intervention behaviors, relevant medical records and medical outcome records within the collection scope of the device platform were collected prospectively . And regular follow-up, guidance of patients with metabolic syndrome control, while collecting all the lifestyle characteristics of patients, some patients with metabolic cabin research, and observe the relevant medical outcomes. After that, all the collected data were coded, and the influence of all lifestyle and medical behavior interventions on patients' medical outcomes was studied by artificial intelligence method.

Enrollment: 1,000 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Diabetes and / or obesity (BMI>=28).
• Emergency room / emergency ward / EICU;
• Be able to understand and agree the research protocol and sign the informed consent

Exclusion criteria

• Pregnant women / lactation period;
• The estimated survival time was less than 1 year;
• Long term follow-up is not guaranteed;
• Failure to comply with the protocol or procedure;
• The collection of medical behavior data can not complete the de privacy or label after de privacy;
• Other researchers think that it is not suitable for inclusion

Trial design