Development and Validation of a Digital Twin-based Clinical Research System (X Town Stage I)

Shanghai 6th People's Hospital1,500 enrolled

Overview

Chronic diseases, characterized by their prolonged duration and slow progression, have emerged as predominant contributors to global morbidity and mortality. The investigators have developed a digital twin-based clinical research system (termed X Town) for chronic diseases, to predict clinical outcomes under various interventions. In this study, the investigators aim to evaluate the reliability of the developed digital twin-based clinical research system in predicting short-term clinical outcomes via virtual and real-world clinical studies.

Study Type

OBSERVATIONAL

Enrollment

1,500

Conditions

Chronic Disease

Eligibility

Sex: ALLMin age: 18 Years

Medical Language ↔ Plain English

Inclusion Criteria: 1. Age≥18 years old 2. Receiving care at a community health service centre 3. Able to understand and comply with the study procedures 4. Agrees to participate in the study and signs the informed consent form Exclusion Criteria: 1. Patients with severe mental illness 2. Patients expected to be unable to complete follow-ups

Locations (1)

Shanghai Health and Medical Center

Wuxi, Jiangsu, China

Outcomes

Primary Outcomes

The agreement between the simulated short-term clinical outcomes in the virtual clinical studies and the real-world short-term clinical outcomes in the real-world clinical studies

We will use three predefined binary metrics to evaluate the agreement: (1) full statistical significance agreement, defined by effect estimates and CIs of the virtual and real-world clinical studies on the same side of the null; (2) estimate agreement, defined by whether effect estimates for the virtual clinical studies fell within the 95% CI for the real-world clinical study results; (3) standardized difference agreement between treatment effect estimates from the real-world clinical studies and the virtual clinical studies, defined by standardized differences (Reference: JAMA. 2023;329(16):1376-1385. doi:10.1001/jama.2023.4221).

Time frame: Within 3 months