Artificial Intelligence-assisted Chest X-ray in TB Screening: Effectiveness of Enhancing the Care Cascades in Chinese Primary-care Settings (ACCESS-CARE)
Trial ID: NCT06963606
Status: RECRUITING
Study type: INTERVENTIONAL
Phase: NA
Start date: 2025-09-01
Completion date: 2027-12-31
Sponsor: Xuelin Yang
Collaborators: China Medical Board (CMB); Yichang Center for Disease Control and Prevention, China; JF Intelligent Healthcare Medical Technology Co
Conditions: Tuberculosis (TB)
Interventions: Artificial intelligence-assisted chest X-ray in TB screening; Routine doctors analyze the process of chest X-rays
Locations: Township Health-care settings in Yichang City
Countries: China
Enrollment: 22000
Age range: 15 Years - None
Sex: ALL

Summary:
The global incidence rate and mortality of tuberculosis (TB) pose a challenge to achieving the goals set out in the tuberculosis eradication strategy and the SDGs by 2030. At present, timely and accessible early detection methods for tuberculosis are still a major obstacle. In this context, the emergence of artificial intelligence (AI), especially the AI-assisted chest X-ray (CXR) in the field of diagnostic imaging, has proved the potential to significantly improve the speed and accuracy of tuberculosis diagnosis. However, the extent to which these technologies can affect the broader tuberculosis care cascade, especially by reducing the diagnostic time in the population level, has not yet been explored. The proposed project plans to use the certified AI-assisted CXR system (JF CXR-1) for tuberculosis screening, which aims not only to integrate AI into the diagnosis process, but also to critically assess its impact on the overall tuberculosis care cascade. The selected location for this project is Yichang City in western Hubei Province, China, which is facing a high TB burden. The city has established a strong city-wide health big data platform ten years ago, providing the basis for this project. The project will first optimize the AI-assisted CXR system through retrospective imaging to validate the accuracy of case screening (Stage Ⅰ). Secondly, the project will shift its focus to the real world, where cluster randomized controlled trials will be conducted in primary-care settings (Stage Ⅱ). In this stage, the effectiveness of the AI-assisted CXR system in reducing the diagnostic time of TB cases will be evaluated by comparing with those settings without using the tool. In stage Ⅲ, the qualitative and quantitative methods will be used to evaluate the generalization, practicality, and feasibility of extending the screening strategy in various community environments. If the AI-assisted screening strategy is proven accurate, effective, and sustainable, it may pave the way for its widespread adoption in primary healthcare institutions and other grassroots areas in China. This can not only improve the timeliness of tuberculosis diagnosis, but also help to allocate medical resources more effectively and significantly reduce tuberculosis-related incidence and mortality, bringing positive changes to global public health. In addition, the results of the project can also provide information for policy decisions and guide the formulation of strategies to prioritize the integration of AI into health care, which can not only fight against tuberculosis but also a series of other diseases.

Eligibility criteria:
Eligibility criteria Inclusion criteria

Participants must receive medical treatment at the primary healthcare hospitals in Yichang City, Hubei Province, and underwent chest X-ray examinations. The participants have to meet the following criteria:

1. \>15 years old.
2. Appearance of tuberculosis-related respiratory symptoms or signs.
3. Individuals not previous diagnosed with active pulmonary tuberculosis.
4. Capable of completing pathogen examinations and subsequent related inspections.

Exclusion criteria

Those who meet any of the below criteria will be excluded:

1. Diagnosed with extrapulmonary tuberculosis or latent tuberculosis infection during the current visit.
2. The quality of Chest X-ray images did not meet the standard requirements.
3. Unrecognized identity information participants.

Withdrawal Criteria

1. Participants who are lost to follow-up or who do not complete the follow-up period.
2. Participants who experience a sudden and serious illness or choose not to continue participating in the study.

Outcomes:
The difference in the diagnostic yield of pulmonary tuberculosis screening in township medical and health institutions between the intervention group and the control group.