Not_yet_recruitingNCT07611695

Artificial Intelligence-driven Tuberculosis Landscape Analysis & Stratification Research

Sponsor: Huashan Hospital

Trial Details

ConditionPulmonary Tuberculosis, Tuberculosis (TB), Tuberculosis Active
StatusNot_yet_recruiting
Participants31,600
Est. Completion31 Dec 2027
Last Updated28 May 2026

Primary Outcome

Predictive Performance of the "Easy-to-Treat" versus "Hard-to-Treat" stratification model for pulmonary tuberculosis (PTB)

Eligibility Criteria

Inclusion Criteria

Inclusion Criteria for Model Development Cohort: * Patient with clinically diagnosed or bacteriologically confirmed pulmonary tuberculosis (TB) who received TB treatment; * Initiation of TB treatment on or after January 1, 2021; * Complete key diagnosis and treatment data available in the electronic medical record system. Inclusion Criteria for External Validation Cohort: * Patient with clinically diagnosed or bacteriologically confirmed pulmonary tuberculosis (TB) who is planning to start TB treatment; * Voluntary participation with signed informed consent form (for adults ≥18 years); parental / guardian consent and co-signed informed consent form are required for minors aged ≤ 18 years. Exclusion Criteria: * Co-morbidity confounding: the presence of other active, life-threatening disease (e.g. late-stage malignancy, non-HIV severe immunodeficiency) for which the expected survival or priority of treatment may substantially interfere with the attribution of TB treatment outcomes; * Extremely poor treatment adherence: documented evidence indicating that the patient either never initiated treatment or was permanently lost to follow-up within the early treatment period (\<2 weeks), precluding the collection of any valid outcome data.

Trial Sites

Countries

China
View Registry Entry

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