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NCT Number: NCT07301892

Generative AI Impact on Rheumatoid Arthritis Complications Diagnosis

Generative AI (GenAI) based on large language models (LLMs) is expected to improve the diagnosis and treatment of autoimmune diseases. We are studying how GenAI may affect the diagnosis of various complications of rheumatoid arthritis (RA). In a retrospective study using RA patients' EHR records, we will quantify physician adoption of GenAI predictions for RA complications and co-existing diseases. In a prospective observational study, we will assess the feasibility of using GenAI predictions as additional clinical information to help physicians make more complete diagnoses of RA complications and co-existing diseases, including complex, uncommon, or rare conditions.

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Key information

Conditions

Rheumatoid Arthritis (RA Amyloidosis Arthritis Arthritis, Rheumatoid Autoimmune Diseases Bone Diseases Bone Diseases, Metabolic Cardiovascular Diseases Connective Tissue Diseases Digestive System Diseases Dry Eye Syndromes Embolism and Thrombosis Endocrine System Diseases Eye Diseases Immune System Diseases Interstitial Lung Disease Joint Diseases Lacrimal Apparatus Diseases Liver Disorders Lung Diseases Lung Diseases, Interstitial Metabolic Diseases Mouth Diseases Musculoskeletal Diseases Nervous System Diseases Neuromuscular Diseases Nutritional and Metabolic Diseases Osteoarthritis Osteoporosis Peripheral Nervous System Diseases Peripheral Neuropathy Proteostasis Deficiencies Pulmonary Complications RA Complications Renal Lesions Respiratory Tract Diseases Rheumatic Diseases Salivary Gland Diseases Sjogren's Syndrome Skin and Connective Tissue Diseases Stomatognathic Diseases Thrombosis Thyroid Diseases Vascular Diseases Vasculitis Xerostomia

Sex eligibility

All sexes

Study type

Observational

Primary location

Guang'anmen Hospital of China Academy of Chinese Medical Sciences

Beijing, Beijing Municipality, 100053, China

Location status: Recruiting

Location contact

Quan Jiang, MD

CONTACT

[email protected]

010-88001942

Quan Jiang, MD

PRINCIPAL_INVESTIGATOR

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Patients with an initial diagnosis of rheumatoid arthritis (RA).
  • All real-world RA inpatients admitted to our department.
  • Admission occurring within the real-world data study period.

Exclusion criteria

  • Patients subsequently confirmed not to have RA during the study.

Treatment and study plan

Generative AI prediction report for RA complications

Other

Generative AI based on multiple large language models (LLMs) is used to predict potential complications and co-existing diseases in patients with rheumatoid arthritis using EHR data available at admission. Physicians use these AI predictions as additional information to adjust their diagnostic plans during differential diagnosis. The impact of this intervention on the final diagnoses at discharge will be measured.

Before the prospective study, the adoptability of the generative AI prediction reports will be validated using EHR records from retrospective RA patients.

Primary outcomes

  1. Will physicians adopt GenAI predictions in diagnosing RA complications?

    Time frame: Immediately after reviewing patient AI report on the day of admission.

    In the routine care workflow, large language models (LLMs) are used to predict potential RA complications for each de-identified patient case and generate an AI report listing possible complications and co-existing diseases. Additional diagnostic tests are suggested to verify the predicted conditions. After reviewing the AI report, physicians immediately evaluate each disease prediction using a 5-point Likert scale (1 = complete disagreement; 2 = disagreement; 3 = neutral; 4 = agreement; 5 = complete agreement). The mean score is calculated as a measure of perceived prediction accuracy. Physicians also indicate whether each specific disease prediction could potentially be adopted or used to assist differential diagnosis (binary: 0 or 1). The percentage of positive adoption responses is calculated as a measure of potential adoption rate, or adoptability.

Secondary outcomes

  1. To what extent are RA complication diagnoses actually affected by GenAI predictions?

    Time frame: Immediately after making the final diagnosis at discharge.

    Before patient discharge, physicians make final diagnoses and record which diagnosed complications or co-existing diseases were influenced by GenAI prediction information for each patient. The percentage of cases in which GenAI predictions affected the final diagnosis is calculated as a measure of AI's actual impact on routine diagnostic practice.

Study contacts

Contact information is provided by the study sponsor or research team.

Quan Jiang Guang'anmen Hospital, China Academy of Chinese Medical Science

CONTACT

[email protected]

010-88001942

Sponsors and collaborators

Lead sponsor

Guang'anmen Hospital of China Academy of Chinese Medical Sciences

Other

Registry information

Official study title

Impact of Generative Artificial Intelligence on Diagnosing Rheumatoid Arthritis Complications

Important dates

Study start
2025
Primary completion
2026
Study completion
2026
First posted
Dec 24, 2025
Registry last updated
Dec 24, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

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This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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