Impact of Generative Artificial Intelligence on Diagnosing Rheumatoid Arthritis Complications
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 100
- 试验地点
- 1
- 主要终点
- Will physicians adopt GenAI predictions in diagnosing RA complications?
研究概览
简要总结
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Cross Sectional
入排标准
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •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.
排除标准
- •Patients subsequently confirmed not to have RA during the study.
结局指标
主要结局
Will physicians adopt GenAI predictions in diagnosing RA complications?
时间窗: 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.
次要结局
- To what extent are RA complication diagnoses actually affected by GenAI predictions?(Immediately after making the final diagnosis at discharge.)
研究者
Quan Jiang
Director of the Rheumatology Department
Guang'anmen Hospital of China Academy of Chinese Medical Sciences