AI-Assisted Antidiabetic Drug Consultation System for Glycemic Control in Type 2 Diabetes Patients Managed by Non-Specialist Physicians (AI-ADCS)
Clinical Validation of AI-assisted Antidiabetic Drug Consultation System-1
This study tests whether an artificial intelligence (AI) tool can help doctors choose better diabetes medicines for their patients. Type 2 diabetes is very common, but there are far more patients than diabetes specialists, so many patients are treated by doctors who are not diabetes specialists. The researchers built an AI consultation system that gives doctors real-time suggestions and predictions about diabetes medicines while they are prescribing. The doctor always makes the final decision.
In this trial, patients with type 2 diabetes whose blood sugar is not well controlled will be placed by chance (randomly) into one of two groups. In one group, the doctor uses the AI system when deciding on diabetes medicines. In the other group, the doctor prescribes as usual, without the AI system. All medicines used are already approved in Taiwan and given at approved doses.
The study follows each patient for 12 months, with check-ups at the start and at 3, 6, 9, and 12 months. The main goal is to compare how much the patients' long-term blood sugar level (HbA1c) improves between the two groups after one year. The researchers also look at how many patients reach their blood sugar target, how often low blood sugar happens, and whether any side effects occur. The aim is to find out whether using the AI tool leads to better blood sugar control.
研究概览
地位
研究类型
注册 (估计的)
阶段
- 不适用
联系人和位置
学习联系方式
- 姓名：Yi-Cheng Chang, M.D.
- 电话号码：886+0972651027
- 邮箱：b83401040@gmail.com
研究联系人备份
- 姓名：Pan Hou Che, PhD student
- 电话号码：886+0987197997
- 邮箱：d12456001@g.ntu.edu.tw
学习地点
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Taipei、台湾、100
- National Taiwan University Hospital
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接触：
- Yi-Cheng Chang, M.D.
- 电话号码：886+0972651027
- 邮箱：b83401040@gmail.com
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-
参与标准
资格标准
适合学习的年龄
- 成人
- 年长者
接受健康志愿者
描述
Inclusion Criteria:
- Adults aged 18 to 80 years
- Diagnosis of type 2 diabetes for at least 6 months
- HbA1c above 8% within the past 3 months
- Currently using one or more oral antidiabetic drugs
- Able to understand and provide written informed consent
Exclusion Criteria:
- Pregnancy or breastfeeding
- Recent participation in another interventional clinical trial
- Cognitive impairment precluding understanding of the study
- Active cancer treatment within the past 6 years
- Use of systemic steroids
学习计划
研究是如何设计的？
设计细节
- 主要用途：治疗
- 分配：随机化
- 介入模型：并行分配
- 屏蔽：单身的
武器和干预
参与者组/臂 |
干预/治疗 |
|---|---|
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实验性的：AI-Assisted Prescribing
Non-specialist physicians prescribe antidiabetic medications after consulting the AI-assisted antidiabetic drug consultation system.
The system provides real-time, interactive prescribing recommendations, a drug-prioritization order, and outcome predictions.
The physician retains full control over the final prescribing decision.
All medications are approved in Taiwan and prescribed within approved dose ranges.
Patients are followed for 12 months.
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A machine-learning based clinical decision support software that provides non-specialist physicians with real-time, interactive antidiabetic prescribing recommendations, a drug-prioritization order, and outcome predictions (e.g., the predicted likelihood of reaching glycemic targets and responder/non-responder status for individual drugs).
The system was developed and validated using the NTUH integrated medical database platform.
It provides advisory recommendations only; the treating physician retains full control over the final prescribing decision.
All recommended medications are approved in Taiwan and within approved dose ranges.
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有源比较器：Manual Prescribing (Non-AI)
Non-specialist physicians prescribe antidiabetic medications manually according to usual clinical practice, without using the AI consultation system.
All medications are approved in Taiwan and prescribed within approved dose ranges.
Patients are followed for 12 months.
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Antidiabetic medications prescribed manually by non-specialist physicians according to usual clinical practice, without using the AI consultation system.
All medications are approved in Taiwan and prescribed within approved dose ranges.
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研究衡量的是什么？
主要结果指标
结果测量 |
措施说明 |
大体时间 |
|---|---|---|
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Change in HbA1c from baseline to 12 months
大体时间：Baseline and 12 months
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The between-group difference in the change in glycated hemoglobin (HbA1c) from baseline to 12 months, comparing the AI-assisted prescribing arm with the manual prescribing (control) arm.
HbA1c reflects long-term glycemic control.
The primary analysis uses analysis of covariance (ANCOVA) adjusting for baseline HbA1c, following the intention-to-treat principle.
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Baseline and 12 months
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次要结果测量
结果测量 |
措施说明 |
大体时间 |
|---|---|---|
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Proportion of participants achieving HbA1c < 7.0% at 12 months
大体时间：12 months
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The proportion of participants reaching the glycemic target of HbA1c below 7.0% at 12 months, compared between arms using chi-square tests.
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12 months
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Incidence of hypoglycemia over 12 months
大体时间：Up to 12 months
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Incidence of hypoglycemic events over the 12-month follow-up, graded by severity: Level 1, glucose < 70 mg/dL (3.9 mmol/L) and ≥ 54 mg/dL (3.0 mmol/L); Level 2, glucose < 54 mg/dL (3.0 mmol/L); Level 3, severe hypoglycemia requiring assistance of another person regardless of glucose value.
Compared between arms using Poisson regression.
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Up to 12 months
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Incidence of prespecified adverse events over 12 months
大体时间：Up to 12 months
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Incidence of prespecified adverse events over the 12-month follow-up, including urinary tract infection, lower-limb edema, signs of heart failure, fractures, nausea, vomiting, and diarrhea.
Compared between arms using Poisson regression.
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Up to 12 months
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Change in HbA1c from baseline at 3, 6, 9, and 12 months
大体时间：Baseline, 3, 6, 9, and 12 months
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Baseline, 3, 6, 9, and 12 months
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合作者和调查者
研究记录日期
研究主要日期
学习开始 (估计的)
初级完成 (估计的)
研究完成 (估计的)
研究注册日期
首次提交
首先提交符合 QC 标准的
首次发布 (实际的)
研究记录更新
最后更新发布 (实际的)
上次提交的符合 QC 标准的更新
最后验证
更多信息
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