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.
調査の概要
状態
条件
研究の種類
入学 (推定)
段階
- 適用できない
連絡先と場所
研究連絡先
- 名前：Yi-Cheng Chang, M.D.
- 電話番号：886+0972651027
- メール：b83401040@gmail.com
研究連絡先のバックアップ
- 名前：Pan Hou Che, PhD student
- 電話番号：886+0987197997
- メール：d12456001@g.ntu.edu.tw
研究場所
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Taipei、台湾、100
- National Taiwan University Hospital
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コンタクト：
- Yi-Cheng Chang, M.D.
- 電話番号：886+0972651027
- メール：b83401040@gmail.com
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-
参加基準
適格基準
就学可能な年齢
- 大人
- 高齢者
健康ボランティアの受け入れ
説明
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
研究計画
研究はどのように設計されていますか？
デザインの詳細
- 主な目的：処理
- 割り当て：ランダム化
- 介入モデル：並列代入
- マスキング：独身
武器と介入
参加者グループ / アーム |
介入・治療 |
|---|---|
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実験的：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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アクティブコンパレータ：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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この研究は何を測定していますか？
主要な結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
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Change in HbA1c from baseline to 12 months
時間枠：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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二次結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
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Proportion of participants achieving HbA1c < 7.0% at 12 months
時間枠：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
時間枠：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
時間枠：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
時間枠：Baseline, 3, 6, 9, and 12 months
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Baseline, 3, 6, 9, and 12 months
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協力者と研究者
研究記録日
主要日程の研究
研究開始 (推定)
一次修了 (推定)
研究の完了 (推定)
試験登録日
最初に提出
QC基準を満たした最初の提出物
最初の投稿 (実際)
学習記録の更新
投稿された最後の更新 (実際)
QC基準を満たした最後の更新が送信されました
最終確認日
詳しくは
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