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.
연구 개요
상태
연구 유형
등록 (추정된)
단계
- 해당 없음
연락처 및 위치
연구 연락처
- 이름: Yi-Cheng Chang, M.D.
- 전화번호: 886+0972651027
- 이메일: b83401040@gmail.com
연구 연락처 백업
- 이름: Pan Hou Che, PhD student
- 전화번호: 886+0987197997
- 이메일: d12456001@g.ntu.edu.tw
연구 장소
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Taipei, 대만, 100
- National Taiwan University Hospital
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연락하다:
- Yi-Cheng Chang, M.D.
- 전화번호: 886+0972651027
- 이메일: b83401040@gmail.com
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참여기준
자격 기준
공부할 수 있는 나이
- 성인
- 고령자
건강한 자원 봉사자를 받아들입니다
설명
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
공부 계획
연구는 어떻게 설계됩니까?
디자인 세부사항
- 주 목적: 치료
- 할당: 무작위
- 중재 모델: 병렬 할당
- 마스킹: 하나의
무기와 개입
참가자 그룹 / 팔 |
개입 / 치료 |
|---|---|
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실험적: 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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활성 비교기: 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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연구는 무엇을 측정합니까?
주요 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
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Change in HbA1c from baseline to 12 months
기간: 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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2차 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
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Proportion of participants achieving HbA1c < 7.0% at 12 months
기간: 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
기간: 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
기간: 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
기간: Baseline, 3, 6, 9, and 12 months
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Baseline, 3, 6, 9, and 12 months
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공동 작업자 및 조사자
연구 기록 날짜
연구 주요 날짜
연구 시작 (추정된)
기본 완료 (추정된)
연구 완료 (추정된)
연구 등록 날짜
최초 제출
QC 기준을 충족하는 최초 제출
처음 게시됨 (실제)
연구 기록 업데이트
마지막 업데이트 게시됨 (실제)
QC 기준을 충족하는 마지막 업데이트 제출
마지막으로 확인됨
추가 정보
이 정보는 변경 없이 clinicaltrials.gov 웹사이트에서 직접 가져온 것입니다. 귀하의 연구 세부 정보를 변경, 제거 또는 업데이트하도록 요청하는 경우 register@clinicaltrials.gov. 문의하십시오. 변경 사항이 clinicaltrials.gov에 구현되는 즉시 저희 웹사이트에도 자동으로 업데이트됩니다. .
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