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Development and Clinical Validation of a Deep Reinforcement Learning-Based Recommendation Model for Hypoglycemic Drug Treatment in T2D Patients

Development and Clinical Validation of a Deep Reinforcement Learning-Based Recommendation Model for Hypoglycemic Drug Treatment in T2D Patients

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400093318
Enrollment
Unknown
Registered
2024-12-02
Start date
2024-12-02
Completion date
Unknown
Last updated
2024-12-09

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Type 2 Diabetes

Interventions

Prospective study:None

Sponsors

Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 80 Years

Inclusion criteria

Inclusion criteria: Retrospective study: patients with T2D who were seen on two or more occasions with an interval of 12±2 months Cross-sectional study: patients diagnosed with T2D according to the Chinese Guidelines for the Prevention and Control of Type 2 Diabetes Mellitus; aged between 18 and 80 years old; currently receiving hypoglycemic medication for T2D; willing and able to sign an informed consent form to participate in the study.

Exclusion criteria

Exclusion criteria: Retrospective study: patients with a history of acute illness or surgery were excluded. Cross-sectional studies: patients with any condition that, in the judgment of the investigator, may pose a risk to the patient or interfere with the objectives of the study; patients who are unable to communicate effectively with the investigator or are unlikely to comply with the study protocol.

Design outcomes

Primary

MeasureTime frame
HbA1C;Fasting blood glucose;Postprandial blood glucose;Diabetes Specific Quality of Life;

Secondary

MeasureTime frame
Low-Density Lipoprotein;Urinary microalbumin-to-creatinine ratio test;Glomerular filtration rate;Adverse drug reactions;Mental state;Complications;Weight;

Countries

China

Contacts

Public ContactXingwei Wu

Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital

wuxingwei@med.uestc.edu.cn+86 159 2801 7367

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026