AI-assisted insulin management for type 2 diabetes patients in hospitals

Efficacy and Safety of the Artificial Intelligence-assisted Insulin Dose Adjustment System for Glycaemic Control in Patients With Type 2 Diabetes Mellitus in General Wards: a Multicentre, Single-blind, Randomised Controlled Study

Not applicable Interventional Shanghai Zhongshan Hospital · NCT06319300

This study is testing whether using an AI system to manage insulin can help hospitalized patients with type 2 diabetes have better blood sugar control compared to traditional methods led by doctors.

Quick facts

PhaseNot applicable
Study typeInterventional
Enrollment140 (estimated)
Ages18 Years and up
SexAll
SponsorShanghai Zhongshan Hospital Academic / other
Drugs / interventionsprednisone
Locations1 site (Shanghai, Shanghai Municipality)
Trial IDNCT06319300 on ClinicalTrials.gov

What this trial studies

This study evaluates the effectiveness of an artificial intelligence-assisted insulin dosimetry system compared to traditional physician-led insulin adjustments for patients with type 2 diabetes admitted to general wards. A total of 140 patients will be randomly assigned to either the AI-assisted group or the physician-led group to assess glycaemic control and safety outcomes. The study aims to determine if AI can improve insulin dosing accuracy and patient outcomes during hospitalization. The trial is single-blind and multicentre, ensuring a robust comparison of the two approaches.

Who should consider this trial

Good fit: Ideal candidates include adults aged 18 and older with a diagnosis of type 2 diabetes for more than three months, requiring insulin therapy during a hospital stay.

Not a fit: Patients with type 1 diabetes, severe complications, or other significant health issues may not benefit from this study.

Why it matters

Potential benefit: If successful, this approach could lead to improved blood glucose control and reduced risk of complications for hospitalized patients with type 2 diabetes.

How similar studies have performed: Other studies have shown promise in using AI for diabetes management, suggesting potential for success in this novel application.

Eligibility criteria

Show full inclusion / exclusion criteria
Inclusion Criteria:

* Diagnosis of type 2 diabetes mellitus \> 3 months
* Age≥18 years old
* Receiving glucose-lowering therapy for at least 90 days
* Blood glucose:7.8-22.2 mmol/L
* Length of proposed hospitalisation ≥5 days

Exclusion Criteria:

* Type 1 diabetes mellitus, other special types of diabetes mellitus.
* BG\>22.2 mmol/L, or acute complications of diabetes, such as diabetic ketoacidosis, diabetic hyperosmolar state.
* History of severe or repeated hypoglycaemia
* BMI≥45 kg/m2
* Pregnant and lactating women
* Clinically relevant liver disease (established cirrhosis and portal hypertension);
* Presence of severe renal disease (serum creatinine ≥3.0 mg/dL or estimated glomerular filtration rate \<30 ml/min/1.73 m2);
* Severe cardiac insufficiency;
* Patients on cortisol-based hormone therapy (equivalent to a prednisone dose \>5 mg/day);
* Psychiatric abnormalities or impaired cognitive function;
* Patients with severe oedema, infection, or peripheral blood circulation disorder;
* Patients with severe illness or patients to be transferred to ICU for treatment;
* Surgery of the heart or abdomen that may have a significant impact on the test is planned during hospitalisation.

Where this trial is running

Shanghai, Shanghai Municipality

How to participate

  1. Review the eligibility criteria above with your treating physician.
  2. Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
  3. Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions Diabetes Type 2diabetesinsulin
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.