EligibleTrials

Validation of Insulin Dose Prediction Model Based on Artificial Intelligence Algorithm

Recruiting · NCT07066891 · Interventional (participants receive a specific treatment) · Lead sponsor: Sun Yat-sen University

View the official record on ClinicalTrials.gov →
Type 2 Diabetes

Interventions studied

CSII in the empirical groupCSII in the prediction model group

What this trial is about

The present study aims to conduct a prospective controlled trial comparing an LSTM-based artificial intelligence (AI) prediction model and clinicians' experience in the efficacy and safety of blood glucose control in hospitalized patients with type 2 diabetes mellitus (T2DM) receiving continuous subcutaneous insulin infusion (CSII) treatment in the Department of Endocrinology. The main question it aims to answer is: Is the prediction model superior to or (at least) non-inferior to clinicians' experience? Eligible patients who receive CSII treatment are randomly allocated into the prediction model group and the empirical group. Patients will: 1. Receive CSII treatment as standard of care during hospitalization for 1-2 weeks, where the daily insulin dose regimen is determined by a prediction model or a clinician's experience. 2. Use continuous glucose monitoring (CGM) for glucose tracking. 3. Receive diabetes self-management education covering nutrition and physical activity.

Who can take part

Age range
18 Years to 75 Years
Sex
All (male and female)
Healthy volunteers
No - a diagnosis or condition is required
Phase
Not applicable (e.g. observational or device study)
Study type
Interventional (participants receive a specific treatment)

Inclusion criteria

Exclusion criteria

Where it is running

1 location listed.

Read the full protocol, contacts and eligibility on ClinicalTrials.gov →

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