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Validation of Insulin Dose Prediction Model Based on Artificial Intelligence Algorithm

Validation of Insulin Dose Prediction Model Based on Long Short- Term Memory Artificial Intelligence Algorithm

Status
Recruiting
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT07066891
Enrollment
400
Registered
2025-07-15
Start date
2025-07-15
Completion date
2026-06-30
Last updated
2025-08-14

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

Conditions

Diabetes Mellitus, Type 2 Diabetes

Keywords

long short-term memory, type 2 diabetes mellitus, continuous subcutaneous insulin infusion, intensive insulin therapy, insulin dose prediction model

Brief summary

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.

Detailed description

Data-driven artificial intelligence (AI) represents a new frontier in the modern medical field. The research group previously constructed a database included over 20 years clinical data of short-term intensive insulin therapy (SIIT) via continuous subcutaneous insulin infusion (CSII) in hospitalized patients with type 2 diabetes.The researchers had trained an insulin dose prediction model based on the database using long short-term memory (LSTM) AI algorithms. To establish more robust evidence to validate the efficacy and safety for this model, the present study aims to conduct a pilot prospective controlled trial comparing between AI prediction model and clinician's experience. Specifically, a randomized controlled trial is performed to compare the efficacy and safety of blood glucose control between the insulin dose prediction model and physicians' subjective experience in hospitalized patients with type 2 diabetes mellitus (T2DM) receiving CSII treatment in the Department of Endocrinology. A random number table of 400 participants will be generated using Excel, and randomly allocated into the prediction model group (n=200) and the empirical group (n=200). Medical data will be collected for all the enrolled patients, including medical history, physical examination, auxiliary test reports, continuous glucose monitoring (CGM) data, in which 8 points of the blood glucose (before and 2 hours- postprandial of the 3 main meals, bedtime, and 3 a.m. in the morning) are specifically collected to feed the model for prediction and used for comparisons. For the prediction model group, baseline information upon admission (including age, body mass index \[BMI\], weight, waist circumference, fasting blood glucose before admission and glycated hemoglobin) is put into the model, which will immediately return the insulin dosage (basal rate and boluses for each meal) for the first day of the insulin pump treatment. Physicians will then issue and execute these orders. On the following days, the model adjust the basal rate and boluses based on the previous day's glucose levels and insulin dosages. This process will continue iteratively during the whole CSII period (around 1 to 2 weeks based on whether or not the patient is newly diagnosed or with different disease durations). Insulin pump will be suspended after the administration of dinner bolus on the final day. Fasting blood glucose on the next day after insulin pump suspension will be recorded to conclude the study. In the control (emperical) group, physicians (residents under the guidance of attending doctors) determine insulin dosage based on individual clinical experience and daily glucose monitoring, with patient data collection identical to the prediction model group. Statistical analyses comparing between-group differences in glucose control during CSII treatment, such as time in range (TIR), time below range (TBR), mean blood glucose, glycemic variability, and post-therapy fasting glucose, insulin doses, etc to evaluate the efficacy and saftey of the two insulin dosage determination methods.

Interventions

DRUGCSII in the prediction model group

1. Everyday insulin dosage decided by AI prediction model. 2. CSII treatment continues for 1 to 2 weeks based on whehter or not the patient is newly diagnosed or with different disease duration.

DRUGCSII in the empirical group

1. Everyday insulin dosage decided by clinicans' experience. 2. CSII treatment continues for 1 to 2 weeks based on whether or not the patient is newly diagnosed or with different disease duration.

Sponsors

Sun Yat-sen University
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
NONE

Intervention model description

The insulin dose prediction model is constructed based on the database from the investigator's department, included all the type 2 diabetes mellitus (T2DM) patients who underwent short-term CSII therapy over the past 20 years. By combining patients' clinical characteristics, the investigators have input the daily capillary blood glucose (CBG) readings and insulin dose adjustment orders from the intensive therapy period into machine learning algorithms. Using a long short-term memory (LSTM) model, the system automatically extracted features and established memory patterns. Through iterative training and model optimization, the model was developed to predict the daily required insulin infusion doses (both basal rates and preprandial boluses) for any given blood glucose level.

Eligibility

Sex/Gender
ALL
Age
18 Years to 75 Years
Healthy volunteers
No

Inclusion criteria

1. Meets the diagnostic criteria of type 2 diabetes mellitus in the Chinese Guidelines for the Prevention and Treatment of Type 2 Diabetes (2020 edition). 2. Insulin pump is used to control blood glucose during hospitalization, and the duration of CSII treatment period ≥6 days and \<30 days.

Exclusion criteria

1. Diabetes other than type 2. 2. Age ≥75 years who is not suitable for intensive insulin therapy. 3. Hypoglycemic regimen other than CSII treatment, such as oral hypoglycemic drugs or multiple daily insulin injections during hospitalization. 4. With severe infection or uncontrolled acute complications (including ketoacidosis coma, hyperosmolar hyperglycemia, etc.) , or any condition that the researcher believes not suitable for the study. 5. Severe hepatic and renal insufficiency (ALT≥5 times the upper limit of normal, eGFR\<30ml/min/1.73m2) ), or patients at the acute stage of cardiovascular and cerebrovascular diseases considered unsuitable for study. 6. Pregnancy.

Design outcomes

Primary

MeasureTime frameDescription
Time in rangeDuring continuous subcutaneous insulin infusion treatment period(assessed up to 2 weeks, the treatment period between the initiation and suspension of the insulin pump)Time in range refers to the percentage time in range between 3.9mmol/L and 10.0 mmol/L in continuous glucose monitoring data during the continuous subcutaneous insulin infusion treatment period.
Time below rangeDuring continuous subcutaneous insulin infusion treatment period(assessed up to 2 weeks, the treatment period between the initiation and suspension of the insulin pump)Time below range refers to percentage time of glucose\<3.9mmol/L in continuous glucose monitoring data during the continuous subcutaneous insulin infusion treatment period.

Secondary

MeasureTime frameDescription
Post-therapy fasting blood glucose12 hours after insulin pump suspension.Insulin pump is suspended after administration of dinner bolus on the final day of continuous subcutaneous insulin infusion treatment. Fasting blood glucose is collected on the next moning before breakfast (12 hours after insulin pump suspension).
HbA1c at 3 months after discharge3 months after discharge.Patients are followed at 3 months after discharge from hospital, glycated hemoglobin A1c is collected during the visit.

Other

MeasureTime frameDescription
Insulin dosage during continuous subcutaneous insulin infusion treatment periodDuring continuous subcutaneous insulin infusion treatment period(assessed up to 2 weeks, the treatment period between the initiation and suspension of the insulin pump)Total insulin dosage per body weight in kilograme on the first day, on the day of maximum insulin dose and final day of the continuous subcutaneous insulin infusion treatment

Countries

China

Contacts

Primary ContactZhimin Huang, MD. & PhD.
hzhim@mail.sysu.edu.cn+86 13925057613
Backup ContactYuping Cao, B.S.
caoyp5@mail2.sysu.edu.cn+86 15107688525

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026