A randomized clinical trial for meal bolus decision using learning-based control in adults with type 2 diabetes
Abstract
BACKGROUND
We proposed an artificial-pancreas-like algorithm (AP-A) which could automatically determine the pre-prandial insulin dose based on intermittently scanned continuous glucose monitoring (isCGM) data trajectories in multiple dose injection (MDI) therapy. We aim to determine whether pre-prandial insulin dose adjustments guided by the AP-A is as effective and safe as physician decisions.
METHODS
We performed a randomized, single-blind, clinical trial at a tertiary, referral hospital in Beijing, China. Type 2 diabetes participants were eligible if they were aged 18 years, with a glycated hemoglobin of 8.0% or higher. Eligible participants were randomly assigned (1:1) to the AP-A arm supervised by physician and the conventional physician treatment arm. The primary objective was to compare percentage time spent with sensor glucose level in 3.9-10.0 mmol/L (TIR) between the two study arms. Safety was assessed by the percentage time spent with sensor glucose level below 3.0 mmol/L (TBR).
RESULTS
140 participants were screened, of whom 119 were randomly assigned to AP-A arm (n = 59) or physician arm (n = 60). The TIR achieved by the AP-A arm was statistically non-inferior compared with the control arm (72.4% (63.3-82.1) vs. 71.2% (54.9-81.4)), with a median difference of 1.33% (95% CI, -6.00 to 10.94, non-inferiority margin -7.5%). TBR was also statistically non-inferior between the AP-A and control arms (0.0% (0.0-0.0) vs. 0.0% (0.0-0.0), respectively; median difference…
How strong is the evidence?
Evidence Hub reads this as a randomized trial, done in people. Its evidence level is 2 of 5 (High · randomized trial). Randomized trials of a reasonable size are the strongest single-study design. Reported size: 140 participants or records.
Read the paper
Related studies
- Nano Biosensors: Properties, applications and electrochemical techniques
- Electrochemically Synthesized MIP Sensors: Applications in Healthcare Diagnostics
- Toward a Harmonization for Using in situ Nutrient Sensors in the Marine Environment
- Electrochemical determination of rutin by using NiFe2O4 nanoparticles-loaded reduced graphene oxide
- Application of Polyoxometalate-based composites for sensor systems: A review
- Sensitive Electrochemical and Thermal Detection of Human Noroviruses Using Molecularly Imprinted Polymer Nanoparticles Generated against a Viral Target
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.