Effect of Adherence to Oral Semaglutide on Glycemic Control in People With Type 2 Diabetes Treated With Metformin: Protocol for an Open-Label Clinical Trial
Bibliographic record
Abstract
BACKGROUND: Treatment adherence by people with type 2 diabetes (T2D) is overall suboptimal, which can hinder glycemic control. Multiple adherence barriers have been identified, such as the dislike and fear of injections. Several of the recommended antidiabetic drugs are available in oral formulations, which may be a good alternative to injection therapy when possible. However, strict dosing instruction could pose adherence barriers; for example, oral semaglutide requires predose and postdose fasting and restricted water intake at dosing time. Currently, oral semaglutide is the only oral glucagon-like peptide-1 receptor agonist and has only been available for a few years; therefore, limited knowledge exists on adherence to it. OBJECTIVE: The aim of this study is to investigate the effect of adherence to oral semaglutide dosing instructions on glycemic control in people with T2D who are dysregulated on metformin and optionally a sodium-glucose cotransporter-2 inhibitor and naïve to oral semaglutide. METHODS: This prospective, noninterventional, open-label, clinical trial with a duration of 12 weeks will be conducted in Denmark. Eligible participants are adults (aged ≥18 years) with dysregulated T2D (hemoglobin A1c of 53-75 mmol/mol) currently treated with metformin and optionally a sodium-glucose cotransporter-2 inhibitor for whom the next natural step in the treatment is to add an antidiabetic drug to the treatment regimen. Potential participants are recruited through announcements on social media and digital mail sent to their official digital mailbox (e-boks). During the trial, 20 participants will be initiated on oral semaglutide and escalated in dosage in accordance with the label. Information on the participants' behavior related to the dosing instructions will be collected using the following devices: a smartwatch to track activity and sleep time, a smart pill bottle to track dosing time, a smart bottle to track time and volume of water intake at dosing time, and a smartphone to take a photo of their breakfast to log time of breakfast. Glycemic control will be assessed using an unblinded continuous glucose monitoring sensor that the participants will wear. Participants are asked to report any cases of nausea or vomiting in terms of time of occurrence, duration, and severity. The primary endpoint is change from baseline to end-of-study time-in-range derived from continuous glucose monitoring data. RESULTS: The first participant visit was in April 2024. Three months of high frequency temporal data on adherence behavior will be collected, despite the relatively few expected participants included. CONCLUSIONS: Participants may change their behavior due to awareness of being observed. Regardless, the knowledge gained from this trial might be integrated into a decision support system, providing people with diabetes with guidance on how to increase adherence and potentially improving glycemic control. TRIAL REGISTRATION: ClinicalTrials.gov NCT06333080.; https://clinicaltrials.gov/study/NCT06333080. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/64899.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.029 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.010 | 0.007 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.055 | 0.012 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".