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
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,032 | 0,029 |
| Méta-épidémiologie (sens strict) | 0,006 | 0,003 |
| Méta-épidémiologie (sens large) | 0,010 | 0,007 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,004 | 0,004 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,009 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,055 | 0,012 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».