Continuous Glucose Monitoring With Low-Carbohydrate Diet Coaching in Adults With Prediabetes: Mixed Methods Pilot Study
Notice bibliographique
Résumé
Background Type 2 diabetes mellitus (T2DM) is preventable; however, few patients with prediabetes participate in prevention programs. The use of user-friendly continuous glucose monitors (CGMs) with low-carbohydrate diet coaching is a novel strategy to prevent T2DM. Objective This study aims to determine the patient satisfaction and feasibility of an intervention combining CGM use and low-carbohydrate diet coaching in patients with prediabetes to drive dietary behavior change. Methods We conducted a mixed methods, single-arm pilot and feasibility study at a suburban family medicine clinic. A total of 15 adults with prediabetes with hemoglobin A1c (HbA1c) levels between 5.7% and 6.4% and a BMI >30 kg/m2 were recruited to participate. The intervention and assessments took place during 3 in-person study visits and 2 qualitative phone interviews (3 weeks and 6 months after the intervention). During visit 1, participants were asked to wear a CGM and complete a food intake and craving log for 10 days. During visit 2, the food intake and craving log along with the CGM results of the participants were reviewed and the participants received low-carbohydrate diet coaching, including learning about carbohydrates and personalized feedback. A second CGM sensor, with the ability to scan and record glucose trends, was placed, and the participants logged their food intake and cravings as they attempted to reduce their total carbohydrate intake (<100 g/day). During visit 3, the participants reviewed their CGM and log data. The primary outcome was satisfaction with the use of CGM and low-carbohydrate diet. The secondary outcomes included feasibility, weight, and HbA1c change, and percentage of time spent in hyperglycemia. Changes in attitudes and risk perception of developing diabetes were also assessed. Results The overall satisfaction rate of our intervention was 93%. The intervention induced a weight reduction of 1.4 lb (P=.02) and a reduction of HbA1c levels by 0.71% (P<.001) since enrollment. Although not significantly, the percentage of time above glucose goal and average daily glucose levels decreased slightly during the study period. Qualitative interview themes indicated no major barriers to CGM use; the acceptance of a low-carbohydrate diet; and that CGMs helped to visualize the impact of carbohydrates on the body, driving dietary changes. Conclusions The use of CGMs and low-carbohydrate diet coaching to drive dietary changes in patients with prediabetes is feasible and acceptable to patients. This novel method merits further exploration, as the preliminary data indicate that combining CGM use with low-carbohydrate diet coaching drives dietary changes, which may ultimately prevent T2DM.
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 | 0,012 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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 ».