Chargement de la fiche…
Chargement de la fiche…
MonRhumato.fr utilise des cookies pour mesurer l'audience (statistiques) et améliorer le site. Aucune donnée de santé identifiable n'est jamais collectée. Politique de confidentialité.
Votre choix est conservé 13 mois (durée max CNIL). Vous pouvez le modifier à tout moment via Préférences cookies.
✨ Génération du profil synthétique IA en cours…
Secteur de conventionnement non disponible (médecin hospitalier ou non présent dans l'Annuaire santé CNAM des libéraux conventionnés).
Lien Doctolib = recherche Google site:doctolib.fr (le 1er résultat est presque toujours le profil correct s'il existe).
The Journal of clinical endocrinology and metabolism · 2016
Joint bone spine · 2000
Diabetes care · 2010
Source PubMed · Recherche par auteur (homonymes possibles, vérifier l'affiliation).
The Journal of clinical endocrinology and metabolism · 2016 · Journal Article
Vargas-Poussou R, Mansour-Hendili L, Baron S, Bertocchio JP, et al.
European journal of endocrinology · 2013 · Journal Article
Bihan H, Murat A, Fysekidis M, Al-Salameh A, et al.
Données ANS publiques (Licence Ouverte 2.0) · Enrichissements MonRhumato 100 % opt-in · Toute personne référencée peut demander la suppression ou la rectification.
OBJECTIVE We investigated the relationship between carbohydrate intake and postprandial blood glucose (BG) levels to determine the most influential meal for type 2 diabetic subjects treated with basal insulin and needing prandial insulin. RESEARCH DESIGN AND METHODS Three-day BG profiles for 37 type 2 diabetic subjects, with A1C levels of 7.7%, treated with sulfonylurea and metformin, and well titrated on insulin glargine, were analyzed using a continuous glucose monitoring system. Food intake from 680 meals was recorded and quantified during continuous glucose monitoring. RESULTS The median BG excursion (ΔBG) was higher at breakfast than at lunch or dinner (111 [81; 160] vs. 69.5 [41.5; 106] and 82.5 mg/dl [53; 119] mg/dl, P < 0.0001). There was a weak overall correlation between ΔBG and carbohydrate intake. Correlation improved when mealtime was taken into account. Simple relationships were established: ΔBG (mg/dl) = 65 × carbohydrate/body weight + 73 for breakfast (R2 = 0.20, P < 0.0001); the slope was reduced by half at lunch and by one-third at dinner. Twelve relevant variables likely to affect ΔBG were integrated into a polynomial equation. This model accounted for 49% of ΔBG variability. Two groups of patients were identified: responders, in whom ΔBG was well correlated with carbohydrate intake (R2 ≥ 0.30, n = 8), and nonresponders (R2 < 0.30, n = 29). Responders exhibited a greater insulinopenic profile than nonresponders. CONCLUSIONS The carbohydrate intake in responders clearly drives ΔBG, whereas, in nonresponders, other factors predominate. This sort of characterization should be used to guide therapeutic choices toward more targeted care with improved type 2 diabetes management.
Diabetes care · 2010 · Journal Article
Franc S, Dardari D, Peschard C, Riveline JP, et al.
Joint bone spine · 2000 · Case Reports
Khanine V, Fournier JJ, Requeda E, Luton JP, et al.