Identification of Subjects with Insulin Resistance and β-Cell Dysfunction Using Alternative Definitions of the Metabolic Syndrome
Notice bibliographique
Résumé
Recently, the metabolic syndrome (MetS) has attracted much attention as a risk cluster for cardiovascular disease. Although it is believed that individuals with the MetS have insulin resistance (IR), there are few data using direct measures of IR such as glucose clamps or frequently sampled intravenous glucose tolerance tests (FSIGTTs). We examined associations of MetS with FSIGTT-derived measures of insulin sensitivity and secretion among nondiabetic subjects in the Insulin Resistance Atherosclerosis Study. Two sets of MetS criteria were evaluated: those from the 1999 World Health Organization (WHO) and the 2001 National Cholesterol Education Program (NCEP). Both WHO and NCEP MetS definitions were significantly associated with risk of being in the lowest quartile of directly measured insulin sensitivity (P < 0.0001 for all subjects as well as within ethnic subgroups). However, the associations with WHO-MetS were stronger for all subjects combined (WHO: odds ratio [OR] = 10.2; 95% CI 7.5-13.9; NCEP: OR = 4.6; 3.4-6.2) and in separate analyses of non-Hispanic whites, blacks, and Hispanics. WHO and NCEP MetS definitions were also significantly associated with risk of being in the lowest quartile of insulin sensitivity-adjusted acute insulin response (AIR) and disposition index (DI; all P < 0.01), although the associations were generally weaker than those for insulin sensitivity and there was no difference between the two definitions in all subjects combined (low AIR, WHO: OR = 1.7, 1.2-2.4; NCEP: OR = 1.7, 1.2-2.5). There were, however, a number of ethnic differences, including a stronger association of NCEP-MetS with low AIR among blacks. WHO-MetS was significantly more sensitive than NCEP-MetS in detecting low insulin sensitivity (65.4 vs. 45.6%, respectively; P < 0.0001), with no significant differences in specificity between the definitions (84.4 vs. 84.6%; P = 0.91), although WHO-MetS had a larger area under the receiver operating characteristic curve (75% vs. 65%; P < 0.0001). In conclusion, although both the WHO and NCEP MetS criteria identify nondiabetic individuals with low insulin sensitivity, the associations were notably stronger using the WHO definition. The definitions are generally less useful for identifying those with low AIR or DI, although NCEP-MetS seems to differentiate black subjects with insulin secretion defects.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».