Analysis of correlation between the mild cognitive impairment (MCI) and level of adiponectin in elderly patients with type 2 diabetes mellitus (T2DM).
Notice bibliographique
Résumé
OBJECTIVE: To investigate the correlation between the mild cognitive impairment (MCI) and serum level of adiponectin in elderly patients with Type II diabetes mellitus (T2DM), so as to provide evidence for early diagnosis of MCI and effective evaluation of the impairment of cognitive functions, thereby preventing the impairment of cognitive function as early as possible. PATIENTS AND METHODS: Clinical data were collected from 260 T2DM patients (≥ 60 years old) in Endocrine Department and 120 healthy subjects (≥ 60 years old) who underwent physical examination in our hospital between June 2015 and June 2017. According to the evaluation results of MCI, these T2DM patients were further divided into the T2DM + MCI group (n = 138) and the T2DM + NMCI group (n = 122). General data, including gender, age, disease history and body mass index (BMI), and the laboratory indexes, including serum adiponectin, fasting blood glucose (FBG), glycosylated hemoglobin (HbA1c) and blood fat, were collected for statistical analysis in T2DM + MCI group, T2DM + NMCI group and healthy control group. RESULTS: Comparisons among T2DM + MCI group, T2DM + NMCI group and healthy control group, showed that the serum level of adiponectin in T2DM + MCI group was significantly lower than those in remaining two groups (p < 0.01). Spearman correlation analysis revealed that score of Montreal Cognitive Assessment (MoCA) was positively correlated with the serum level of adiponectin (r = 0.446, p < 0.01). Multivariate linear regression analysis indicated that education (standard β = 0.325, p = 0.003), age (standard β = -0.236, p = 0.016), disease course of hypertension (standard β = -0.242, p = 0.006), disease course of diabetes mellitus (standard β = -0.377, p < 0.001) and the level of adiponectin were correlated with the cognitive impairment. The results of itemized assessment in MoCA scale showed that in T2DM + MCI group, the scores in visuospatial and executive abilities, attention, language and orientation were significantly lower than those in other two groups (p < 0.01). As for the delayed recall, the score in T2DM + MCI group was significantly lower than those in other two groups (p < 0.01), while the score in T2DM + NMCI group was lower than that in the healthy control group (p < 0.01); in terms of the naming ability and abstraction, no statistically significant differences were identified among three groups (p > 0.05). CONCLUSIONS: Age, poor education, disease course of hypertension, disease course of diabetes mellitus and a low level of adiponectin in serum are the risk factors in MCI of T2DM patients. Besides, the level of adiponectin in serum of T2DM patients is correlated with the development of MCI; elderly T2DM patients are afflicted by cognitive impairment, mainly in visuospatial and executive abilities, attention, language, delayed recall and orientation.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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) | 0,001 | 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 ».