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Enregistrement W1532196684 · doi:10.1111/j.1532-5415.2006.00643_11.x

FACTORS ASSOCIATED WITH COGNITIVE IMPAIRMENT IN ELDERLY PATIENTS WITH DIABETES MELLITUS

2006· letter· en· W1532196684 sur OpenAlexaboutno aff
Mari Suzuki, Hiroyuki Umegaki, Satsuki Ieda, Nanaka Mogi, Akihisa Iguchi

Notice bibliographique

RevueJournal of the American Geriatrics Society · 2006
Typeletter
Langueen
DomaineNeuroscience
ThématiqueNeuroinflammation and Neurodegeneration Mechanisms
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineDementiaWechsler Adult Intelligence ScaleDiabetes mellitusBody mass indexInternal medicineCognitive declineCognitionStroke (engine)Memory spanTrail Making TestMontreal Cognitive AssessmentDiseasePhysical therapyPsychiatryCognitive impairmentEndocrinologyWorking memory

Résumé

récupéré en direct d'OpenAlex

To the Editor: Cognitive function in elderly subjects has recently attracted considerable attention as a complication related to diabetes mellitus (DM). Many reports indicate that several aspects of brain functions are impaired in older subjects with DM.1, 2 It has been hypothesized that inflammatory mechanisms play a role in the pathogenesis of several age-associated diseases. In addition, high plasma levels of inflammatory proteins reportedly increase the risk of cognitive decline in people without DM,3, 4 although the involvement of inflammation in DM-related cognitive impairment has not been investigated. In the present study, the association between clinical markers such as inflammatory proteins and cognitive function was investigated in nondemented elderly DM subjects. Forty-five outpatients (25 men and 20 women) ranging in age from 65 to 85 (mean age±standard deviation 72.6±5.7) were recruited at Chiaki Hospital (Aichi, Japan). Average hemoglobin A1c and body mass index were 7.0% and 24.6, respectively. Subjects with a diagnosis of dementia or whose score on the Mini-Mental State Examination (MMSE)1 was 23 or lower were excluded, as were those who had a clinical history or neurological symptoms of stroke. The cognitive assessment included MMSE; Word List Recall (immediate and delayed) from a subtest of the Alzheimer's Disease Assessment Scale;5 Digit Symbol Test, a subtest of the Wechsler Adult Intelligence Scale-Revised (WAIS-R);1 and the Stroop Color-Word Test.1 The clinical variables assessed were age, sex, years of education, DM duration, hemoglobin A1c, fasting serum glucose, immunoreactive insulin, body mass index, total cholesterol, high-density lipoprotein cholesterol, triglyceride, systolic blood pressure, diastolic blood pressure, statin use, antihypertensive medication, and smoking and the existence of diabetic microangiopathic complications (neuropathy, nephropathy, retinopathy). The levels of serum tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) were determined using commercially available enzyme-linked immunosorbent assays (Quantikine HS TNFα and Quantikine HS IL-6, R & D Systems, Minneapolis, MN). High-sensitivity C-reactive protein was measured using latex-enhanced assay.6 Comparisons between two groups were made using the Student t test and chi-square analysis. Logistic regression analysis was performed to determine whether the significant variables identified using the Student t test and the chi-square analysis were significant factors that would predict that the scores of the cognitive tests were in the lowest quartiles. Total cholesterol and TNF-α showed a significant difference between the lowest quartile and those in the other three quartiles on the WAIS-R Digit Symbol Test score, as did the distribution of the existence of diabetic neuropathy and the values of diastolic blood pressure for the verbal memory (delayed recall) test. Logistic regression analysis revealed that TNF-α (odds ratio (OR)=44.49, 95% confidence interval (CI)=1.38–1426.30) and the existence of neuropathy (OR=0.09, 95% CI=0.01–0.84) were significant predictors for decline on their respective tests (Table 1). The substitution of nephropathy for neuropathy or of systolic blood pressure for diastolic blood pressure did not change the results in the analysis of verbal memory (delayed recall). The highest quartile of serum TNF-α levels had significantly lower scores on the WAIS-R Digit Symbol Test and MMSE (31.9±9.1 vs 38.9±9.0 and 26.5±1.1 vs 27.9±1.4, respectively). It was not possible to devise significant models for other cognitive tests. Several studies on subjects without DM have demonstrated that inflammatory markers are associated with cognitive impairment.3, 4 Because overexpression of IL-6 led to progressive neuronal loss and decreased learning7 in an animal model, it is possible that inflammation itself could affect cognitive ability. Another potential mechanism could be through atherosclerosis. It has been suggested that inflammatory markers, including TNF-α, are involved in the process of atherogenesis.8 Serum inflammatory markers, including TNF-α, were found to be high in patients with brain infarction, and one study has demonstrated a relationship between inflammatory proteins and silent brain infarctions.9 In the present study, all potential subjects with a clinical history of strokes or focal neurological signs were excluded, although subjects with high serum TNF-α might have silent brain infarctions, which could affect cognitive functions. The factor associated with lower verbal memory scores measured using the Alzheimer's Disease Assessment Scale Word List Recall in the current study was the presence of neuropathy or nephropathy. Several mechanisms are involved in the pathogenesis of diabetic neuropathy, including vascular dysfunction, polyol pathway, and advanced glycation end-product accumulations.10 A common mechanism may be involved in DM-related central nervous system dysfunction and peripheral neuropathy. The current analysis demonstrates that the specific factors associated with decline were different in two different tests, suggesting that multiple factors may cause diabetes-related cognitive decline. Financial Disclosure: This work was supported by a Grant-in-Aid for Longevity Scientific Research H17-Cyouju-013 from the Ministry of Health, Labour and Welfare, Japan. Author Contributions: All authors had active roles in study concept and design, acquisition of data, analysis and interpretation of data, and preparation of manuscript. Sponsor's Role: None.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,015
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,005
Score d'incertitude au seuil0,011

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,015
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0020,001
Études des sciences et des technologies0,0010,001
Communication savante0,0020,002
Science ouverte0,0020,001
Intégrité de la recherche0,0050,005
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

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.

Tête enseignante Opus0,018
Tête enseignante GPT0,223
Écart entre enseignants0,205 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations19
Publié2006
Routes d'admission1
Résumé présentoui

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