#3040 The association of cognitive dysfunction with markers of oxidative stress and vitamin K deficiency in Chronic Kidney Disease patients
Notice bibliographique
Résumé
Abstract Background and Aims During recent years, it became evident that cognitive impairment is highly prevalent in End-Stage Kidney Disease (ESKD), which was mainly attributed to advanced age and vascular calcification (VC). However, the actual prevalence and incidence of cognitive impairment in Chronic Kidney Disease (CKD) are probably underreported. In this study we aimed to investigate the prevalence of cognitive impairment and the possible associations of cognitive function with various traditional and novel VC risk factors in a large cohort of CKD patients. Method We recruited 482 CKD patients of all stages (35 stage I, 29 stage II, 79 stage III, 55 stage 4 and 289 end-stage kidney disease-126 Peritoneal Dialysis-PD and 163 Hemodialysis-HD) and measured plasma levels of the inactive vitamin-K dependent Matrix Gla Protein (dp-ucMGP) (CARIM Institute, Maastricht, Netherlands). In these patients we determined arterial stiffness parameters (pulse wave velocity-PWV) by the Mobil-O-Graph device (IEM, Stolberg, Germany), carotid intime media thickness (cIMT) as a marker of arterial calcification with a B-mode ultrasonography and the presence of plaque in the carotid arteries. We also measured serum malondialdehyde (MDA) a marker of lipid peroxidation in the Department of Biochemistry, Medical School of Nis, Serbia, by ELISA. In our population, we used the MoCA (Montreal Cognitive Assessment) test, a 30-point screening test to detect cognitive impairment in 8 different areas (memory, language, attention and concentration, conceptual thinking, orientation, calculations, executive functions and visuoconstructional skills). Results The mean age of all patients was 65.9 ± 15.4 years and 34% were female. Moca score was correlated with central systolic and diastolic blood pressure (r = 0.15, P = 0.02 and r = 0.28, P < 0.0001), cardiac rhythm (r = 0.12 P = 0.04) creatinine (r = 0.35, P = 0.03), age (r = −0.53, P < 0.0001), duration of hypertension, diabetes mellitus and CVD (r = −0.18, P = 0.001, r = −0.32, P < 0.0001 and r = −0.28 P < 0.0001 respectively), glycated hemoglobin (r = −0.35, P = 0.03), high density lipoprotein cholesterol (r = 0.12, P = 0.003), serum MDA (r = 0.12, P = 0.023) and plasma dp-ucMGP (r = −0.22, P < 0.0001), Spearman's rho test. Kruskal-Wallis analysis showed that Moca score was significantly increased in patients with previous history of CVD (P < 0.0001) and those having a plaque in the carotid artery (P < 0.0001). Moreover, MoCA score decreased progressively with CKD stages (P < 0.0001) Stage Ι 29.2 ± 1.2 Stage II 28.2 ± 2.6 Stage III 26.6 ± 4.3 Stage IV 26.5 ± 3.9 ESKD 26.5 ± 4.3 (HD 26.2 ± 5.3, PD 26.8 ± 3.1). Conclusion Cognitive dysfunction starts early in CKD, is progressively increased with deterioration of kidney function and might be associated with vascular calcification, vitamin K deficiency and increased oxidative stress that are common in this population.
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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 | 0,001 |
| 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) | 0,000 | 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 ».