MO204CHRONIC KIDNEY DISEASE, SLEEPINESS, MILD COGNITIVE IMPAIRMENT AND FINE MOTOR CONTROL
Notice bibliographique
Résumé
Abstract Background and Aims Chronic kidney disease (CKD) is a systemic condition because it modifies all organs' function due to an imbalance in plasma volume, electrolytes, hormones, and proteins. Indeed, at the nervous system level, mild cognitive impairment (MCI), sleep disorders and depression often accompany CKD. MCI partially explains the low quality of life of CKD patients, comparable to that of metastatic cancer patients. Mild Cognitive Impairment (MCI) has a high prevalence in this cohort (27-62%). Nevertheless, scattered literature data suggest that CKD patients can also have poor motor control, evidenced by a higher risk of falls, postural instability, reduced gait speed. In this cohort, few data are available regarding the motor circuits called central pattern generators, which control physiological tremor. Specifically, uraemic encephalopathy accentuates physiological tremor, which is regulated by central and peripheral oscillators. Overall, subtle changes in motor control often accompany other forms of MCI. Therefore, this study aimed at evaluating the effects of chronic kidney disease on cognitive and motor functions using up-to-date technologies to record physiological tremor and innovative data analysis. Method This retrospective case-control study enrolled 313 patients (139 controls, 79 CKD patients stage III-IV, 35 kidney transplant (Tx), 60 dialysis (HD) patients). These groups were comparable for age and weight. Creatininemia, azotemia, LDL, HDL, hemoglobin, and proteinuria were used for correlative analyses. We evaluated the chronotype using the Morningness-Eveningness Questionnaire (MEQ) and the degree of sleepiness using the Epworth Sleepiness Scale (ESS). Cognitive impairment was assessed by the Montreal Cognitive Assessment test (MoCA). Cognitive domains of the MoCA score were projected onto brain regions using CerebroViz library in R and a new transformation matrix derived from fMRI literature data. UMAP algorithm was used to identify patients' subgroups. The physiological tremor was recorded on patients maintaining the dominant arm extended using the smartphone App Phyphox. The tremor frequency spectrum was extracted by Fourier analysis. Results The sleepiness score (ESS) was significantly increased in HD (ESS = 5±0.4) compared to the healthy controls (ESS= 4±0.41) whereas was not significantly modified in CKD patients (3.24± 0.32). The chronotype was also not significantly different among the various groups. The mean score of the MoCA test was significantly lower in CKD, Tx, and HD groups (CKD MoCA =24.5±0.3; Tx MoCA =25.4±0.6; HD MoCA =24.6±0.7) than controls (MoCA score=28±0.1). A different pattern of impairment in the cognitive domains of MoCA was evidenced in the various groups using the CerebroViz projection and UMAP tools. MoCA score was inversely correlated with proteinuria (Pearson coefficient=-0.47; p<0.05). The higher frequencies of the physiological tremor (11-13 Hz) were significantly more represented in Tx patients compared to controls (p<0.05). Conversely, the lower frequencies (1-4 Hz) were significantly less represented in the HD group compared to controls (p<0.05). The peak frequency was inversely correlated with age in all patients (Pearson coefficient= -0.45; p<0.05) and inversely associated with azotemia levels, particularly in HD patients (Pearson coefficient=0.43; p<0.05). Conclusion Our results suggest that CKD patients present altered cognitive and motor control patterns, linked in part to the proteinuria level, suggesting a pathogenetic role of endothelial dysfunction. The characteristic motor, sleepiness and cognitive patterns of HD patients might be due to the arteriovenous fistula or the other peculiarities of these patients. These results might help identify new early markers of brain dysfunction in these patients, with the possibility of delaying or reversing cognitive decay.
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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) | 0,002 | 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 ».