Basal Ganglia and Prefrontal Regions Influence Postural Control and Cognitive Impairment in Parkinson's Disease
Notice bibliographique
Résumé
Objective Postural instability is one of clinical manifestations caused by the deterioration of basal ganglia (BG) in Parkinson's disease (PD). It has frequently been found in moderate and advanced stages of the disease, simultaneously, impairments of cognition and executive function are also commonly present. Several studies reported interferences between postural control and cognitive tasks passing the prefrontal regions. We aimed to reveal the roles of BG and prefrontal regions in postural control and cognitive impairment in PD patients who exhibit freezing of gait (FOG). Methods We measured postural control in 60 patients with Parkinson's disease (PD) in on‐medication (39 PD patients with FOG and 21 PD patients without FOG). A Nintendo Wii balance board was utilized to measure postural stability in terms of center of pressure (CoP). A modified Hoehn and Yahr scale (H&Y) was used to classify clinical staging of PD. Subjects' disease severities were evaluated by using Unified Parkinson's Disease Rating Scale (UPDRS) (part III). Levodopa Equivalent Dose (LED), New Freezing of Gait questionnaire (NFOG‐Q), and Montreal Cognitive Assessment were also assessed. The participants were instructed to stand naturally on the balance platform and look at a marker, which was 3 meters from the board. The subjects were asked to perform counting days backward for a total of 170 seconds. A computer program collected the data automatically (Buated, W., et.al. Gerontology and Geriatric Medicine, 2016). Regression analysis were performed for posturographic and clinical variables to identify relationships of mild cognitive impairment, postural instability and FOG. An important parameter of CoP; path length (PL), which was found to be dominant factor of the balance analysis (Buated, W., et al. The 19 th International Congress of Parkinson's Disease and Movement Disorders, 2015) , was also calculated. Principal component analysis was used to analyze all clinical variables and determined the statistical significance of the variance. Results Associations between PL and clinical variables were observed in all patients; LED (R 2 = 0.150, p = 0.001 ), H&Y (R 2 = 0.060, p = 0.060 ), duration of disease (R 2 = 0.065, p < 0.049 ) and NFOG‐Q (R 2 = 0.108, p = 0.010 ). In PD patients with FOG, relationship was found in LED (R 2 = 0.125, p = 0.032 ). On the other hand, no relationship was noticed in PD patients without FOG. Conclusions Basal ganglia and prefrontal regions play important roles in postural control and cognitive function in PD patients. Freezing of gait (FOG), cognitive impairment and postural control are associated with the effects of medication. Among the clinical variables, the correlation between LED and PL was found to be most important. These influences of the interruption of the neural circuitry were expressed in the postural control of PD patients, especially those subjects with FOG symptoms. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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 | 0,000 | 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) | 0,001 | 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 ».