A cross sectional study on the relationship between age, white matter lesion, brain atrophy and cognitive function
Notice bibliographique
Résumé
Scope: the present study was designed to examine the relationship between structural brain changes, involving macrostructural and microstructural white matter changes, brain atrophy and cognitive function. Purpose: Cognitive deterioration is generally thought to be due to structural brain changes as part of the aging process. The present study sought to determine how age- related structural brain changes at the macrostructural and microstructural levels correlate with cognitive function among a cohort of reasonably healthy elderly. The study also explored the possible link between white matter damage and cognitive dysfunction, and examined whether this relationship was also influenced by age- associated loss of brain volume i.e. brain atrophy. Last but not least, the study examined the level of the usefulness of a global cognitive measure in comparison to specific neuropsychological subtests assessing executive function, working memory and episodic memory domains. Methodology: the volumetric measures were utilised to account for brain macrostructural changes, while the Diffusion Tensor Imaging (DTI)- based measures were used to examine microstructural properties of white matter disruptions among seventy reasonably healthy elderly recruited from Hunter Medical Research Institute (HMRI) Volunteer Register and specialised neurovascular clinic. The Montreal Cognitive Assessment (MoCA) was used to assess global cognition and twelve neuropsychological subtests were administered to measure specific deficit associated with subtle cognitive dysfunction in white matter pathology. The Pearson correlation coefficient and hierarchical multiple regression were utilised for data analyses. Results: the MoCA has captured variation associated with brain volumes and DTI- based changes, not fully accounted by specific cognitive tests administered in this study. Even after adjusting for age, FSIQ, and brain atrophy separately, the independent association between the MoCA and radial diffusivity remained stable. Interestingly, the MoCA is a brief, yet powerful tool that even accounts for global cognitive deficit for which white matter pathology and brain atrophy are not sensitive markers. White matter macrostructural and microstructural changes are associated with age- related cognitive dysfunction, characterised as subtle, varied and diffuse in nature. Brain atrophy not only linked to age, but also influenced the association between global cognition and white matter pathology on the volumetric measure; and partially explained the relationship between white matter microstructural disruption and specific deficit in visual working memory and visual episodic memory. In addition, the hierarchical regression analysis revealed that the MoCA was the strongest predictor of radial diffusivity (ℛ² = .476, 𝜌<.01) even after controlling for age (ℛ² = .392, 𝜌<.01), and cerebral atrophy was not a significant predictor of radial diffusivity. Conclusions and Implications: age- related white matter macrostructural and microstructural changes are not benign, even among reasonably healthy elderly by which their future functioning may be compromised. The so-called ‘healthy’ elderly appear to be a more vulnerable population, as the nature of the dysfunction can be very subtle and diffuse. Early detection thus, serves as a main preventative measure for this population. Since our findings strongly point to the MoCA as a beneficial screening tool for cognitive dysfunction at the early stage of white matter disease, we therefore recommend this brief, easily accessible tool for frontline clinicians to incorporate into their investigation protocol.
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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 | 0,001 | 0,002 |
| 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 | 0,001 |
| 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 ».