The Additional Contribution of White Matter Hyperintensity Location to Post-stroke Cognitive Impairment: Insights From a Multiple-Lesion Symptom Mapping Study
Notice bibliographique
Résumé
White matter hyperintensities (WMH) are common in acute ischemic stroke patients. Although WMH volume has been reported to influence post-stroke cognition, it is still not clear whether WMH location, independent of acute ischemic lesion (AIL) volume and location, contributes to cognitive impairment after stroke. Here, we proposed a multiple-lesion symptom mapping model that considers both the presence of WMH and AIL to measure the additional contribution of WMH locations to post-stroke cognitive impairment. Seventy-six first-ever stroke patients with AILs in the left hemisphere were examined by Montreal Cognitive Assessment (MoCA) at baseline and 1 year after stroke. The association between the location of AIL and WMH and global cognition was investigated by a multiple-lesion symptom mapping (MLSM) model based on support vector regression (SVR). To explore the relative merits of MLSM over the existing lesion-symptom mapping approaches with only AIL considered (mass-univariate VLSM and SVR-LSM), we measured the contribution of the significant AIL and/or WMH clusters from these models to post-stroke cognitive impairment. In addition, we compared the significant WMH locations identified by the optimal SVR-MLSM model for cognitive impairment at baseline and 1 year post stroke. The identified strategic locations of WMH significantly contributed to the prediction of MoCA at baseline (short-term) and 1 year (long-term) after stroke independent of the strategic locations of AIL. The significant clusters of WMH for short-term and long-term post-stroke cognitive impairment were mainly in the corpus callosum, corona radiata, and posterior thalamic radiation. We noted that in some regions, the AIL clusters that were significant for short-term outcome were no longer significant for long-term outcome, and interestingly more WMH clusters in these regions became significant for long-term outcome compared to short-term outcome. This indicated that there are some regions where local WMH burden has larger impact than AIL burden on the long-term post-stroke cognitive impairment. In consequence, SVR-MLSM was effective in identifying the WMH locations that have additional impact on post-stroke cognition on top of AIL locations. Such a method can also be applied to other lesion-behavior studies where multiple types of lesions may have potential contributions to a specific behavior.
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 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 | 0,001 |
| 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) | 0,000 | 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 ».