Cognitive Impairment Among Stroke Survivors at the University of Calabar Teaching Hospitalcalabar Cross River State, Nigeria
Notice bibliographique
Résumé
Background: Post-stroke cognitive impairment is very prevalent among stroke survivors but is often missed or underdiagnosed. Previous studies in Nigeria have focused more on post-stroke depression, leading to a shortage of information on cognitive impairment after stroke. Aim: To investigate the occurrence of post-stroke cognitive impairment among stroke survivors at the University of Calabar Teaching Hospital (UCTH), Calabar, Nigeria. Materials and Methods: This cross-sectional study was conducted among stroke survivors at the University of Calabar Teaching Hospital. All the stroke survivors had a CT-scan confirmed stroke. A consecutive sampling method was used to recruit respondents. The following questionnaires were administered to 122 stroke survivors. Sociodemographic/clinical questionnaire, National Institute of Health Stroke Scale (NIHSS), The Mini-International Neuropsychiatry Interview (MINI)-Depression module, Mini-Mental State Examination (MMSE), Oslo Social Support Scale (OSSS-3), and the Modified Rankin Scale (MRS). The data were analysed using SPSS version 25. Results: The study recruited 122 stroke survivors. The mean age of the participants was 60.23 ± 13.0. The proportion of male respondents was 62.3%, while that of female respondents was 37.7%. Respondents with the right hemispheric stroke were 51.6%, while those with the left hemispheric stroke were 36.1%. The proportion of respondents with ischaemic stroke (87.1%) was higher than that of those with hemorrhagic stroke (12.3%). The prevalence of post-stroke cognitive impairment among the respondents was 41.8%. Respondents with left hemispheric stroke were more likely to have cognitive impairment than those with right cerebral stroke. Also, respondents with severe stroke-related disability were more likely to have cognitive impairment than those with mild stroke-related disability. However, respondents with a tertiary and secondary level of education were less likely to have cognitive impairment than those with a primary level of education. Conclusion: The result of the study showed that post-stroke cognitive impairment is high among the study population. The condition is often neglected by the primary physicians managing these patients, leading to poor treatment outcomes. Efforts should be made to include cognitive assessment/ treatment in the routine care of stroke patients.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 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 ».