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Optimized Management of Endovascular Treatment for Acute Ischemic Stroke
Published on: January 18, 2018
Preexisting Cerebral Abnormalities and Functional Outcomes After Acute Ischemic Stroke
Jian-Feng Qu1, Yang-Kun Chen1, Huo-Hua Zhong1,2
11 Department of Neurology, Dongguan People's Hospital (Affiliated Dongguan Hospital, South Medical University), Dongguan, Guangdong Province, China.
Preexisting silent brain infarcts (SBI) and severe medial temporal lobe atrophy (MTLA) predict poor functional outcomes in acute ischemic stroke patients. These cerebral abnormalities are crucial for assessing stroke recovery and prognosis.
Area of Science:
- Neurology
- Neuroimaging
- Stroke Medicine
Background:
- Acute ischemic stroke significantly impacts patient function.
- Preexisting cerebral abnormalities may influence stroke recovery.
- Identifying predictors of functional outcomes is vital for patient management.
Purpose of the Study:
- To investigate the association between preexisting cerebral abnormalities and functional outcomes in acute ischemic stroke patients.
- To determine if specific MRI-detected abnormalities predict long-term functional status.
Main Methods:
- 272 patients with first-ever acute ischemic stroke were recruited.
- Cerebral abnormalities (infarcts, SBI, WMLs, atrophy) were assessed via MRI.
- Functional outcomes (IADL, BADL) were evaluated at 3 and 6 months post-stroke.
Main Results:
- Poor functional outcomes were associated with older age, male sex, higher NIHSS scores, and specific stroke subtypes.
- Cortical/subcortical/infratentorial infarcts, larger infarct volume, SBI, severe WMLs, and MTLA were linked to poorer outcomes.
- NIHSS, subcortical infarcts, and MTLA predicted poor IADL at 3 months; NIHSS, SBI, and MTLA predicted poor IADL at 6 months.
Conclusions:
- Silent brain infarcts (SBI) and severe medial temporal lobe atrophy (MTLA) are significant predictors of poorer functional outcomes after acute ischemic stroke.
- These findings underscore the importance of preexisting cerebral abnormalities in predicting stroke recovery.
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