Objective: We proposed the concept of the cerebral infarction coefficient, which is cerebral infarction volume/brain volume. This study aimed to evaluate the prognostic value of the cerebral infarction coefficient in patients with massive cerebral infarction (MCI).
Methods: According to the modified Rankin score, 71 patients with acute MCI were divided into good prognosis and poor prognosis groups. Clinical and imaging data of the two groups were collected and univariate analysis was carried out. If there were significant differences in the data between the two groups, binary logistic regression analysis was performed.
Results: The poor prognosis group had a significantly higher cerebral infarction volume, cerebral infarction coefficient, and D-dimer levels, older age, the highest body temperature, a higher rate of a history of atrial fibrillation, and a lower rate of a history of hypertension compared with the good prognosis group (all P < 0.05). Binary logistic regression analysis showed that the cerebral infarction coefficient was an independent risk factor for a poor prognosis of patients with MCI (P < 0.05, 95 % confidence interval, 2.091, 42.562), and the odds ratio was 8.506. The area under the receiver operating characteristic curve for the cerebral infarction coefficient was 0.753. When the cut-off value was 7.8 %, the sensitivity of predicting a poor prognosis of patients with MCI was 92.5 %.
Conclusion: The cerebral infarction coefficient may have predictive value in determining the prognosis of patients with MCI.
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http://dx.doi.org/10.1016/j.clineuro.2020.106009 | DOI Listing |
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