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Early prognostication of ischemic stroke using computed tomography perfusion and S100 beta level
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Background
Early outcome prediction in ischemic stroke is a crucial concern for clinicians for proper decisions to reduce morbidity and mortality. The present study aimed to compare between computed tomography (CT) perfusion, National Institutes of Health Stroke Scale (NIHSS), and S100β for early outcome prediction.
Patients and methods
The study was carried out on 50 adult patients with acute ischemic stroke, classified into two groups according to modified Rankin score into group I (favorable outcome) and group II (unfavorable outcome). CT-perfusion was done on admission, NIHSS was calculated on admission, and blood was withdrawn on admission and third day for S100β.
Results
Infarction core size and the penumbra size were larger significantly in unfavorable-outcome group (
P
<0.001). Also, S100β levels and NIHSS on admission were higher in group 2 than group 1 significantly (
P
<0.001,
P
=0.001, respectively).
Area under the curves were 0.787 for NIHSS score, 0.877 for S100β level, and 0.844 for penumbra size. A combination between penumbra size, S100β, and NIHSS to predict outcome. The receiver operating characteristic curve yielded an area under the curve of 0.905 (
P
<0.001). Furthermore, the comparison between a combination of penumbra size, S100β, NIHSS on admission, and the final infarct in noncontrast CT on day 3 had a significant positive correlation coefficient (
r
=0.577,
P
<0.001).
Conclusion
We suggest that higher NIHSS score on admission, large core and penumbra size, and high S100β level are independent early predictors of the functional outcome for acute ischemic-stroke patients. Moreover, detecting cases with NIHSS score more than 19, S100β more than 241 pg/ml, core size more than 10.35 cm
3
, and penumbra size more than 17.9 cm
3
, can individually predict unfavorable functional outcome in acute ischemic-stroke patients. Hence, using these cutoffs in combination might predict the outcome in a more precise manner.
Egyptian Knowledge Bank
Title: Early prognostication of ischemic stroke using computed tomography perfusion and S100 beta level
Description:
Background
Early outcome prediction in ischemic stroke is a crucial concern for clinicians for proper decisions to reduce morbidity and mortality.
The present study aimed to compare between computed tomography (CT) perfusion, National Institutes of Health Stroke Scale (NIHSS), and S100β for early outcome prediction.
Patients and methods
The study was carried out on 50 adult patients with acute ischemic stroke, classified into two groups according to modified Rankin score into group I (favorable outcome) and group II (unfavorable outcome).
CT-perfusion was done on admission, NIHSS was calculated on admission, and blood was withdrawn on admission and third day for S100β.
Results
Infarction core size and the penumbra size were larger significantly in unfavorable-outcome group (
P
<0.
001).
Also, S100β levels and NIHSS on admission were higher in group 2 than group 1 significantly (
P
<0.
001,
P
=0.
001, respectively).
Area under the curves were 0.
787 for NIHSS score, 0.
877 for S100β level, and 0.
844 for penumbra size.
A combination between penumbra size, S100β, and NIHSS to predict outcome.
The receiver operating characteristic curve yielded an area under the curve of 0.
905 (
P
<0.
001).
Furthermore, the comparison between a combination of penumbra size, S100β, NIHSS on admission, and the final infarct in noncontrast CT on day 3 had a significant positive correlation coefficient (
r
=0.
577,
P
<0.
001).
Conclusion
We suggest that higher NIHSS score on admission, large core and penumbra size, and high S100β level are independent early predictors of the functional outcome for acute ischemic-stroke patients.
Moreover, detecting cases with NIHSS score more than 19, S100β more than 241 pg/ml, core size more than 10.
35 cm
3
, and penumbra size more than 17.
9 cm
3
, can individually predict unfavorable functional outcome in acute ischemic-stroke patients.
Hence, using these cutoffs in combination might predict the outcome in a more precise manner.
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