sICAM as a Predictor of Outcome in Acute Spontaneous Intracerebral Hemorrhage

Review Article

Austin Crit Care J. 2017; 4(1): 1020.

sICAM as a Predictor of Outcome in Acute Spontaneous Intracerebral Hemorrhage

Mohamed H1, Hussein A2, Risk A3, Fawzy M2, Sherif AA2 and Ibrahim I4*

1Department of Critical Care Medicine, International Medical Centre, Saudi Arabia

2Department of Critical Care Medicine, Cairo University, Egypt

3Department of Clinical Pathology, Department of Critical Care, Cairo University, Egypt

4Department of Pulmonary and critical care medicine, University of California San Diego, USA

*Corresponding author: Islam Ibrahim, Department of Pulmonary and Critical Care Medicine, University of California San Diego, USA

Received: February 27, 2017; Accepted: September 13, 2017; Published: September 22, 2017


Background: Serum concentrations of adhesion molecules may be connected to the pathogenesis of secondary brain injury after spontaneous Intracerebral Hemorrhage (ICH). This study posits the hypothesis that levels of adhesion molecules substantially increase after ICH and are decreased thereafter, and that they can predict treatment outcomes.

Methods: Our study was conducted as a prospective study on 25 patients with acute spontaneous ICH presenting to ED of AL Sahel teaching hospital over a period of 19 months (May 2014 to November 2015) confirmed by patient history and brain CT scan. The studied population was divided into two groups; group 1(25 patients) with acute ICH and group 2(25) young volunteers. Patients in both groups were investigated with serial serum levels of sICAM during their hospital stay; the results of the 2 groups were compared. The case group was divided according to the outcome into two subgroups; bad outcome and good outcome by using the Modified Rankin Disability Scale (mMRS).

Results: Fifteen patients had bad outcome and 10 had good outcome. Cutoff point for the studied population for sICAM level on admission at 455 ng/ml could predict poor outcome with sensitivity 73% and specificity 80%, at 680 ng/ ml could predict clinical seizures at sensitivity 100% and specificity 81% and at 505 ng/ml could predict non survivors with sensitivity 89% and specificity 88%.

Conclusion: Persistent increase in sICAM level implies a danger of poor therapeutic outcome for the treatment of spontaneous ICH during hospitalization. These findings are important because they offer a potential therapeutic target for patients with spontaneous ICH.

Keywords: ICAM; Modified rank in disability scale; GCS; Intraventricular hemorrhage


Adhesion molecules sICAM-1 and Soluble Vascular Cell Adhesion Molecule-1 (sVCAM-1) are pro-inflammatory parameters for the activation of the immune system [1]. Their physiologic role is the regulation of cell-to-cell contacts [2]. Recruitment of activated peripheral blood mononuclear cells across endothelial cells of the blood brain barrier seems to be an essential step in the initiation of brain inflammation [3]. This step of immune cell entry into the brain tissue is regulated by adhesion molecules and leads to a complex cascade of events [2,4]. Moreover, adhesion molecules play a pathophysiologic role in cerebrovascular diseases [5].

Aim of the work

The aim of our study is to evaluate the role of sICAM as a predictor of outcome after acute spontaneous intracerebral hemorrhage.

Patients and Methods

Our study was conducted as a prospective case/control study on 25 patients with acute spontaneous intracerebral hemorrhage as confirmed by patient history and brain Computed Tomography (CT) scan, who were investigated with serial Serum Levels of Adhesion Molecules (sICAM) during their hospital stay compared to levels in volunteers. We have excluded patients who are/have:

a) Near death.

b) Central nervous system infection acquired during hospitalization.

c) Major systemic disease like end-stage renal disease, liver cirrhosis, or CHF.

The studied population was divided into two groups

Group 1 (Case group): Consisted of twenty five patients with acute spontaneous intracerebral hemorrhage.

Group 2 (Control group): Consisted of twenty five healthy volunteers.

Outcome in the case group (Group 1) was assessed upon discharge by using the Modified Rankin Disability Scale (mMRS). Good outcome was defined as an mMRS score of 0 or 1, whereas poor outcome was an mMRS score of at k least 2 or death.


1. CT scan soon after arrival at the emergency room as well as serial follow-up brain CT every 3 days concurrently with the sampling for sICAM during hospitalization.

2. Emergency brain CT scan was performed if there is clinical deterioration.

Serum ICAM: Levels of serum ICAM on admission (ICAM0), day 4 (ICAM1) and day 7 (ICAM2) will be assessed. One blood sample from each patient will be taken within 24 hours after the onset of ICH, then additional blood samples will be obtained on days 4 and 7 after the onset of ICH regardless of clinical deterioration.

Statistical analysis

Data will be expressed as mean ± standard deviation. Categorical variables will be compared by using the chi-square test or Fisher exact test, when appropriate. Serum levels of adhesion molecules will be compared by unpaired Student t test. Repeated measures of analysis of variance will be used to compare adhesion molecules at three different time points (days 1, 4 and 7). All continuous variables will be correlated by Pearson correlation coefficient. Receiver Operating Characteristic (ROC) curves will be generated for soluble adhesion molecule levels to determine cut off point for prediction of bad outcome. P value will be considered to be significant if ≤ 0.05.

Correlation refers to a process for establishing whether or not relationships exist between two variables whereas correlation coefficient (r) means a single number that gives a good idea about how closely one variable is related to another variable [6].

Receiver Operating Characteristic (ROC) curves are a useful way to interpret sensitivity and specificity levels and to determine related cut scores. ROC curves are a generalization of the set of potential combinations of sensitivity and specificity possible for predictors [7] ROC curve analysis not only provide information about cut scores, but also provide a natural common scale for comparing different predictors that are measured in different units, whereas the odds ratio in logistic regression analysis must be interpreted according to a unit increase in the value of the predictor, which can make comparison between predictors difficult [7]. An overall indication of the diagnostic accuracy of a ROC curve is The Area Under the Curve (AUC). AUC values closer to 1 indicate the screening measure reliably distinguishes among students with satisfactory and unsatisfactory reading performance, whereas values at. 50 indicate the predictor is no better than chance [8].


Demographic data of the case group on admission

Age: The mean age of the case group was 60.04 years with standard deviation 12.08 (Table 1).