Authors

  1. Fowler, Susan B.
  2. Mancini, Barbara

Article Content

Decreased blood flow to the brain deprives the brain of oxygen, triggering the ischemic cascade that includes calcium influx, overstimulation of excitatory amino acids, and overproduction of free radicals. Ischemia results in biochemical changes that manifest by markers in the bloodstream (Castillo & Rodriguez, 2004). Cerebral ischemia also initiates an inflammatory response in the brain and triggers the release of biochemical markers into the blood.

 

Biochemical markers (Table 1) linked to the ischemic cascade have the potential to predict outcomes before, during, and after stroke. Such markers are associated with signs of early neurological deterioration, final infarct volume, and many other outcomes (Castillo & Rodriguez, 2004; Christensen & Boysen, 2004; Herrmann, Vos, Wunderlich, de Bruijn, & Lamers, 2000; Smith et al., 2004). This article reviews the inflammatory response to ischemia as well as select biochemical markers (Table 2) released as part of this response.

  
Table 1 - Click to enlarge in new window Predictive Value of Select Biochemical Markers
 
Table 2 - Click to enlarge in new window Biochemical Markers Involved in Cerebrae Ischemia

Inflammatory Response and Biochemical Markers

The acute inflammatory response is important in early and late clinical outcomes, early clinical worsening, and brain damage following stroke (Chamorro, 2004). Inflammation occurs as a result of ischemia (Koenig, 2005). In addition, inflammation plays a role in and is characterized by leukocyte migration into the brain, which in turn causes cytokine production and release (Hopkins, 2003). Cytokines are glycoproteins that interact with each other and with many other cell types to maintain homeostasis (Castillo & Rodriguez, 2004). Additionally, by releasing cytokines, platelets also play a role in inflammation.

 

The localized response of cytokines makes systemic measurement of most markers difficult. One biochemical marker, IL-6, has a systemic action that makes its measurement easier and its concentration more meaningful. However, it is nonspecific, and its levels may only be elevated in correlation with extensive ischemia.

 

C-Reactive Protein

C-reactive protein (CRP) activates the complement system, which plays a pivotal role in inflammation. CRP levels have been shown to correlate with an increased incidence of stroke (Di Napoli, Papa, & Bocola, 2001) and to be an independent risk factor for mortality at 1 year following stroke (Christensen & Boysen, 2004). Increased CRP levels are also noted in patients with atrial fibrillation, a stroke risk factor, supporting an inflammatory state that favors thromboembolism (Conway, Buggins, Hughes, & Lip, 2004). Interestingly, statins have been shown to decrease elevated CRP levels (Koenig, 2005). Unfortunately, CRP is somewhat nonspecific, and its presence may be associated with infection, smoking, or atherosclerosis (Christensen & Boysen). Furthermore, CRP levels are elevated in acute myocardial infarction, dilated cardiomyopathy, and coronary artery syndrome.

 

Tissue Necrosis Factor

Tissue necrosis factor (TNF) is a cytokine with diverse antiinflammatory actions; TNF levels are elevated within 6 hours of stroke onset. Hypoperfusion seen in perfusion-weighted magnetic resonance imaging has been associated with increased TNF levels. Final infarct volume between the fourth and seventh day after stroke onset can be predicted by measuring early levels of TNF. In addition, TNF levels have been shown to predict the efficacy of thrombolytic therapy with a focus on hemorrhagic complications (Castillo & Rodriguez, 2004).

 

Interleukin-6

Interleukin-6 (IL-6) levels are elevated in the acute phase of stroke, usually within 6 hours of stroke onset. Additionally, increased IL-6 levels have been detected in patients with atrial fibrillation (Conway et al., 2004; Roldan et al., 2005).

 

IL-6 levels correlate with infarct volume on computed tomography (CT) scans as well as on the modified Rankin scale at 3 months following stroke (Smith et al., 2004). In addition, Castillo & Rodriguez (2004) suggested that IL-6 levels can help predict the efficacy of thrombolytic therapy.

 

S100B

Levels of S100B, a glial-derived protein, are elevated within 6 hours after stroke onset and then increase steadily, though the release of the protein may be slow (Wunderlich, Wallesch, & Goertler, 2004). Researchers have found that S100B is associated with neurological deficits and functional outcome following acute ischemic stroke. This relationship reflects increased S100B levels beginning 6 hours after stroke onset that increase to amounts > 0.2 mcg/L after 48 hours (Wunderlich et al.).

 

S100B also correlates with infarct size (Herrmann et al., 2000). Correlation between S100B levels and the amount of infarcted brain tissue has been documented in patients experiencing stroke following cardiac surgery (Jonsson et al., 2001). In addition, Foerch et al. (2004) found that S100B is sensitive and predictive for forecasting a malignant course in acute stroke heralded by cerebral herniation.

 

MMP

Matrix metalloproteinase-9 (MMP) is a proteolytic enzyme activated by IL-6 and TNF-alpha, and it has been studied for its predictive value in thrombolytic treatment and hemorrhagic complications (Castillo & Rodriguez, 2004). In association with diffusionweighted imaging, MMP has shown abilities to predict infarct volume (p < .05; Montaner et al., 2003). In a study where an MMP-inhibiting drug was given to rabbits that had received thrombolytic therapy, the incidence of hemorrhage was found to be less (p < .05; Lapchak, Chapman, & Zivin, 2000).

 

Challenges

No single marker has yet been shown to possess the predictive capacity required for it to serve as a clinically useful diagnostic test to distinguish ischemic stroke from controls (Floyd & Laskowitz, 2004). Therefore, models that measure multiple biochemical markers are warranted. A model proposed by Floyd and Laskowitz (2004) includes three markers: MMP, vascular cell adhesion molecule (VCAM), and von Willebrand factor (vWF), with a sensitivity and specificity greater than 90%, a positive predictive value of 63%, and a negative predictive value of 99%. Another model by Lynch et al. (2004) added S100B to the previously mentioned markers, with a resultant 90% predictive value for clinical diagnosis of ischemic stroke (i.e., neurological symptoms lasting longer than 24 hours).

 

Although prediction includes a variety of outcome measures, in these models, ischemia is distinguished from controls by measuring biochemical markers involved in the ischemic cascade. Compared to neuroimaging techniques, blood tests may be less costly and, in some clinical settings, easier to obtain.

 

Further study is needed to determine the significance of markers in the first few hours immediately following symptomatic onset of stroke. Additional models are needed to differentiate by type of stroke (e.g., lacunar and cardioembolic).

 

Additional markers also need to be investigated. Most recently, investigators have studied lipoprotein-associated phospholipase A2 with CRP as risk factors for identifying middle-aged individuals at increased risk for ischemic stroke (Ballantyne et al., 2005).

 

Nursing Implications

As researchers continue to study biochemical markers involved in stroke, neuroscience nurses may be engaged in obtaining blood samples as well as collecting data on outcome variables. Neuroscience nurses educate and inform patients and families about many issues related to stroke that go beyond the disease process and recovery. In the future, that information may include improved understanding of and treatments for stroke based on research related to the usefulness of biochemical markers in predicting outcomes.

 

Summary

Biochemical markers of cerebral ischemia and subsequent inflammation represent a potential diagnostic and predictive modality in acute ischemic stroke. Measurement of these markers may improve clinical functions ranging from diagnosis of ischemic stroke to prediction of functional outcome at 3 months. Predictive models, using various biochemical markers, continue to be investigated.

 

References

 

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