Clinical review: Neuromonitoring - an update
© BioMed Central Ltd 2013
Published: 15 January 2013
Critically ill patients are frequently at risk of neurological dysfunction as a result of primary neurological conditions or secondary insults. Determining which aspects of brain function are affected and how best to manage the neurological dysfunction can often be difficult and is complicated by the limited information that can be gained from clinical examination in such patients and the effects of therapies, notably sedation, on neurological function. Methods to measure and monitor brain function have evolved considerably in recent years and now play an important role in the evaluation and management of patients with brain injury. Importantly, no single technique is ideal for all patients and different variables will need to be monitored in different patients; in many patients, a combination of monitoring techniques will be needed. Although clinical studies support the physiologic feasibility and biologic plausibility of management based on information from various monitors, data supporting this concept from randomized trials are still required.
The overall aims of neuromonitoring are to: 1) identify worsening neurological function and secondary cerebral insults that may benefit from specific treatment(s); 2) improve pathophysiological understanding of cerebral disease in critical illness; 3) provide clear physiological data to guide and individualize therapy; 4) assist with prognostication. In this article, we will outline the neuromonitoring techniques currently in use in critically ill patients and suggest how they should be best applied to help us care for such patients. We will focus on clinically available techniques and not discuss new approaches that are still largely in the research stage of development.
Pathophysiology of acute brain injury
The human brain constitutes 2% of body weight, yet the energy-consuming processes that enable adequate brain function account for about 25% of total body energy expenditure and 20% of the oxygen consumption of the whole organism. Glucose is the main energy substrate of the brain and, given the low glycogen stores in the brain, brain glucose levels are highly dependent on blood glucose. Transport of glucose from the systemic circulation to the brain is a tightly regulated process mediated by specialized cell membrane glucose transporters (GLUT). Experimental and human studies show evidence of flow-metabolism uncoupling and increased glucose utilization after acute brain injury ('cerebral hyper-glycolysis'). Importantly, this can occur in the absence of low cerebral blood flow (CBF) and cerebral ischemia and may lead to a state of reduced availability of the main energy substrate (glucose) with a subsequent risk of cerebral energy dysfunction [1, 2]. However, hyperglycolysis also results in increased processing of glucose to pyruvate by astrocytes and conversion to lactate. Endogenous lactate, released in the extracellular space, can in turn be transferred, via specific monocarboxylate transporters, to neurons (a process known as the 'astrocyte-neuron lactate shuttle') . Brain lactate may thus be used as an alternative aerobic energy substrate to glucose . Indeed, studies in subarachnoid hemorrhage (SAH) patients suggest that a pattern of increased cerebral hyper-glycolytic lactate is associated with better outcome .
Cerebral blood flow, oxygen delivery and ischemia
Cerebral ischemia is a frequent cause of secondary brain injury . In normal conditions, reduced systemic pressure triggers an active vasodilatory response that keeps cerebral blood flow (CBF) constant over a wide range of mean arterial pressures (MAPs), thereby preventing brain hypoperfusion (cerebral pressure autoregulation) . In brain-injured patients, cerebrovascular reactivity may be impaired, and a decrease in MAP or cerebral perfusion pressure (CPP) may thus translate into reduced CBF and secondary ischemia .
Cerebral oxygen utilization is proportional to the product of CBF and the arterio-venous difference in oxygen content . Mechanisms other than perfusion-limited ischemia (microvascular collapse, endothelial swelling, perivascular edema) may increase the diffusion gradient for oxygen between venous blood and brain tissue (PvO2-PbtO2), reduce cellular oxygen delivery and attenuate the ability of the brain to increase oxygen extraction fraction in response to reduced CBF .
Neurological examination of the ICU patient
Clinical neurological examination is a fundamental component of neuromonitoring and should take into account the effects of sedative drugs, which may markedly influence neurological responses. The degree of awareness should first be assessed. Clinical assessment is based mainly on evaluating eye and motor responses to verbal orders and noxious stimuli. The depth of coma can be evaluated by the Glasgow Coma Scale (GCS)  or the Full Outline of UnResponsiveness (FOUR) score , which includes assessment of the pupillary light and corneal reflexes and of the breathing pattern. Delirium is a fluctuating state characterized by altered attention, spatio-temporal disorientation, disorganized thinking and alteration of awareness. Delirious patients can be hypoactive, hyperactive or both alternately. The Confusion Assessment Method for the ICU (CAM-ICU)  or the ICU Delirium Screening Checklist (ICU DSC)  can be used to assess the presence and degree of delirium.
Neurological examination should then assess for neck stiffness, motor responses, plantar and deep tendon reflexes and cranial nerve functions. The presence of focal neurological signs should prompt brain imaging, which should also be considered, along with an electro-encephalogram (EEG), if there is no obvious cause for delirium or coma.
Elevated intracranial pressure (ICP; >20 mmHg) is associated with increased mortality after acute traumatic brain injury (TBI) . The most recent Brain Trauma Foundation guidelines  recommend (level II evidence) that ICP should be monitored in all salvageable patients with severe TBI (GCS score of 3 to 8 after resuscitation) and an abnormal head CT scan.
ICP monitoring is also used in non-traumatic neurological disorders, such as SAH, and to a lesser extent in brain tumors, infarctions, intracerebral hemorrhage, and infections. After SAH, external ventricular drainage is recommended in patients with higher World Federation of Neurological Societies (WFNS) scale scores or acute hydrocephalus , to monitor ICP and to drain cerebrospinal fluid (CSF) for ICP control. In spontaneous intracerebral hemorrhage, ICP monitoring is seldom used, but recent guidelines  suggest that in patients with a GCS score of <8, those with clinical evidence of transtentorial herniation, or those with intraventricular hemorrhage or hydrocephalus, ICP monitoring and treatment may be considered (class IIb; level of evidence: C).
Although non-invasive evaluation of ICP is possible using the transcranial Doppler (TCD)-derived pulsatility index  or optic nerve sonography , the only methods for continuous on-line monitoring of ICP remain invasive. Intra-ventricular devices have long been considered the 'gold standard'; however, intra-parenchymal pressure monitoring provides equivalent pressure measurements . Intraventricular probes are particularly useful when CSF drainage is desirable.
Cerebral blood flow
Direct, continuous measurement of regional CBF is now feasible using a thermal diffusion probe (TDP; Hemedex® Cambridge, Massachusetts, USA) inserted into the brain parenchyma. The sensor at the tip provides a quantitative measure in the volume of tissue surrounding the sensor. The TDP technique showed good agreement with CBF measured by xenon-CT .
Correct and stable positioning of regional CBF probes with a skull bolt is crucial and a CT- scan should be performed to verify correct placement. Precise quantification of regional CBF using a TDP is dependent on the presence of a stable temperature and may be altered in conditions of hyperthermia or rapid fluctuation in a patient's temperature.
In patients with SAH, Muench and colleagues  used TDP monitoring to guide medical therapy for delayed cerebral ischemia, and demonstrated that increasing blood pressure with vasopressors was the only intervention that improved CBF and PbtO2; hypervolemia and hemodilution had only marginal effects at best. Hence, normovolemia and MAP/CPP augmentation are increasingly used instead of 'triple-H' therapy in these patients. TDP monitoring may also guide CPP management after TBI . TDP data are currently limited to small single-center studies and larger trials are needed to confirm the validity and use of this technique.
Direct measurement of blood flow in the brain arteries would be of value in all cases of brain damage. Using an ultrasound probe, flow velocity (rather than flow itself) can be measured in the main arteries of the base of the brain. TCD combines ultrasound and the Doppler principle to represent erythrocyte flow in the basal cerebral arteries. In some 10% of patients, transtemporal insonation is not feasible because of anatomical barriers. When cerebrovascular resistance increases - for example, in vasospasm of the middle cerebral artery - systolic TCD velocity increases, whereas diastolic velocity decreases, leading to a clear increase in the pulsatility index (the ratio of the difference between systolic and diastolic flow to diastolic flow). For this reason, TCD is often used to monitor the time course of vasospasm after SAH . However, correct interpretation of the pulsatility index is complex, because it depends not only on cerebrovascular resistance, but also on several systemic and cerebral variables .
TCD has also been used to assess cerebrovascular autoregulation in TBI and SAH patients . Flow velocity responses to spontaneous or induced (with vasopressors) changes in CPP may quantify the status of static pressure autoregulation; autoregulation estimated by TCD in the middle cerebral artery correlated with autoregulation studied by positron emission tomography in TBI patients .
The main advantage of TCD is that it is non-invasive and can be carried out at the bedside. However, the quality of the TCD signal is operator-dependent and correct interpretation requires training. TCD signals may also vary over time with temperature, arterial carbon dioxide tension (PaCO2 and, in some series, correlation with actual CBF measurements was disappointing .
Microcirculatory alterations play a key role in the pathogenesis of organ dysfunction. Brain endothelial cells help regulate vessel diameter and permeability , contributing to coupling of flow to metabolism . Unfortunately, it is still not possible to visualize the brain microcirculation in clinical practice without direct exposure of the cerebral cortex after craniectomy and data on microvascular abnormalities in humans are limited.
Direct evaluation of the brain microcirculation can be performed using sidestream dark field imaging and intravital microscopy . These methods allow continuous and in vivo observation of the microcirculation at high resolution as well as evaluation of vessel size, number, density and flow. Although intravital microscopy is still considered the gold standard, it is not suitable for human use. The sidestream dark field technique can be applied on exposed cortical areas during craniectomy but care must be taken to limit pressure artifacts and minimize the risk of infection . In patients with stroke from middle cerebral artery occlusion who underwent decompressive craniectomy, brain microcirculatory density and flow were significantly altered when compared to control patients . Similarly, altered microvascular reactivity has been demonstrated in patients with SAH .
Brain tissue oxygen monitoring
Several techniques can be used to measure brain oxygenation, the most common in the ICU being jugular venous bulb oximetry and direct PbtO2 measurement. Near infra-red spectroscopy has also been used for this purpose.
Jugular venous bulb oximetry
This technique requires placement of a catheter into the jugular bulb. The arterio-jugular difference in oxygen content (AJDO2) is proportional to CBF and inversely proportional to oxygen consumption (cerebral metabolic rate for oxygen, CMRO2) and is often used as a global measure of adequate perfusion. Proper positioning of the probe in the jugular bulb is crucial, since blood draining from extra-cerebral structures, such as the neck and face, can contaminate the lower portions of the jugular vein.
Under most conditions in which arterial hemoglobin saturation is constant, just the jugular oxygen saturation (SjO2) is measured. This measurement can be performed by intermittent sampling, or continuously using fiberoptic probes. Normal values for SjO2 in patients without brain damage are about 57% (95% confidence interval 52 to 62%) . In the early hours after trauma, low SjO2 values have been detected, especially in the most severe cases . Severe and frequent SjO2 desaturations are associated with worse outcome in TBI patients .
Because of the anatomy of the cerebral circulation, SjO2 is an average indicator and a large volume of brain must be underperfused for an abnormality to be detected. Two-thirds of the blood flowing in each jugular vein comes from the ipsilateral and one-third from the contralateral hemisphere ; focal areas of mismatch between flow/metabolism can, therefore, be missed by this global measurement . Additionally, SjO2 values in one jugular vein may differ from values in the other . Despite these limitations, intermittent SjO2 sampling is a cheap and relatively easy tool for estimating adequacy of flow and metabolism, particularly when CBF is manipulated - for example, when using hyperventilation.
Direct PbtO2 measurement
Direct PbtO2 monitors are the most common technique used in the ICU to assess cerebral oxygenation. Probe positioning is crucial: usually inserted in the white matter, readings are dependent, in part, on proximity to intracranial pathology . For example, if close to a contusion, values may be reduced and this should be considered when making management decisions. When the PbtO2 probe is in what appears to be normal white matter on CT, then the reading, although local in nature, provides a reasonable estimate of global brain oxygenation.
PbtO2 is not a 'surrogate' for ischemia or CBF, because it varies not only with CBF (and factors that regulate it - for example, CO2 and MAP) but also with changes in arterial oxygen tension (PaO2) among many other factors. PbtO2 is, therefore, more a marker of the balance between regional oxygen supply and cellular oxygen consumption .
Monitoring PbtO2 has been validated against fiberoptic SjO2 monitoring, xenon-enhanced CT scanning, and SPECT. Threshold values vary slightly depending on what type of PbtO2 monitor is used but values <20 mmHg are considered worth treating and values <15 mmHg indicate brain hypoxia or ischemia [43, 44]. Decreases in PbtO2 have been associated with independent chemical markers of brain ischemia in microdialysis studies . The number, duration, and intensity of brain hypoxic episodes (PbtO2 <15 mmHg) and any PbtO2 values ≤5 mmHg are associated with poor outcome after TBI [46, 47]. Episodes of brain hypoxia are common and may occur even when ICP and CPP are normal . The exact relationship with outcome may, however, vary according to whether the probe is positioned in normal white matter, the penumbra or in a contusion [42, 49]. Monitoring of PbtO2 can be used in combination with other intra-parenchymal monitors, mainly ICP and cerebral microdialysis. Clinical studies suggest that therapy based on information from both an ICP and a PbtO2 monitor may be associated with better outcomes than that based on ICP monitoring alone .
Near infra-red spectroscopy
Oxyhemoglobin, deoxyhemoglobin, and oxidized cytochrome oxidase absorb specific portions of the light spectra. When a tissue layer is illuminated with a source of light in the near infra-red wavelength, the attenuation of the light signal is correlated to the relative proportions of oxyhemoglobin and deoxyhemoglobin (HbO2/Hb) and oxidized cytochrome oxidase in the tissue. Using appropriate calculations, an estimate of tissue oxygenation can, therefore, be made non-invasively and continuously.
Near infra-red spectroscopy has been used in TBI  and SAH , with ambiguous results. The technique has major limitations in adults: baseline normal values vary widely, extracranial contamination is a problem, and poor correlation with independent measurements of cerebral oxygenation has been reported frequently.
Cerebral microdialysis (CMD) involves the insertion of a catheter tipped with a semi- permeable membrane (usually with a 20 kDa cutoff) in the brain parenchyma. The CMD catheter is constantly perfused, thereby allowing regular sampling of the patient's brain extracellular fluid . CMD sampling is limited to the interstitial tissue area around the catheter, thus measuring regional brain metabolism. In clinical practice, a pattern of elevated lactate/pyruvate ratio and low glucose is considered as a warning sign for cerebral ischemia/hypoxia [54, 55]. High lactate/pyruvate ratios in normoxic conditions have been interpreted as markers of hyperglycolysis. Elevated glutamate is a marker of cellular dysfunction, for example, delayed cerebral ischemia in high-risk SAH patients . Absolute CMD values are important, but trends over time may provide more useful information. Recently, CMD has been used to identify the 'optimal' threshold for blood glucose during insulin therapy , and when used in combination with PbtO2, CMD monitoring has potential clinical utility to target adequate values of MAP/CPP [58, 59] and blood hemoglobin concentration .
Neurological biomarkers, quantitative indicators of brain dysfunction or damage, may be obtained via sampling of biological tissues (blood, CSF, brain interstitial fluid), electrophysiological recordings, or neuroimaging. For soluble biomarkers, modeling of extracerebral concentration kinetics is complex and must account for passage across anatomical barriers into the bloodstream or CSF; serum levels of a marker may therefore correlate less closely with brain levels than with alterations in blood-brain barrier integrity. An emerging body of work suggests that multi-marker panels may enhance sensitivity and specificity for acute neurological injury [61, 62]. There is also considerable interest in genomic, proteomic and lipidomic profiles.
Brain biomarkers are categorized according to their source as primarily neuronal, astroglial, or microglial. Here we briefly review the key biomarkers that have been tested clinically in acute neurological injury.
Increased levels of this astroglial protein are associated with injury severity and are predictive of long-term death or severe disability in severe TBI [63, 64], and following cardiac arrest  or aneurysmal SAH . Although highly sensitive, the specificity of this marker for acute brain injury is generally low .
Glial fibrillary acidic protein
Glial fibrillary acidic protein is associated with intermediate filaments in astrocytes. Increased serum levels are observed following moderate and severe TBI , ischemic stroke , SAH , and cardiac arrest . Serum glial fibrillary acidic protein levels more accurately discriminate TBI outcomes than do levels of s-100β .
Neuron-specific enolase is an enzyme that is found in neurons, cells of neuroendocrine origin, erythrocytes and platelets. Increased serum neuron-specific enolase has been observed in patients with ischemic stroke, TBI, SAH and after cardiac arrest [63, 65, 73]. Neuron-specific enolase can help discriminate between favorable and unfavorable outcomes following severe TBI and cardiac arrest [63, 65].
Tau is a neuronal protein that stabilizes microtubules, thereby promoting axonal transport. Significant elevations in tau have been observed in the CSF  and brain interstitial fluid  of patients with severe TBI. CSF tau protein is also elevated in patients with SAH, and is associated with neurological severity and outcome .
Amyloid β is a peptide cleaved from neuronal and glial amyloid precursor protein. CSF amyloid β fragment levels are lower in TBI and in SAH patients than in control subjects, and lower levels are predictive of short-term functional outcome . Recently, amyloid β has been measured in brain interstitium [75, 78].
Neurofilament heavy chain
Elevated levels of NfH (neurofilament heavy chain), a neuronal protein that is integral to the axonal cytoskeleton, have been reported in the brain interstitial fluid of patients with severe TBI and are associated with physiological abnormalities and mortality . CSF NfH is increased following SAH and hypertensive intracerebral hemorrhage [80, 81]. Serum concentrations of NfH do not reliably identify brain injury, perhaps because the large size of this molecule impedes passage through the blood-brain barrier.
Ubiquitin carboxy-terminal hydrolase L1
CSF levels of UCH-L1 (Ubiquitin carboxy-terminal hydrolase L1) are significantly elevated in severe TBI patients and are associated with lower levels of consciousness and worse six-month functional outcomes . Serum levels of UCH-L1 are associated with TBI severity and survival .
Alpha II-spectrin is a fundamental component of the neuronal cytoskeleton, which in the setting of injury is degraded into fragments referred to as spectrin breakdown products. CSF concentrations of these are elevated after TBI and correlate with the severity of injury and with six-month outcome . Spectrin breakdown products are also detectable in serum and have diagnostic and prognostic value in children with TBI .
Several groups have used qEEG to detect seizures and other causes of brain dysfunction, such as ischemia. In SAH patients, the percent alpha trend variability (PAV) decreased acutely with the onset of vasospasm-induced decreases in CBF and returned to normal with treatment and resolution of vasospasm . More recently, Rathakrishnan and colleagues  reported that changes in α power could help to distinguish delayed cerebral ischemia from vasospasm after SAH. Thus, there appears to be good evidence for the use of qEEG to detect cerebral ischemia.
qEEG may also be used to monitor the depth of sedation in the ICU. The most commonly used modality is the 'bispectral index' (BIS) , an algorithm-derived number that approximates the degree of sedation-induced EEG activity when patients are under general anesthesia. It ranges from 0 (brain dead) to 100 (normal brain function); a value of <60 indicates general anesthesia, and <30 indicates burst suppression.
Electrocorticography and spreading depression
Electrodes placed on the surface of the human cortex (electrocorticography), usually in proximity to damaged areas, can detect spontaneous waves of depolarization, which appear as spreading depression. Evidence is accumulating that these spreading depolarization waves cause an imbalance in energy consumption and delivery and may lead to secondary brain injury [95, 96]. Spreading depression has been identified in TBI  and in patients with SAH  in whom the number of spreading depressions correlated significantly with the development of delayed cerebral ischemia even in the absence of vasospasm. Electrocorticography requires a craniotomy, but recent studies have suggested there may be correlates with human scalp direct and alternating current electroencephalography .
Somatosensory evoked potentials (SSEPs) are measured on the scalp as evoked EEG responses to an electrical stimulus applied typically to the median or tibial nerves. SSEPs are less affected by pharmacological agents or hypothermia than is the EEG. The main variable used for prognosis is the cortical response, which usually occurs at 20 msec after the stimulus, and hence is called the N20 peak. After cardiac arrest, bilateral absence of the N20 SSEP is associated with persistent vegetative state or death in all patients [100, 101]. SSEPs can be measured during periods of sedation and even hypothermia, but most clinicians wait for return of normothermia. There is some concern about inter- and intra-observer variability in interpretation of SSEPs . The use of so-called 'cognitive' potentials, such as N70, has been suggested to improve the predictive value of poor prognosis of this test but this approach is not widely used .
CT is the imaging modality of choice in the initial evaluation of patients with TBI or when acute hemorrhage is suspected. It helps to rule out surgical masses, and to identify early signs of intracranial hypertension. Since hemorrhagic lesions or edema may evolve over the first hours after injury, a CT scan must be repeated whenever there is clinical deterioration even if the initial imaging was apparently normal. The severity of TBI lesions may be classified using the Marshall  or Rotterdam  scales. New features, such as angioCT and CT perfusion, add important information to non-contrast CT and are increasingly used in stroke and SAH evaluation.
Magnetic resonance imaging
Magnetic resonance imaging (MRI) has great spatial resolution and, in patients with TBI, can identify pathologic abnormalities that are undetected or poorly characterized with CT, such as traumatic axonal injury. Acute ischemic stroke can also be detected earlier using MRI than CT. MRI is multi-parametric and can provide anatomical detail and quantitative information on brain physiology and metabolism, also allowing neuronal activation to be mapped. MRI has the advantage over other radiological methods in that it does not require ionizing radiation. Challenges for MRI scanning of critically ill patients include: monitoring and resuscitation devices that are incompatible with the magnetic field, the need for sedation or even neuromuscular blockade to prevent movement artifacts, and the risks inherent to transport outside of the ICU environment.
Specific MRI sequences can enhance the diagnostic and prognostic evaluation of patients with acute brain injury.
Diffusion weighted imaging
Reductions in the apparent diffusion coefficient (ADC), a marker of water diffusion, are associated with acute tissue infarction in stroke and in cardiac arrest. Reduced ADC values have been noted in major gray matter and white matter structures after cardiac arrest and are predictive of six-month outcome .
Diffusion tensor imaging
Diffusion tensor imaging evaluates the directional preference (anisotropy) of water diffusion and allows quantitative assessments of white matter damage in patients with TBI. The magnitude of fractional anisotropy change correlates with clinical TBI severity in the acute setting and with long-term outcomes [107, 108].
Magnetic resonance spectroscopy
Magnetic resonance spectroscopy measures tissue levels of selected neurometabolites and can provide important insight into TBI pathophysiology and natural history. It has been demonstrated that N-acetyl aspartate, a marker of neuronal integrity, is decreased in TBI, often in brain tissue that appears normal on cranial CT or on conventional MRI. Brain N-acetyl aspartate levels are associated with worse clinical condition and are predictive of functional outcome following TBI .
Susceptibility weighted imaging
Susceptibility weighted imaging is highly sensitive to microscopic hemorrhagic lesions associated with TBI, which are believed to represent a subtype of diffuse axonal injury. In children with diffuse axonal injury, the number and volume of hemorrhagic lesions seen with susceptibility weighted imaging correlates with neurological severity on initial presentation and with long-term cognitive impairment and functional disability .
Functional MRI demonstrates that cortical-subcortical networks governing motor activity are significantly impaired following TBI .
Integration of variables
A single monitoring technique may not fully describe the complex pathophysiological changes in the brain and the concept of multimodality monitoring, the simultaneous digital recording of multiple parameters of brain function, has been introduced . Multicenter collaborations, such as BrainIT (Brain monitoring with Information Technology collaborative network) , have demonstrated that recording of many physiological variables across multiple patients is feasible and can provide new clinical insights . Advanced statistical and mathematical tools can be applied to the large volumes of data obtained with the aim of identifying patterns of brain injury and providing clinicians with easier identification of specific targets . Challenges in data integration and synchronization remain, but, ultimately, this concept should provide real-time, user-friendly advanced data analysis that, when applied at the bedside, could improve treatment.
Neurological monitoring has developed rapidly over the past 25 years with widespread application of various monitors, but, although clinical studies suggest the physiological feasibility of this concept, there are still no published data from randomized trials to support that targeting any variables improves clinical outcome.
Neurocritical care research over the past 20 years has focused on the possibility that early pharmacological intervention might improve outcome, which has deflected attention from trials designed to answer simple questions about the everyday management of acute brain injury patients, such as optimum hemoglobin transfusion thresholds, hyperventilation, and arterial pressure management after hemorrhagic stroke, for example. More extensive availability and use of neuromonitoring technology should facilitate the development of large clinical trials networks to provide the infrastructure necessary to design and conduct studies to resolve some of these issues.
Monitoring of brain function in critically ill patients must begin with a careful clinical evaluation. Monitoring systems typically look at single variables and there is a need to integrate/combine systems in order to obtain a full and accurate assessment of the patient's condition so as to be able to select the most appropriate therapy. Importantly, neuromonitoring is a dynamic process and not a single measurement; the ability to follow changes over time is vital to assess response to therapy and predict prognosis. No monitor will, by itself, improve patient outcomes but wise interpretation of the data and integration of the information obtained into an individualized therapeutic plan should help optimize care of critically ill patients with brain injury.
Monitoring of brain function should be considered in all comatose patients in the ICU.
Brain monitoring is centered on a careful clinical examination, although this can be limited in comatose and/or sedated patients.
The goals of neuromonitoring are to: identify worsening neurological function and secondary insults that may benefit from specific treatments; improve pathophysiological understanding of cerebral disease in critical illness; provide physiological data to guide and individualize therapy; assist in prognostication.
At present there is no 'ideal' single brain monitor; a combination of monitoring techniques may provide better insight into brain function than a single monitor used alone.
Trends over time and threshold values are both important when assessing brain function.
Clinical studies suggest the physiological feasibility and biological plausibility of management based on information from various monitors but data supporting this concept from randomized trials are still required.
cerebral blood flow
cerebral perfusion pressure
Glasgow Coma Scale
mean arterial pressure
magnetic resonance imaging
percent α trend variability
brain tissue PO2
jugular oxygen saturation
somatosensory evoked potential
traumatic brain injury
thermal diffusion probe.
- Glenn TC, Kelly DF, Boscardin WJ, McArthur DL, Vespa P, Oertel M, Hovda DA, Bergsneider M, Hillered L, Martin NA: Energy dysfunction as a predictor of outcome after moderate or severe head injury: indices of oxygen, glucose, and lactate metabolism. J Cereb Blood Flow Metab 2003, 23: 1239-1250.PubMedGoogle Scholar
- Vespa P, Bergsneider M, Hattori N, Wu HM, Huang SC, Martin NA, Glenn TC, McArthur DL, Hovda DA: Metabolic crisis without brain ischemia is common after traumatic brain injury: a combined microdialysis and positron emission tomography study. J Cereb Blood Flow Metab 2005, 25: 763-774. 10.1038/sj.jcbfm.9600073PubMed CentralPubMedGoogle Scholar
- Pellerin L, Bouzier-Sore AK, Aubert A, Serres S, Merle M, Costalat R, Magistretti PJ: Activity-dependent regulation of energy metabolism by astrocytes: an update. Glia 2007, 55: 1251-1262. 10.1002/glia.20528PubMedGoogle Scholar
- Bouzier-Sore AK, Voisin P, Canioni P, Magistretti PJ, Pellerin L: Lactate is a preferential oxidative energy substrate over glucose for neurons in culture. J Cereb Blood Flow Metab 2003, 23: 1298-1306.PubMedGoogle Scholar
- Oddo M, Levine JM, Frangos S, Maloney-Wilensky E, Carrera E, Daniel RT, Levivier M, Magistretti PJ, LeRoux PD: Brain lactate metabolism in humans with subarachnoid hemorrhage. Stroke 2012, 43: 1418-1421. 10.1161/STROKEAHA.111.648568PubMedGoogle Scholar
- Coles JP, Fryer TD, Smielewski P, Chatfield DA, Steiner LA, Johnston AJ, Downey SP, Williams GB, Aigbirhio F, Hutchinson PJ, Rice K, Carpenter TA, Clark JC, Pickard JD, Menon DK: Incidence and mechanisms of cerebral ischemia in early clinical head injury. J Cereb Blood Flow Metab 2004, 24: 202-211.PubMedGoogle Scholar
- Czosnyka M, Smielewski P, Piechnik S, Steiner LA, Pickard JD: Cerebral autoregulation following head injury. J Neurosurg 2001, 95: 756-763. 10.3171/jns.2001.95.5.0756PubMedGoogle Scholar
- Coles JP, Steiner LA, Johnston AJ, Fryer TD, Coleman MR, Smieleweski P, Chatfield DA, Aigbirhio F, Williams GB, Boniface S, Rice K, Clark JC, Pickard JD, Menon DK: Does induced hypertension reduce cerebral ischaemia within the traumatized human brain? Brain 2004, 127: 2479-2490. 10.1093/brain/awh268PubMedGoogle Scholar
- Rosenthal G, Hemphill JC, Sorani M, Martin C, Morabito D, Obrist WD, Manley GT: Brain tissue oxygen tension is more indicative of oxygen diffusion than oxygen delivery and metabolism in patients with traumatic brain injury. Crit Care Med 2008, 36: 1917-1924. 10.1097/CCM.0b013e3181743d77PubMedGoogle Scholar
- Menon DK, Coles JP, Gupta AK, Fryer TD, Smielewski P, Chatfield DA, Aigbirhio F, Skepper JN, Minhas PS, Hutchinson PJ, Carpenter TA, Clark JC, Pickard JD: Diffusion limited oxygen delivery following head injury. Crit Care Med 2004, 32: 1384-1390. 10.1097/01.CCM.0000127777.16609.08PubMedGoogle Scholar
- Teasdale G, Jennett B: Assessment of coma and impaired consciousness. A practical scale. Lancet 1974, 2: 81-84.PubMedGoogle Scholar
- Wijdicks EF, Bamlet WR, Maramattom BV, Manno EM, McClelland RL: Validation of a new coma scale: The FOUR score. Ann Neurol 2005, 58: 585-593. 10.1002/ana.20611PubMedGoogle Scholar
- Ely EW, Margolin R, Francis J, May L, Truman B, Dittus R, Speroff T, Gautam S, Bernard GR, Inouye SK: Evaluation of delirium in critically ill patients: validation of the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). Crit Care Med 2001, 29: 1370-1379. 10.1097/00003246-200107000-00012PubMedGoogle Scholar
- Bergeron N, Dubois MJ, Dumont M, Dial S, Skrobik Y: Intensive Care Delirium Screening Checklist: evaluation of a new screening tool. Intensive Care Med 2001, 27: 859-864. 10.1007/s001340100909PubMedGoogle Scholar
- Marmarou A, Anderson RL, Ward JD, Choi SC, Young HF, Eisenberg HM, Foulkes MA, Marshall LF, Jane JA: Impact of ICP instability and hypotension on outcome in patients with severe head trauma. J Neurosurg Special Suppl 1991, 75: S59-S66.Google Scholar
- Brain Trauma Foundation, American Association of Neurological Surgeons, Congress of Neurological Surgeons, Joint Section on Neurotrauma and Critical Care, AANS/CNS, Bratton SL, Chestnut RM, Ghajar J, McConnell Hammond FF, Harris OA, Hartl R, Manley GT, Nemecek A, Newell DW, Rosenthal G, Schouten J, Shutter L, Timmons SD, Ullman JS, Videtta W, Wilberger JE, Wright DW: Guidelines for the management of severe traumatic brain injury. VI. Indications for intracranial pressure monitoring. J Neurotrauma 2007, (24 Suppl 1:):S37-S44.
- Bederson JB, Connolly ES Jr, Batjer HH, Dacey RG, Dion JE, Diringer MN, Duldner JE Jr, Harbaugh RE, Patel AB, Rosenwasser RH: Guidelines for the management of aneurysmal subarachnoid hemorrhage: a statement for healthcare professionals from a special writing group of the Stroke Council, American Heart Association. Stroke 2009, 40: 994-1025. 10.1161/STROKEAHA.108.191395PubMedGoogle Scholar
- Morgenstern LB, Hemphill JC, Anderson C, Becker K, Broderick JP, Connolly ES Jr, Greenberg SM, Huang JN, MacDonald RL, Messe SR, Mitchell PH, Selim M, Tamargo RJ: Guidelines for the management of spontaneous intracerebral hemorrhage: a guideline for healthcare professionals from the American Heart Association/American Stroke Association. Stroke 2010, 41: 2108-2129. 10.1161/STR.0b013e3181ec611bPubMed CentralPubMedGoogle Scholar
- Pickard JD, Czosnyka M: Management of raised intracranial pressure. J Neurol Neurosurg Psychiatry 1993, 56: 845-858. 10.1136/jnnp.56.8.845PubMed CentralPubMedGoogle Scholar
- Bouzat P, Francony G, Fauvage B, Payen JF: Transcranial Doppler pulsatility index for initial management of brain-injured patients. Neurosurgery 2010, 67: E1863-E1864.PubMedGoogle Scholar
- Rajajee V, Vanaman M, Fletcher JJ, Jacobs TL: Optic nerve ultrasound for the detection of raised intracranial pressure. Neurocrit Care 2011, 15: 506-515. 10.1007/s12028-011-9606-8PubMedGoogle Scholar
- Brain Trauma Foundation, American Association of Neurological Surgeons, Congress of Neurological Surgeons, Joint Section on Neurotrauma and Critical Care, AANS/CNS, Bratton SL, Chestnut RM, Ghajar J, McConnell Hammond FF, Harris OA, Hartl R, Manley GT, Nemecek A, Newell DW, Rosenthal G, Schouten J, Shutter L, Timmons SD, Ullman JS, Videtta W, Wilberger JE, Wright DW: Guidelines for the management of severe traumatic brain injury. VII. Intracranial pressure monitoring technology. J Neurotrauma 2007, (24 Suppl 1:):S45-S54.
- Vajkoczy P, Roth H, Horn P, Lucke T, Thome C, Hubner U, Martin GT, Zappletal C, Klar E, Schilling L, Schmiedek P: Continuous monitoring of regional cerebral blood flow: experimental and clinical validation of a novel thermal diffusion microprobe. J Neurosurg 2000, 93: 265-274. 10.3171/jns.2000.93.2.0265PubMedGoogle Scholar
- Muench E, Horn P, Bauhuf C, Roth H, Philipps M, Hermann P, Quintel M, Schmiedek P, Vajkoczy P: Effects of hypervolemia and hypertension on regional cerebral blood flow, intracranial pressure, and brain tissue oxygenation after subarachnoid hemorrhage. Crit Care Med 2007, 35: 1844-1851. 10.1097/01.CCM.0000275392.08410.DDPubMedGoogle Scholar
- Rosenthal G, Sanchez-Mejia RO, Phan N, Hemphill JC, Martin C, Manley GT: Incorporating a parenchymal thermal diffusion cerebral blood flow probe in bedside assessment of cerebral autoregulation and vasoreactivity in patients with severe traumatic brain injury. J Neurosurg 2011, 114: 62-70. 10.3171/2010.6.JNS091360PubMedGoogle Scholar
- Washington CW, Zipfel GJ: Detection and monitoring of vasospasm and delayed cerebral ischemia: a review and assessment of the literature. Neurocrit Care 2011, 15: 312-317. 10.1007/s12028-011-9594-8PubMedGoogle Scholar
- de Riva N, Budohoski KP, Smielewski P, Kasprowicz M, Zweifel C, Steiner LA, Reinhard M, Fabregas N, Pickard JD, Czosnyka M: Transcranial Doppler Pulsatility Index: what it is and what it isn't. Neurocrit Care 2012, 17: 58-66. 10.1007/s12028-012-9672-6PubMedGoogle Scholar
- Steiner LA, Coles JP, Johnston AJ, Chatfield DA, Smielewski P, Fryer TD, Aigbirhio FI, Clark JC, Pickard JD, Menon DK, Czosnyka M: Assessment of cerebrovascular autoregulation in head-injured patients: a validation study. Stroke 2003, 34: 2404-2409. 10.1161/01.STR.0000089014.59668.04PubMedGoogle Scholar
- Chieregato A, Sabia G, Tanfani A, Compagnone C, Tagliaferri F, Targa L: Xenon-CT and transcranial Doppler in poor-grade or complicated aneurysmatic subarachnoid hemorrhage patients undergoing aggressive management of intracranial hypertension. Intensive Care Med 2006, 32: 1143-1150. 10.1007/s00134-006-0226-2PubMedGoogle Scholar
- Zonta M, Angulo MC, Gobbo S, Rosengarten B, Hossmann KA, Pozzan T, Carmignoto G: Neuron-to-astrocyte signaling is central to the dynamic control of brain microcirculation. Nat Neurosci 2003, 6: 43-50. 10.1038/nn980PubMedGoogle Scholar
- Panerai RB: Assessment of cerebral pressure autoregulation in humans-a review of measurement methods. Physiol Meas 1998, 19: 305-338. 10.1088/0967-3334/19/3/001PubMedGoogle Scholar
- De Backer D, Ospina-Tascon G, Salgado D, Favory R, Creteur J, Vincent JL: Monitoring the microcirculation in the critically ill patient: current methods and future approaches. Intensive Care Med 2010, 36: 1813-1825. 10.1007/s00134-010-2005-3PubMedGoogle Scholar
- De Backer D, Donadello K, Taccone FS, Ospina-Tascon G, Salgado D, Vincent JL: Microcirculatory alterations: potential mechanisms and implications for therapy. Ann Intensive Care 2011, 1: 27. 10.1186/2110-5820-1-27PubMed CentralPubMedGoogle Scholar
- Perez-Barcena J, Goedhart P, Ibanez J, Brell M, Garcia R, Llinas P, Jimenez C, Ince C: Direct observation of human microcirculation during decompressive craniectomy after stroke. Crit Care Med 2011, 39: 1126-1129. 10.1097/CCM.0b013e31820ead5ePubMedGoogle Scholar
- Pennings FA, Albrecht KW, Muizelaar JP, Schuurman PR, Bouma GJ: Abnormal responses of the human cerebral microcirculation to papaverin during aneurysm surgery. Stroke 2009, 40: 317-320. 10.1161/STROKEAHA.108.522375PubMedGoogle Scholar
- Chieregato A, Calzolari F, Trasforini G, Targa L, Latronico N: Normal jugular bulb oxygen saturation. J Neurol Neurosurg Psychiatry 2003, 74: 784-786. 10.1136/jnnp.74.6.784PubMed CentralPubMedGoogle Scholar
- Verweij BH, Muizelaar JP, Vinas FC: Hyperacute measurement of intracranial pressure, cerebral perfusion pressure, jugular venous oxygen saturation, and laser Doppler flowmetry, before and during removal of traumatic acute subdural hematoma. J Neurosurg 2001, 95: 569-572. 10.3171/jns.2001.95.4.0569PubMedGoogle Scholar
- Gopinath SP, Robertson CS, Contant CF, Hayes C, Feldman Z, Narayan RK, Grossman RG: Jugular venous desaturation and outcome after head injury. J Neurol Neurosurg Psychiatry 1994, 57: 717-723. 10.1136/jnnp.57.6.717PubMed CentralPubMedGoogle Scholar
- Shenkin HA, Harmel MH, Kety SS: Dynamic anatomy of the cerebral circulation. Arch Neurol Psychiatry 1948, 60: 240-252. 10.1001/archneurpsyc.1948.02310030021002PubMedGoogle Scholar
- Coles JP, Fryer TD, Coleman MR, Smielewski P, Gupta AK, Minhas PS, Aigbirhio F, Chatfield DA, Williams GB, Boniface S, Carpenter TA, Clark JC, Pickard JD, Menon DK: Hyperventilation following head injury: effect on ischemic burden and cerebral oxidative metabolism. Crit Care Med 2007, 35: 568-578. 10.1097/01.CCM.0000254066.37187.88PubMedGoogle Scholar
- Stocchetti N, Paparella A, Bridelli F, Bacchi M, Piazza P, Zuccoli P: Cerebral venous oxygen saturation studied with bilateral samples in the internal jugular veins. Neurosurgery 1994, 34: 38-43. 10.1227/00006123-199401000-00007PubMedGoogle Scholar
- Ponce LL, Pillai S, Cruz J, Li X, Julia H, Gopinath S, Robertson CS: Position of probe determines prognostic information of brain tissue PO2 in severe traumatic brain injury. Neurosurgery 2012, 70: 1492-1503. 10.1227/NEU.0b013e31824ce933PubMed CentralPubMedGoogle Scholar
- Scheufler KM, Lehnert A, Rohrborn HJ, Nadstawek J, Thees C: Individual value of brain tissue oxygen pressure, microvascular oxygen saturation, cytochrome redox level, and energy metabolites in detecting critically reduced cerebral energy state during acute changes in global cerebral perfusion. J Neurosurg Anesthesiol 2004, 16: 210-219. 10.1097/00008506-200407000-00005PubMedGoogle Scholar
- Chang JJ, Youn TS, Benson D, Mattick H, Andrade N, Harper CR, Moore CB, Madden CJ, Diaz-Arrastia RR: Physiologic and functional outcome correlates of brain tissue hypoxia in traumatic brain injury. Crit Care Med 2009, 37: 283-290. 10.1097/CCM.0b013e318192fbd7PubMedGoogle Scholar
- Hlatky R, Valadka AB, Goodman JC, Contant CF, Robertson CS: Patterns of energy substrates during ischemia measured in the brain by microdialysis. J Neurotrauma 2004, 21: 894-906. 10.1089/0897715041526195PubMedGoogle Scholar
- Dings J, Meixensberger J, Jager A, Roosen K: Clinical experience with 118 brain tissue oxygen partial pressure catheter probes. Neurosurgery 1998, 43: 1082-1095. 10.1097/00006123-199811000-00045PubMedGoogle Scholar
- van den Brink WA, van Santbrink H, Steyerberg EW, Avezaat CJ, Suazo JA, Hogesteeger C, Jansen WJ, Kloos LM, Vermeulen J, Maas AI: Brain oxygen tension in severe head injury. Neurosurgery 2000, 46: 868-876.PubMedGoogle Scholar
- Oddo M, Levine JM, Mackenzie L, Frangos S, Feihl F, Kasner SE, Katsnelson M, Pukenas B, MacMurtrie E, Maloney-Wilensky E, Kofke WA, LeRoux PD: Brain hypoxia is associated with short-term outcome after severe traumatic brain injury independently of intracranial hypertension and low cerebral perfusion pressure. Neurosurgery 2011, 69: 1037-1045.PubMedGoogle Scholar
- Longhi L, Valeriani V, Rossi S, De Marchi M, Egidi M, Stocchetti N: Effects of hyperoxia on brain tissue oxygen tension in cerebral focal lesions. Acta Neurochir Suppl 2002, 81: 315-317.PubMedGoogle Scholar
- Nangunoori R, Maloney-Wilensky E, Stiefel M, Park S, Andrew KW, Levine JM, Yang W, Le Roux PD: Brain tissue oxygen-based therapy and outcome after severe traumatic brain injury: A systematic literature review. Neurocrit Care 2012, 17: 131-138. 10.1007/s12028-011-9621-9PubMedGoogle Scholar
- Leal-Noval SR, Cayuela A, rellano-Orden V, Marin-Caballos A, Padilla V, Ferrandiz-Millon C, Corcia Y, Garcia-Alfaro C, maya-Villar R, Murillo-Cabezas F: Invasive and noninvasive assessment of cerebral oxygenation in patients with severe traumatic brain injury. Intensive Care Med 2010, 36: 1309-1317. 10.1007/s00134-010-1920-7PubMedGoogle Scholar
- Naidech AM, Bendok BR, Ault ML, Bleck TP: Monitoring with the Somanetics INVOS 5100C after aneurysmal subarachnoid hemorrhage. Neurocrit Care 2008, 9: 326-331. 10.1007/s12028-008-9077-8PubMedGoogle Scholar
- Hillered L, Vespa PM, Hovda DA: Translational neurochemical research in acute human brain injury: the current status and potential future for cerebral microdialysis. J Neurotrauma 2005, 22: 3-41. 10.1089/neu.2005.22.3PubMedGoogle Scholar
- Andrews PJ, Citerio G, Longhi L, Polderman K, Sahuquillo J, Vajkoczy P: NICEM consensus on neurological monitoring in acute neurological disease. Intensive Care Med 2008, 34: 1362-1370. 10.1007/s00134-008-1103-yPubMedGoogle Scholar
- Bellander BM, Cantais E, Enblad P, Hutchinson P, Nordstrom CH, Robertson C, Sahuquillo J, Smith M, Stocchetti N, Ungerstedt U, Unterberg A, Olsen NV: Consensus meeting on microdialysis in neurointensive care. Intensive Care Med 2004, 30: 2166-2169. 10.1007/s00134-004-2461-8PubMedGoogle Scholar
- Sarrafzadeh A, Haux D, Sakowitz O, Benndorf G, Herzog H, Kuechler I, Unterberg A: Acute focal neurological deficits in aneurysmal subarachnoid hemorrhage: relation of clinical course, CT findings, and metabolite abnormalities monitored with bedside microdialysis. Stroke 2003, 34: 1382-1388. 10.1161/01.STR.0000074036.97859.02PubMedGoogle Scholar
- Oddo M, Schmidt JM, Carrera E, Badjatia N, Connolly ES, Presciutti M, Ostapkovich ND, Levine JM, Le Roux P, Mayer SA: Impact of tight glycemic control on cerebral glucose metabolism after severe brain injury: a microdialysis study. Crit Care Med 2008, 36: 3233-3238. 10.1097/CCM.0b013e31818f4026PubMedGoogle Scholar
- Ko SB, Choi HA, Parikh G, Helbok R, Schmidt JM, Lee K, Badjatia N, Claassen J, Connolly ES, Mayer SA: Multimodality monitoring for cerebral perfusion pressure optimization in comatose patients with intracerebral hemorrhage. Stroke 2011, 42: 3087-3092. 10.1161/STROKEAHA.111.623165PubMed CentralPubMedGoogle Scholar
- Schmidt JM, Ko SB, Helbok R, Kurtz P, Stuart RM, Presciutti M, Fernandez L, Lee K, Badjatia N, Connolly ES, Claassen J, Mayer SA: Cerebral perfusion pressure thresholds for brain tissue hypoxia and metabolic crisis after poor-grade subarachnoid hemorrhage. Stroke 2011, 42: 1351-1356. 10.1161/STROKEAHA.110.596874PubMed CentralPubMedGoogle Scholar
- Oddo M, Milby A, Chen I, Frangos S, MacMurtrie E, Maloney-Wilensky E, Stiefel M, Kofke WA, Levine JM, Le Roux PD: Hemoglobin concentration and cerebral metabolism in patients with aneurysmal subarachnoid hemorrhage. Stroke 2009, 40: 1275-1281. 10.1161/STROKEAHA.108.527911PubMedGoogle Scholar
- Laskowitz DT, Kasner SE, Saver J, Remmel KS, Jauch EC: Clinical usefulness of a biomarker-based diagnostic test for acute stroke: the Biomarker Rapid Assessment in Ischemic Injury (BRAIN) study. Stroke 2009, 40: 77-85. 10.1161/STROKEAHA.108.516377PubMedGoogle Scholar
- Turck N, Vutskits L, Sanchez-Pena P, Robin X, Hainard A, Gex-Fabry M, Fouda C, Bassem H, Mueller M, Lisacek F, Puybasset L, Sanchez JC: A multiparameter panel method for outcome prediction following aneurysmal subarachnoid hemorrhage. Intensive Care Med 2010, 36: 107-115. 10.1007/s00134-009-1641-yPubMedGoogle Scholar
- Vos PE, Lamers KJ, Hendriks JC, van Haaren M, Beems T, Zimmerman C, van Geel W, de Reus H, Biert J, Verbeek MM: Glial and neuronal proteins in serum predict outcome after severe traumatic brain injury. Neurology 2004, 62: 1303-1310. 10.1212/01.WNL.0000120550.00643.DCPubMedGoogle Scholar
- Korfias S, Stranjalis G, Boviatsis E, Psachoulia C, Jullien G, Gregson B, Mendelow AD, Sakas DE: Serum S-100B protein monitoring in patients with severe traumatic brain injury. Intensive Care Med 2007, 33: 255-260. 10.1007/s00134-006-0463-4PubMedGoogle Scholar
- Zandbergen EG, Hijdra A, Koelman JH, Hart AA, Vos PE, Verbeek MM, de Haan RJ: Prediction of poor outcome within the first 3 days of postanoxic coma. Neurology 2006, 66: 62-68. 10.1212/01.wnl.0000191308.22233.88PubMedGoogle Scholar
- Sanchez-Pena P, Pereira AR, Sourour NA, Biondi A, Lejean L, Colonne C, Boch AL, Al Hawari M, Abdennour L, Puybasset L: S100B as an additional prognostic marker in subarachnoid aneurysmal hemorrhage. Crit Care Med 2008, 36: 2267-2273. 10.1097/CCM.0b013e3181809750PubMedGoogle Scholar
- Sen J, Belli A: S100B in neuropathologic states: the CRP of the brain? J Neurosci Res 2007, 85: 1373-1380. 10.1002/jnr.21211PubMedGoogle Scholar
- Vos PE, Jacobs B, Andriessen TM, Lamers KJ, Borm GF, Beems T, Edwards M, Rosmalen CF, Vissers JL: GFAP and S100B are biomarkers of traumatic brain injury: an observational cohort study. Neurology 2010, 75: 1786-1793. 10.1212/WNL.0b013e3181fd62d2PubMedGoogle Scholar
- Herrmann M, Vos P, Wunderlich MT, de Bruijn CH, Lamers KJ: Release of glial tissue-specific proteins after acute stroke: A comparative analysis of serum concentrations of protein S-100B and glial fibrillary acidic protein. Stroke 2000, 31: 2670-2677. 10.1161/01.STR.31.11.2670PubMedGoogle Scholar
- Vos PE, van Gils M, Beems T, Zimmerman C, Verbeek MM: Increased GFAP and S100beta but not NSE serum levels after subarachnoid haemorrhage are associated with clinical severity. Eur J Neurol 2006, 13: 632-638. 10.1111/j.1468-1331.2006.01332.xPubMedGoogle Scholar
- Kaneko T, Kasaoka S, Miyauchi T, Fujita M, Oda Y, Tsuruta R, Maekawa T: Serum glial fibrillary acidic protein as a predictive biomarker of neurological outcome after cardiac arrest. Resuscitation 2009, 80: 790-794. 10.1016/j.resuscitation.2009.04.003PubMedGoogle Scholar
- Pelinka LE, Kroepfl A, Leixnering M, Buchinger W, Raabe A, Redl H: GFAP versus S100B in serum after traumatic brain injury: relationship to brain damage and outcome. J Neurotrauma 2004, 21: 1553-1561. 10.1089/neu.2004.21.1553PubMedGoogle Scholar
- Cronberg T, Rundgren M, Westhall E, Englund E, Siemund R, Rosen I, Widner H, Friberg H: Neuron-specific enolase correlates with other prognostic markers after cardiac arrest. Neurology 2011, 77: 623-630. 10.1212/WNL.0b013e31822a276dPubMedGoogle Scholar
- Ost M, Nylen K, Csajbok L, Ohrfelt AO, Tullberg M, Wikkelso C, Nellgard P, Rosengren L, Blennow K, Nellgard B: Initial CSF total tau correlates with 1-year outcome in patients with traumatic brain injury. Neurology 2006, 67: 1600-1604. 10.1212/01.wnl.0000242732.06714.0fPubMedGoogle Scholar
- Magnoni S, Esparza TJ, Conte V, Carbonara M, Carrabba G, Holtzman DM, Zipfel GJ, Stocchetti N, Brody DL: Tau elevations in the brain extracellular space correlate with reduced amyloid-beta levels and predict adverse clinical outcomes after severe traumatic brain injury. Brain 2012, 135: 1268-1280. 10.1093/brain/awr286PubMed CentralPubMedGoogle Scholar
- Kay A, Petzold A, Kerr M, Keir G, Thompson E, Nicoll J: Temporal alterations in cerebrospinal fluid amyloid beta-protein and apolipoprotein E after subarachnoid hemorrhage. Stroke 2003, 34: e240-e243. 10.1161/01.STR.0000100157.88508.2FPubMedGoogle Scholar
- Franz G, Beer R, Kampfl A, Engelhardt K, Schmutzhard E, Ulmer H, Deisenhammer F: Amyloid beta 1-42 and tau in cerebrospinal fluid after severe traumatic brain injury. Neurology 2003, 60: 1457-1461. 10.1212/01.WNL.0000063313.57292.00PubMedGoogle Scholar
- Brody DL, Magnoni S, Schwetye KE, Spinner ML, Esparza TJ, Stocchetti N, Zipfel GJ, Holtzman DM: Amyloid-beta dynamics correlate with neurological status in the injured human brain. Science 2008, 321: 1221-1224. 10.1126/science.1161591PubMed CentralPubMedGoogle Scholar
- Petzold A, Tisdall MM, Girbes AR, Martinian L, Thom M, Kitchen N, Smith M: In vivo monitoring of neuronal loss in traumatic brain injury: a microdialysis study. Brain 2011, 134: 464-483. 10.1093/brain/awq360PubMed CentralPubMedGoogle Scholar
- Petzold A, Keir G, Kay A, Kerr M, Thompson EJ: Axonal damage and outcome in subarachnoid haemorrhage. J Neurol Neurosurg Psychiatry 2006, 77: 753-759. 10.1136/jnnp.2005.085175PubMed CentralPubMedGoogle Scholar
- Petzold A, Rejdak K, Belli A, Sen J, Keir G, Kitchen N, Smith M, Thompson EJ: Axonal pathology in subarachnoid and intracerebral hemorrhage. J Neurotrauma 2005, 22: 407-414. 10.1089/neu.2005.22.407PubMedGoogle Scholar
- Papa L, Akinyi L, Liu MC, Pineda JA, Tepas JJ, Oli MW, Zheng W, Robinson G, Robicsek SA, Gabrielli A, Heaton SC, Hannay HJ, Demery JA, Brophy GM, Layon J, Robertson CS, Hayes RL, Wang KK: Ubiquitin C-terminal hydrolase is a novel biomarker in humans for severe traumatic brain injury. Crit Care Med 2010, 38: 138-144. 10.1097/CCM.0b013e3181b788abPubMed CentralPubMedGoogle Scholar
- Mondello S, Papa L, Buki A, Bullock MR, Czeiter E, Tortella FC, Wang KK, Hayes RL: Neuronal and glial markers are differently associated with computed tomography findings and outcome in patients with severe traumatic brain injury: a case control study. Crit Care 2011, 15: R156. 10.1186/cc10286PubMed CentralPubMedGoogle Scholar
- Pineda JA, Lewis SB, Valadka AB, Papa L, Hannay HJ, Heaton SC, Demery JA, Liu MC, Aikman JM, Akle V, Brophy GM, Tepas JJ, Wang KK, Robertson CS, Hayes RL: Clinical significance of alphaII-spectrin breakdown products in cerebrospinal fluid after severe traumatic brain injury. J Neurotrauma 2007, 24: 354-366. 10.1089/neu.2006.003789PubMedGoogle Scholar
- Berger RP, Hayes RL, Richichi R, Beers SR, Wang KK: Serum concentrations of ubiquitin C-terminal hydrolase-L1 and alphaII-spectrin breakdown product 145 kDa correlate with outcome after pediatric TBI. J Neurotrauma 2012, 29: 162-167. 10.1089/neu.2011.1989PubMed CentralPubMedGoogle Scholar
- Vespa PM, Miller C, McArthur D, Eliseo M, Etchepare M, Hirt D, Glenn TC, Martin N, Hovda D: Nonconvulsive electrographic seizures after traumatic brain injury result in a delayed, prolonged increase in intracranial pressure and metabolic crisis. Crit Care Med 2007, 35: 2830-2836. 10.1097/01.CCM.0000295667.66853.BCPubMed CentralPubMedGoogle Scholar
- Pandian JD, Cascino GD, So EL, Manno E, Fulgham JR: Digital video-electroencephalographic monitoring in the neurological-neurosurgical intensive care unit: clinical features and outcome. Arch Neurol 2004, 61: 1090-1094. 10.1001/archneur.61.7.1090PubMedGoogle Scholar
- Claassen J, Mayer SA, Kowalski RG, Emerson RG, Hirsch LJ: Detection of electrographic seizures with continuous EEG monitoring in critically ill patients. Neurology 2004, 62: 1743-1748. 10.1212/01.WNL.0000125184.88797.62PubMedGoogle Scholar
- Vespa PM, Nuwer MR, Juhasz C, Alexander M, Nenov V, Martin N, Becker DP: Early detection of vasospasm after acute subarachnoid hemorrhage using continuous EEG ICU monitoring. Electroencephalogr Clin Neurophysiol 1997, 103: 607-615. 10.1016/S0013-4694(97)00071-0PubMedGoogle Scholar
- Rathakrishnan R, Gotman J, Dubeau F, Angle M: Using continuous electroencephalography in the management of delayed cerebral ischemia following subarachnoid hemorrhage. Neurocrit Care 2011, 14: 152-161. 10.1007/s12028-010-9495-2PubMedGoogle Scholar
- Klopman MA, Sebel PS: Cost-effectiveness of bispectral index monitoring. Curr Opin Anaesthesiol 2011, 24: 177-181. 10.1097/ACO.0b013e328343eb19PubMedGoogle Scholar
- Boccagni C, Bagnato S, Sant AA, Prestandrea C, Galardi G: Usefulness of standard EEG in predicting the outcome of patients with disorders of consciousness after anoxic coma. J Clin Neurophysiol 2011, 28: 489-492.PubMedGoogle Scholar
- Vespa PM, Boscardin WJ, Hovda DA, McArthur DL, Nuwer MR, Martin NA, Nenov V, Glenn TC, Bergsneider M, Kelly DF, Becker DP: Early and persistent impaired percent alpha variability on continuous electroencephalography monitoring as predictive of poor outcome after traumatic brain injury. J Neurosurg 2002, 97: 84-92. 10.3171/jns.2002.97.1.0084PubMedGoogle Scholar
- Hebb MO, McArthur DL, Alger J, Etchepare M, Glenn TC, Bergsneider M, Martin N, Vespa PM: Impaired percent alpha variability on continuous electroencephalography is associated with thalamic injury and predicts poor long-term outcome after human traumatic brain injury. J Neurotrauma 2007, 24: 579-590. 10.1089/neu.2006.0146PubMedGoogle Scholar
- Dreier JP: The role of spreading depression, spreading depolarization and spreading ischemia in neurological disease. Nat Med 2011, 17: 439-447. 10.1038/nm.2333PubMedGoogle Scholar
- Feuerstein D, Manning A, Hashemi P, Bhatia R, Fabricius M, Tolias C, Pahl C, Ervine M, Strong AJ, Boutelle MG: Dynamic metabolic response to multiple spreading depolarizations in patients with acute brain injury: an online microdialysis study. J Cereb Blood Flow Metab 2010, 30: 1343-1355. 10.1038/jcbfm.2010.17PubMed CentralPubMedGoogle Scholar
- Hartings JA, Watanabe T, Bullock MR, Okonkwo DO, Fabricius M, Woitzik J, Dreier JP, Puccio A, Shutter LA, Pahl C, Strong AJ: Spreading depolarizations have prolonged direct current shifts and are associated with poor outcome in brain trauma. Brain 2011, 134: 1529-1540. 10.1093/brain/awr048PubMedGoogle Scholar
- Woitzik J, Dreier JP, Hecht N, Fiss I, Sandow N, Major S, Winkler M, Dahlem YA, Manville J, Diepers M, Muench E, Kasuya H, Schmiedek P, Vajkoczy P: Delayed cerebral ischemia and spreading depolarization in absence of angiographic vasospasm after subarachnoid hemorrhage. J Cereb Blood Flow Metab 2012, 32: 203-212. 10.1038/jcbfm.2011.169PubMed CentralPubMedGoogle Scholar
- Drenckhahn C, Winkler MK, Major S, Scheel M, Kang EJ, Pinczolits A, Grozea C, Hartings JA, Woitzik J, Dreier JP: Correlates of spreading depolarization in human scalp electroencephalography. Brain 2012, 135: 853-868. 10.1093/brain/aws010PubMed CentralPubMedGoogle Scholar
- Robinson LR, Micklesen PJ, Tirschwell DL, Lew HL: Predictive value of somatosensory evoked potentials for awakening from coma. Crit Care Med 2003, 31: 960-967. 10.1097/01.CCM.0000053643.21751.3BPubMedGoogle Scholar
- Oddo M, Rossetti AO: Predicting neurological outcome after cardiac arrest. Curr Opin Crit Care 2011, 17: 254-259. 10.1097/MCC.0b013e328344f2aePubMedGoogle Scholar
- Hakimi K, Kinney G, Kraft G, Micklesen P, Robinson L: Reliability in interpretation of median somatosensory evoked potentials in the setting of coma: factors and implications. Neurocrit Care 2009, 11: 353-361. 10.1007/s12028-009-9251-7PubMedGoogle Scholar
- Zandbergen EG, Koelman JH, de Haan RJ, Hijdra A: SSEPs and prognosis in postanoxic coma: only short or also long latency responses? Neurology 2006, 67: 583-586. 10.1212/01.wnl.0000230162.35249.7fPubMedGoogle Scholar
- Marshall LF, Marshall SB, Klauber MR, van Berkum Clark M, Eisenberg HM, Jane JA, Luerssen TG, Marmarou A, Foulkes MA: A new classification of head injury based on computerized tomography. J Neurosurg 1991, 75: S14-S20.Google Scholar
- Maas AI, Hukkelhoven CW, Marshall LF, Steyerberg EW: Prediction of outcome in traumatic brain injury with computed tomographic characteristics: a comparison between the computed tomographic classification and combinations of computed tomographic predictors. Neurosurgery 2005, 57: 1173-1182.PubMedGoogle Scholar
- Wijman CA, Mlynash M, Caulfield AF, Hsia AW, Eyngorn I, Bammer R, Fischbein N, Albers GW, Moseley M: Prognostic value of brain diffusion-weighted imaging after cardiac arrest. Ann Neurol 2009, 65: 394-402. 10.1002/ana.21632PubMed CentralPubMedGoogle Scholar
- Sidaros A, Engberg AW, Sidaros K, Liptrot MG, Herning M, Petersen P, Paulson OB, Jernigan TL, Rostrup E: Diffusion tensor imaging during recovery from severe traumatic brain injury and relation to clinical outcome: a longitudinal study. Brain 2008, 131: 559-572. 10.1093/brain/awm294PubMedGoogle Scholar
- Tollard E, Galanaud D, Perlbarg V, Sanchez-Pena P, Le Fur Y, Abdennour L, Cozzone P, Lehericy S, Chiras J, Puybasset L: Experience of diffusion tensor imaging and 1H spectroscopy for outcome prediction in severe traumatic brain injury: Preliminary results. Crit Care Med 2009, 37: 1448-1455. 10.1097/CCM.0b013e31819cf050PubMedGoogle Scholar
- Tong KA, Ashwal S, Holshouser BA, Nickerson JP, Wall CJ, Shutter LA, Osterdock RJ, Haacke EM, Kido D: Diffuse axonal injury in children: clinical correlation with hemorrhagic lesions. Ann Neurol 2004, 56: 36-50. 10.1002/ana.20123PubMedGoogle Scholar
- Kasahara M, Menon DK, Salmond CH, Outtrim JG, Taylor Tavares JV, Carpenter TA, Pickard JD, Sahakian BJ, Stamatakis EA: Altered functional connectivity in the motor network after traumatic brain injury. Neurology 2010, 75: 168-176. 10.1212/WNL.0b013e3181e7ca58PubMed CentralPubMedGoogle Scholar
- Karakis I, Montouris GD, Otis JA, Douglass LM, Jonas R, Velez-Ruiz N, Wilford K, Espinosa PS: A quick and reliable EEG montage for the detection of seizures in the critical care setting. J Clin Neurophysiol 2010, 27: 100-105. 10.1097/WNP.0b013e3181d649e4PubMedGoogle Scholar
- Piper I, Chambers I, Citerio G, Enblad P, Gregson B, Howells T, Kiening K, Mattern J, Nilsson P, Ragauskas A, Sahuquillo J, Donald R, Sinnott R, Stell A: The brain monitoring with Information Technology (BrainIT) collaborative network: EC feasibility study results and future direction. Acta Neurochir (Wien) 2010, 152: 1859-1871. 10.1007/s00701-010-0719-1Google Scholar
- Sorani MD, Hemphill JC, Morabito D, Rosenthal G, Manley GT: New approaches to physiological informatics in neurocritical care. Neurocrit Care 2007, 7: 45-52. 10.1007/s12028-007-0043-7PubMedGoogle Scholar
- Maas AI, Menon DK, Lingsma HF, Pineda JA, Sandel ME, Manley GT: Reorientation of clinical research in traumatic brain injury: report of an international workshop on comparative effectiveness research. J Neurotrauma 2012, 29: 32-46. 10.1089/neu.2010.1599PubMed CentralPubMedGoogle Scholar