Karol P. Budohoski

Continuous determination of optimal cerebral perfusion pressure in traumatic brain injury

Objectives: We have sought to develop an automated methodology for the continuous updating of optimal cerebral perfusion pressure (CPPopt) for patients after severe traumatic head injury, using continuous monitoring of cerebrovascular pressure reactivity. We then validated the CPPopt algorithm by determining the association between outcome and the deviation of actual CPP from CPPopt. Design: Retrospective analysis of prospectively collected data. Setting: Neurosciences critical care unit of a university hospital. Patients: A total of 327 traumatic head-injury patients admitted between 2003 and 2009 with continuous monitoring of arterial blood pressure and intracranial pressure. Measurements and Main Results: Arterial blood pressure, intracranial pressure, and CPP were continuously recorded, and pressure reactivity index was calculated online. Outcome was assessed at 6 months. An automated curve fitting method was applied to determine CPP at the minimum value for pressure reactivity index (CPPopt). A time trend of CPPopt was created using a moving 4-hr window, updated every minute. Identification of CPPopt was, on average, feasible during 55% of the whole recording period. Patient outcome correlated with the continuously updated difference between median CPP and CPPopt (chi-square = 45, p < .001; outcome dichotomized into fatal and nonfatal). Mortality was associated with relative “hypoperfusion” (CPP < CPPopt), severe disability with “hyperperfusion” (CPP > CPPopt), and favorable outcome was associated with smaller deviations of CPP from the individualized CPPopt. While deviations from global target CPP values of 60 mm Hg and 70 mm Hg were also related to outcome, these relationships were less robust. Conclusions: Real-time CPPopt could be identified during the recording time of majority of the patients. Patients with a median CPP close to CPPopt were more likely to have a favorable outcome than those in whom median CPP was widely different from CPPopt. Deviations from individualized CPPopt were more predictive of outcome than deviations from a common target CPP. CPP management to optimize cerebrovascular pressure reactivity should be the subject of future clinical trial in severe traumatic head-injury patients.

Impairment of Cerebral Autoregulation Predicts Delayed Cerebral Ischemia After Subarachnoid Hemorrhage: A Prospective Observational Study

Background and Purpose— Delayed cerebral ischemia (DCI) is a recognized contributor to unfavorable outcome after subarachnoid hemorrhage (SAH). Recent data challenge the concept of vasospasm as the sole cause of ischemia and suggest a multifactorial process with dysfunctional cerebral autoregulation as a component. We tested the hypothesis that early autoregulatory failure, detected using near-infrared spectroscopy–based index, TOxa and transcranial Doppler–based index, Sxa, can predict DCI. Methods— In this prospective observational study we enrolled consecutive patients with aneurysmal SAH that occurred <5 days from admission. The primary end point was the occurrence of DCI within 21 days of ictus. The predictive value of autoregulatory disturbances detected in the first 5 days was assessed using univarate proportional hazards model and a multivariate model. Results— Ninety-eight patients were included. Univariate analysis demonstrated increased odds of developing DCI when early autoregulation failure was detected (odds ratio [OR], 7.46; 95% confidence interval [CI], 3.03–18.40 and OR, 4.52; 95% CI, 1.84–11.07 for Sxa and TOxa, respectively) but not TCD-vasospasm (OR, 1.36; 95% CI, 0.56–3.33). In a multivariate model Sxa and TOxa remained independent predictors of DCI (OR, 12.66; 95% CI, 2.97–54.07 and OR, 5.34; 95% CI, 1.25–22.84 for Sxa and TOxa, respectively). Conclusions— Disturbed autoregulation in the first 5 days after SAH significantly increases the risk of DCI. Autoregulatory disturbances can be detected using near-infrared spectroscopy and transcranial Doppler technologies.

Clinical relevance of cerebral autoregulation following subarachnoid haemorrhage.

Subarachnoid haemorrhage (SAH) is a form of stroke that is associated with substantial morbidity, often as a result of cerebral ischaemia that occurs in the following days. These delayed deficits in blood flow have been traditionally attributed to cerebral vasospasm (the narrowing of large arteries), which can lead to cerebral infarction and poor neurological outcome. Data from recent studies, however, show that treatment of vasospasm in patients with SAH, using targeted medication, does not translate to better neurological outcomes, and argue against vasospasm being the sole cause of the delayed ischaemic complications. Cerebral autoregulation—a mechanism that maintains stability of cerebral blood flow in response to changes in cerebral perfusion pressure—has been reported to fail after SAH, often before vasospasm becomes apparent. Failure of autoregulation, therefore, has been implicated in development of delayed cerebral ischaemia. In this Review, we summarize current knowledge about the clinical effect of disturbed cerebral autoregulation following aneurysmal SAH, with emphasis on development of delayed cerebral ischaemia and clinical outcome, and provide a critical assessment of studies of cerebral autoregulation in SAH with respect to the method of blood-flow measurement. Better understanding of cerebral autoregulation following SAH could reveal mechanisms of blood-flow regulation that could be therapeutically targeted to improve patient outcome.

The pathophysiology and treatment of delayed cerebral ischaemia following subarachnoid haemorrhage

Cerebral vasospasm has traditionally been regarded as an important cause of delayed cerebral ischaemia (DCI) which occurs after aneurysmal subarachnoid haemorrhage, and often leads to cerebral infarction and poor neurological outcome. However, data from recent studies argue against a pure focus on vasospasm as the cause of delayed ischaemic complications. Findings that marked reduction in the incidence of vasospasm does not translate to a reduction in DCI, or better outcomes has intensified research into other possible mechanisms which may promote ischaemic complications. Early brain injury and cell death, blood-brain barrier disruption and initiation of an inflammatory cascade, microvascular spasm, microthrombosis, cortical spreading depolarisations and failure of cerebral autoregulation, have all been implicated in the pathophysiology of DCI. This review summarises the current knowledge about the mechanisms underlying the development of DCI. Furthermore, it aims to describe and categorise the known pharmacological treatment options with respect to the presumed mechanism of action and its role in DCI.

Cerebral autoregulation after subarachnoid hemorrhage: comparison of three methods.

In patients after subarachnoid hemorrhage (SAH) failure of cerebral autoregulation is associated with delayed cerebral ischemia (DCI). Various methods of assessing autoregulation are available, but their predictive values remain unknown. We characterize the relationship between different indices of autoregulation. Patients with SAH within 5 days were included in a prospective study. The relationship between three indices of autoregulation was analyzed: two indices calculated using spontaneous blood pressure fluctuations, Sxa (based on transcranial Doppler) and TOxa (based on near-infrared spectroscopy); and transient hyperemic response test (THRT) where a brief compression of the common carotid artery is used. The predictive value of indices was assessed using data from the first 5 days. Overall there was only moderate correlation between indices. However, both Sxa and TOxa showed good accuracy in predicting impaired autoregulation evidenced by a negative THRT (area under the curve (AUC): 0.788, 95% CI: 0.723 to 0.854 and AUC: 0.827, 95% CI: 0.769 to 0.885, respectively). All indices proved accurate in predicting DCI when 0- to 5-day data were used (AUC: 0.801, 95% CI: 0.660 to 0.942; AUC: 0.857, 95% CI: 0.731 to 0.984, AUC: 0.796, 95% CI: 0.658 to 0.934 for THRT, Sxa, and TOxa, respectively). Combining all three indices had 100% specificity for predicting DCI. While multiple colinearities exist between the assessed methods, multimodal monitoring of cerebral autoregulation can aid in predicting DCI.

What comes first? The dynamics of cerebral oxygenation and blood flow in response to changes in arterial pressure and intracranial pressure after head injury

BACKGROUND Brain tissue partial oxygen pressure (Pbt(O(2))) and near-infrared spectroscopy (NIRS) are novel methods to evaluate cerebral oxygenation. We studied the response patterns of Pbt(O(2)), NIRS, and cerebral blood flow velocity (CBFV) to changes in arterial pressure (AP) and intracranial pressure (ICP). METHODS Digital recordings of multimodal brain monitoring from 42 head-injured patients were retrospectively analysed. Response latencies and patterns of Pbt(O(2)), NIRS-derived parameters [tissue oxygenation index (TOI) and total haemoglobin index (THI)], and CBFV reactions to fluctuations of AP and ICP were studied. RESULTS One hundred and twenty-one events were identified. In reaction to alterations of AP, ICP reacted first [4.3 s; inter-quartile range (IQR) -4.9 to 22.0 s, followed by NIRS-derived parameters and CBFV (10.9 s; IQR: -5.9 to 39.6 s, 12.1 s; IQR: -3.0 to 49.1 s, 14.7 s; IQR: -8.8 to 52.3 s for THI, CBFV, and TOI, respectively), with Pbt(O(2)) reacting last (39.6 s; IQR: 16.4 to 66.0 s). The differences in reaction time between NIRS parameters and Pbt(O(2)) were significant (P<0.001). Similarly when reactions to ICP changes were analysed, NIRS parameters preceded Pbt(O(2)) (7.1 s; IQR: -8.8 to 195.0 s, 18.1 s; IQR: -20.6 to 80.7 s, 22.9 s; IQR: 11.0 to 53.0 s for THI, TOI, and Pbt(O(2)), respectively). Two main patterns of responses to AP changes were identified. With preserved cerebrovascular reactivity, TOI and Pbt(O(2)) followed the direction of AP. With impaired cerebrovascular reactivity, TOI and Pbt(O(2)) decreased while AP and ICP increased. In 77% of events, the direction of TOI changes was concordant with Pbt(O(2)). CONCLUSIONS NIRS and transcranial Doppler signals reacted first to AP and ICP changes. The reaction of Pbt(O(2)) is delayed. The results imply that the analysed modalities monitor different stages of cerebral oxygenation.

Critical closing pressure determined with a model of cerebrovascular impedance.

Critical closing pressure (CCP) is the arterial blood pressure (ABP) at which brain vessels collapse and cerebral blood flow (CBF) ceases. Using the concept of impedance to CBF, CCP can be expressed with brain-monitoring parameters: cerebral perfusion pressure (CPP), ABP, blood flow velocity (FV), and heart rate. The novel multiparameter method (CCPm) was compared with traditional transcranial Doppler (TCD) calculations of CCP (CCP1). Digital recordings of ABP, intracranial pressure (ICP), and TCD-based FV from previously published studies of 29 New Zealand White rabbits were reanalyzed. Overall, CCP1 and CCPm showed correlation across wide ranges of ABP, ICP, and PaCO2 (R = 0.93, P < 0.001). Three physiological perturbations were studied: increase in ICP (n = 29) causing both CCP1 and CCPm to increase (P < 0.001 for both); reduction of ABP (n = 10) resulting in decrease of CCP1 (P = 0.006) and CCPm (P = 0.002); and controlled increase of PaCO2 (n = 8) to hypercapnic levels, which decreased CCP1 and CCPm, albeit insignificantly (P = 0.123 and P = 0.306 respectively), caused by a spontaneous significant increase in ABP (P = 0.025). Multiparameter mathematical model of critical closing pressure explains the relationship of CCP on brain-monitoring variables, allowing the estimation of CCP during cases such as hypercapnia-induced hyperemia, where traditional calculations, like CCP1, often reach negative non-physiological values.

Regulation of the cerebral circulation: bedside assessment and clinical implications

Regulation of the cerebral circulation relies on the complex interplay between cardiovascular, respiratory, and neural physiology. In health, these physiologic systems act to maintain an adequate cerebral blood flow (CBF) through modulation of hydrodynamic parameters; the resistance of cerebral vessels, and the arterial, intracranial, and venous pressures. In critical illness, however, one or more of these parameters can be compromised, raising the possibility of disturbed CBF regulation and its pathophysiologic sequelae. Rigorous assessment of the cerebral circulation requires not only measuring CBF and its hydrodynamic determinants but also assessing the stability of CBF in response to changes in arterial pressure (cerebral autoregulation), the reactivity of CBF to a vasodilator (carbon dioxide reactivity, for example), and the dynamic regulation of arterial pressure (baroreceptor sensitivity). Ideally, cerebral circulation monitors in critical care should be continuous, physically robust, allow for both regional and global CBF assessment, and be conducive to application at the bedside. Regulation of the cerebral circulation is impaired not only in primary neurologic conditions that affect the vasculature such as subarachnoid haemorrhage and stroke, but also in conditions that affect the regulation of intracranial pressure (such as traumatic brain injury and hydrocephalus) or arterial blood pressure (sepsis or cardiac dysfunction). Importantly, this impairment is often associated with poor patient outcome. At present, assessment of the cerebral circulation is primarily used as a research tool to elucidate pathophysiology or prognosis. However, when combined with other physiologic signals and online analytical techniques, cerebral circulation monitoring has the appealing potential to not only prognosticate patients, but also direct critical care management.

The limitations of near-infrared spectroscopy to assess cerebrovascular reactivity: the role of slow frequency oscillations.

BACKGROUND:A total hemoglobin reactivity index (THx) derived from near-infrared spectroscopy (NIRS) has recently been introduced to assess cerebrovascular reactivity noninvasively. Analogously to the pressure reactivity index (PRx), THx is calculated as correlation coefficient with arterial blood pressure (ABP). However, the reliability of THx in the injured brain is uncertain. Although slow oscillations have been described in NIRS signals, their significance for assessment of autoregulation remains unclear. In the current study, we investigated the role of slow oscillations of total hemoglobin for NIRS-based cerebrovascular reactivity monitoring. METHODS:This study was based on a retrospective analysis of data that were consecutively recorded for a different project published previously. Thirty-seven patients with traumatic brain injury and admitted to Addenbrookes Neurosciences Critical Care Unit between June 2008 and June 2009 were included. After artifact removal, we performed spectral analysis of the tissue hemoglobin index (THI, a measure of oxy- and deoxygenated hemoglobin) and intracranial pressure (ICP) signal. PRx and THx were calculated as moving correlations between ICP and ABP, and THI and ABP, respectively. The agreement between PRx and THx as a function of normalized power of slow oscillations (0.015–0.055 Hz) contained in the input signals was assessed performing between-subject and within-subject correlation analyses. Furthermore, the correlation between the THx values derived from the right and left sides was analyzed. RESULTS:The agreement between PRx and THx depended on the power of slow oscillations in the input signals. Between-subject comparisons revealed a significant correlation between THx and PRx (r = 0.80, 95% confidence interval 0.53–0.92, P < 0.01) for patients with normalized slow wave activity >0.4 in the THI signal, compared with r = 0.07 (95% confidence interval −0.40 to 0.51, P = 0.79) in the remaining files. Furthermore, within-subject comparisons suggested that THx may be used as a substitute for PRx only when there is an at least moderate agreement (r = 0.36) between the THx values derived from the right and left sides. CONCLUSIONS:Our results suggest that the NIRS-based cerebrovascular reactivity index THx can be used as a noninvasive substitute for PRx, but only during phases with sufficient slow wave power in the input signal. Furthermore, a good agreement between the THx measures on both sides seems to be a prerequisite for comparison of a global (PRx) versus the more local (THx) index. Nevertheless, noninvasive assessment of cerebrovascular reactivity may be desirable in patients without ICP monitoring and help to guide ABP management in these patients.

Comparison of frequency and time domain methods of assessment of cerebral autoregulation in traumatic brain injury

The impulse response (IR)-based autoregulation index (ARI) allows for continuous monitoring of cerebral autoregulation using spontaneous fluctuations of arterial blood pressure (ABP) and cerebral flow velocity (FV). We compared three methods of autoregulation assessment in 288 traumatic brain injury (TBI) patients managed in the Neurocritical Care Unit: (1) IR-based ARI; (2) transfer function (TF) phase, gain, and coherence; and (3) mean flow index (Mx). Autoregulation index was calculated using the TF estimation (Welch method) and classified according to the original Tiecks’ model. Mx was calculated as a correlation coefficient between 10-second averages of ABP and FV using a moving 300-second data window. Transfer function phase, gain, and coherence were extracted in the very low frequency (VLF, 0 to 0.05 Hz) and low frequency (LF, 0.05 to 0.15 Hz) bandwidths. We studied the relationship between these parameters and also compared them with patients’ Glasgow outcome score. The calculations were performed using both cerebral perfusion pressure (CPP; suffix ‘c’) as input and ABP (suffix ‘a’). The result showed a significant relationship between ARI and Mx when using either ABP (r=−0.38, P<0.001) or CPP (r=−0.404, P<0.001) as input. Transfer function phase and coherence_a were significantly correlated with ARI_a and ARI_c (P<0.05). Only ARI_a, ARI_c, Mx_a, Mx_c, and phase_c were significantly correlated with patients’ outcome, with Mx_c showing the strongest association.