Neurocrit Care DOI 10.1007/s12028-014-0049-x
REVIEW ARTICLE
The International Multi-disciplinary Consensus Conference on Multimodality Monitoring: Future Directions and Emerging Technologies Paul Vespa • David Menon • Peter Le Roux • and the Participants in the International Multi-disciplinary Consensus Conference on Multimodality Monitoring
Ó Springer Science+Business Media New York 2014
Abstract Neuromonitoring has evolved rapidly in recent years and there now are many new monitors that have revealed a great deal about the ongoing pathophysiology of brain injury and coma. Further evolution will include the consolidation of multi-modality monitoring (MMM), the development of next-generation informatics tools to identify complex physiologic events and decision support tools to permit targeted individualized care. In this review, we examine future directions and emerging technologies in neuromonitoring including: (1) device development, (2) what is the current limitation(s) of MMM in its present format(s), (3) what would improve the ability of MMM to enhance neurocritical care, and (4) how do we develop evidence for use of MMM? Keywords Secondary brain injury Monitor Informatics
The Participants in the International Multi-disciplinary Consensus Conference on Multimodality Monitoring are listed in ‘‘Appendix’’ section. P. Vespa Neurocritical Care, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA D. Menon Division of Anaesthesia, University of Cambridge, Cambridge, UK P. Le Roux (&) Brain and Spine Center, Suite 370, Medical Science Building, Lankenau Medical Center, 100 East Lancaster Avenue, Wynnewood, PA 19096, USA e-mail: [email protected]
Introduction Following acute brain injury (ABI), outcome is associated with both the primary insult whether it be traumatic brain injury (TBI), ischemic stroke, or aneurysm rupture among others and with a cascade of pathophysiologic events that evolve over time, i.e., secondary brain injury (SBI). These SBIs come in many different forms but their management is central to neurocritical care. This management is dependent, in large part on neuromonitoring. Traditionally, we have relied upon the clinical neurological examination to be our main neurological monitor and despite advances in monitoring devices it will always play a fundamental role in neurocritical care decisionmaking. Recent advances have seen the development of ‘‘objective scales’’ that permit serial assessment of consciousness, pain, sedation, and delirium among other functions to limit intra-and interobserver variability. We have tracked the clinical examination and made important decisions based on the changes in exam particularly when coupled with imaging findings. The importance of this is not to be underestimated [1] and will continue to evolve as imaging, particularly computed tomography (CT) and ultrasound (US), is brought to the bedside and used in point of care testing [2, 3]. However, in the last 20 years, we have learned that the clinical examination can frequently be nonspecific and unhelpful, may lag behind physiologic findings derived from a monitor and fails to inform substantial changes in neurologic function or final clinical outcome. Simultaneously, a substantial number of neurological monitors have been developed that provide specific information about various aspects of brain physiology, function, and structure. These specific data appear to be time sensitive, robust, informative, and deterministic or at least prognostic
123
Neurocrit Care
and have revealed a great deal about the ongoing pathophysiology of brain injury and coma. We have also learnt that there is no single ideal monitor [although we continue to strive to create one (Table 1)] and that more than one monitor should be used since the brain is a complex organ and no one single method can provide comprehensive information about the brain’s health [4], i.e., multimodality monitoring (MMM). Multimodality monitoring is compelling since the data are objective and provide discriminative dynamic information about human brain pathophysiology that can be quantified, trended, and evaluated. This concept of MMM—i.e., the simultaneous collection of data from multiple diverse sources associated with a single patient has evolved in recent years and it is safe to say that MMM is here to stay and likely will be the backbone of bedside physiologic monitoring in neurocritcial care in the foreseeable future. Accumulating evidence suggests that much of the information gained from MMM substantially augments our assessment of patients well beyond the clinical exam and can enhance outcome when used to guide patient management in a patient-specific, targeted fashion [4–7]. The current challenge is it is difficult to digest these data and the future may be less about new device development but more about data display, integration and analysis, and decision support [8, 9]. The reader is referred to the article by Schmidt et al. in this Supplement for a discussion on the emerging field of bioinformatics. What new technologies can we expect and what will the future of MMM be? This is a complex question that entails several considerations about the current capabilities, current limitations, technology development that is entangled with industry desire, commercial interests and legislative limitations, and desires about how MMM is integrated into our clinical practice that in large part depends on generating evidence that use of a monitor makes a difference. Here the question gets more complex because no monitor or combination of monitors makes a difference. Rather it is
the wise application of the data from monitoring the injured brain that can influence therapeutic decisions. We will consider the following as we discuss the future directions of neuromonitoring: (1) Devices and device development, (2) what is the current limitation(s) of MMM in its present format(s), (3) what would enhance the ability of MMM to be useful in changing clinical outcome, and (4) how do we develop evidence for use of MMM? Questions to consider when evaluating neuromonitors are listed in Table 2.
Devices and Device Development There are a wide range of devices used to monitor the brain and in 2012, the global brain monitoring devices market was valued at $1.08 billion and is expected to grow at a compound annual growth rate (CAGR) of 8.6% [10]. There are many reasons for this continued growth including: (1) technological advancements, (2) ease of operation, (3) device miniaturization, (4) rising awareness of the role of SBI not only in ABI but also in other disorders including cardiovascular diseases, sleep disorders, peri-operative care, and neurodegenerative diseases to name a few, (5) use of devices for reasons other than traditional ‘‘monitoring,’’ e.g., enhanced communication in the ‘‘locked-in syndrome’’ or a brain-computer interface (BCI), and (6) an increase in computing power. In addition, the introduction and advancement of wireless, non-invasive, and mobile devices including smart phone technology means that neuro-monitoring is no longer limited to the intensive care unit but also is used in the emergency room, preoperative and postoperative care, and during routine evaluations.
Table 2 Questions to consider when evaluating neuromonitors What is the device, i.e., what exactly does it measure Are there complimentary monitors that can be used in the same pathophysiologic process How to use it
Table 1 Features of an ‘‘ideal neuromonitor’’ Portable Provides point of care measurement High spatial resolution High temporal resolution Continuous or frequently repeatable Does not interfere with patient care Noninvasive Reliable and reproducible quantitative data
Who to use it or in who is the pathophysiologic process important Are we measuring what we think we are measuring Device accuracy, precision, sensitivity and specificity Limitations, technical problems, troubleshooting, and safety The limiting conditions in which accuracy or precision are lost Reproducibility of measurements Effects of observer bias Balance the desirable and undesirable consequences of tests or information from a monitor
Not operator dependent
Does data from a device (or of monitoring a specific pathophysiological process) make a contribution to patient care
Easy to perform; requires little training to use Suggest a cause and appropriate treatment
Deficits in knowledge and future directions Cost effectiveness and justification in clinical care
123
Neurocrit Care
Technologic advances that occur in these environments will influence critical care neuromonitoring and vice versa. Currently, there are a variety of invasive and noninvasive probes that are used for brain monitoring. In this supplement, we have explored pathophysiologic processes that are of interest to intensivists rather than individual devices. These various monitors each have a number of advantages but all have disadvantages or limitations that preclude or limit broad generalizability of use (see individual chapters in this Supplement). For the invasive monitors such as intracranial pressure (ICP), brain tissue oxygen (PbtO2), and brain microdialysis, the devices are by their nature invasive and carry the risk of intracranial bleeding and infection. The invasive devices therefore cannot be used in coagulopathic patients. In addition, they are not used in patients with mild or moderate injury. A question that remains is whether some of the devices used in severe injury may have their best role in moderate injury. The non-invasive devices such as near-infrared spectroscopy (NIRS), cEEG, and transcranial Doppler (TCD), suffer from nonspecificity and sampling restriction limitations. For example, cEEG is a powerful technique, but nonspecificity of changes as they relate to cerebral perfusion and metabolism, as well as the inability to detect important electrical events deep inside of the tissue and adjacent to brain hemorrhage, are important limitations. Better Probes and Monitors The near future (5–10 years) is likely to see the development of better probes and better monitors of currently identified processes rather than the identification of some new pathophysiologic process to evaluate. The exception to this may be the evolution of biomarkers or combinations of biomarkers. Development at present is following one or two avenues: (1) non-invasive tools that use near-infrared spectroscopy (NIRS), acoustic, or ultrasound signals among other methodologies or (2) incorporation of many monitors onto a single invasive device [11–16]. There are several monitors that are undergoing product development to enhance their capability. NIRS is one type of device that is being modified to provide information not only on brain oxygenation but also on cerebral blood flow (CBF) and metabolism [15]. The next-generation NIRS devices will be able to make noninvasive CBF measures and the use of NIRS to perform diffuse correlational spectroscopy enables measures of cortical CBF which have been validated against xenon CT CBF imaging [16]. A combined NIRS and depth EEG probe has been successfully tested in rodent models [17]. Outside of the ICU the combination of NIRS and EEG is used to enhance the BCI for neuroprosthetics [18]. Conceptually this makes sense since EEG and NIRS are sensitive to different cascades of
events that are linked to the same neural activities. cEEG techniques and software analysis programs are being modified to provide better indicators of seizures, and CBF. Depth electrode modifications are being considered that will enable the reliable detection of cortical spreading depolarizations (CSDs) [19] and seizures. Noninvasive ICP monitors are being developed and potentially could include assessment of optic nerve sheath diameter [20, 21], venous ophthalmodynamometry [22, 23], TCD analytics [24], pupillometry [25, 26], or modifications of NIRS. At present none of the non-invasive devices are able to replace their invasive counterpart and much work is still required. There are several novel diagnostic devices that may play a role in MMM in the future. One technology is called volumetric electromagnetic phase shift spectroscopy (VEPS). This device is shown in Fig. 1. This is a noninvasive device that creates a magnetic field surrounding the head, and can detect cerebral edema and hemorrhage. One could envision this as an adjunct to conventional imaging to track progressive brain edema. This device is not FDA approved yet and has only been studied to a limited extent in humans [27]. Another diagnostic device that is FDA approved is the Infrascanner. This is a handheld device that is capable of detecting intracerebral hemorrhages greater than 3.5 cc [28]. This device is envisioned to be used in a triage setting before conventional scanning, however, with further device development one could foresee it’s use in the ICU as a supplement to serial neurologic examination. The focus of this supplement has been on physiologic monitors. However, the concept of bedside imaging in the ICU being used as a monitor has already started to develop and is important to the concept of MMM. For example, probe position can influence data interpretation [29], hence a postinsertion CT scan can be very valuable in evaluating treatment effects. The use of portable CT scanners is a prime example of this [2, 3]. Importantly bringing imaging technology to the bedside can significantly decrease complications and physiologic derangements associated with patient transport and will become an important component of ICU care in the future [30, 31]. Some ICUs have CT, MRI, and PET directly adjacent to the ICU. Interventional suites that feature multimodality imaging during acute vascular interventions are now being planned and implemented [32].
Current Limitations The main limitation of multimodality monitoring, and of bedside neuromonitoring in general in neurocritical care, is the limited evidence, specifically level 1 evidence that guides how best to use the various devices, integrate them and most importantly whether the knowledge gained from them can have a positive effect on outcome. This limitation
123
Neurocrit Care Fig. 1 The VEPS brain edema online monitoring system
is discussed in much of the analysis in the selected chapters. This is not surprising given the inherent problems with creating a definitive study, including (1) the reality that disease-specific variables influence outcome to a great extent thus limiting the power of any study of goal directed treatment derived by brain monitoring to influence outcome, (2) the uncertain best treatments based on the reliable brain monitoring indicators of secondary injury, and (3) the lack of experience in using, interpreting, and utilizing goal directed therapy in neurocritical care. It is conceivable that answers may not come from randomized controlled studies of brain monitoring in a goal-directed therapy. Instead careful clinical observation may help provide greater insight into disease pathophysiology, understand mechanisms of disease, help design-targeted treatment strategies, and importantly develop new treatments. We should take a lesson from the experience of the pulmonary artery catheter studies of the past and not be anxious to ‘‘prove the monitor.’’ It is likely that we will one day be able to test these devices, but careful consideration needs to be applied and more understanding about the pathophysiology is required before we embark on such a study, i.e., it is not the monitor per se that needs study but rather how the data is used that requires study. That assumes effective therapies exist. The second main limitation is that we do not have an integrated electronic platform to present and manipulate the multiple data streams from the monitors that are in use.
123
Table 3 Developments that will enhance the role of monitoring in neurocritical care Data accuracy (+artifact rejection) Data integration and multivariate/nonlinear synthesis and analysis Data display and decision support Non-invasive options Cost effectiveness Practical solutions for the real world Industry standardisation and compatibility Precompetitive benefits for industry and societal good from industry
Most electronic health record systems in the ICU are capable of displaying tabular information and some limited graphics of 1 or 2 parameters but generally are recapitulations of the medical record. Furthermore, these systems cannot display an integrated data set of the neurologic monitors to enable a summary graphic display of the data. More importantly, these systems cannot post-process the information to permit analysis of the data using simple methods (e.g., regression analysis) or time-aligned trend analysis. Hence, the information is disparate and non-time aligned. This places limits on interpretation of the data, and limits the usability of these data to a smaller number of people who are accustomed to mentally integrate the information. This type of manual/cognitive integration is subject to bias, human error, and misinterpretation.
Neurocrit Care
Future Directions
Table 4 Challenges to neurocritical care informatics (modified from references [8, 9])
There are several important developments that will enhance the ability of MMM to be useful in changing clinical outcome (Table 3). In particular, two stand out: (1) enhanced informatics (data display, integration, and analysis), and (2) improved studies that demonstrate efficacy of the techniques, and adaptations to several of the monitors.
Data acquisition electronically as a standard in intensive care units
Informatics
Missing data due to artifact, disconnection, different time domains, etc.
Neurocritical care depends on the continuous, real-time measurement of a variety of physiologic parameters that are both systemic, e.g., cardiac function and neurospecific, e.g., ICP, PbtO2, and CBF, to identify SBIs. This data requires interpretation with non-continuous data and ordinal data including the clinical examination, laboratory analysis, and imaging, i.e., the type of data is diverse and in different formats. However, while the number of variables that can be measured has grown the ability to transform the data into meaningful therapeutic strategies remains crude in large part because we use a uni-variate reactive threshold approach for data interpretation rather than a multivariate approach that also uses trends. Consequently, next-generation MMM will include an informatics approach and improved electronic data technologies to collect and interpret the ever increasing amount of data that has become available. In addition, decision support tools will develop. Informatics is the process of acquiring, storing, and analyzing data for clinical decision-making. Ideally this also includes techniques such as decision trees and Dynamic Bayesian Networks to enhance decision support. The field of bio-informatics is rapidly expanding and over the next 5 years, we will likely see the development and implementation of several visualization and presentation interfaces in neurocritical care (perhaps specific to the field) that serve to integrate the data into a time-aligned stream of information. There are several obstacles to critical bio-informatics (Table 4) including the proprietary nature of medical devices and software and the presence of artifacts that limits central capture and storage of highdensity data. Hence, the future evolution of MMM will require collaboration between industry, intensivists, and informatics experts. Several groups are working on components that are necessary for such an integrated view [33]. This informatics approach will feature discreet data elements from many of our brain monitors, all time aligned, so that the clinician can more easily interpret the data. An example of this type of integration is shown in Figs. 2 and 3. These figures show integrated dashboards of information that feature anatomic imaging combined with longitudinal
Varying types of data (e.g., numeric, imaging, text, continuous, ordinal)
Interoperability of different monitoring devices to acquire data Standardization of global-controlled vocabularies of terminology Volume and resolution of data Regulatory aspects of data collection (e.g., HIPAA and privacy boards) Automated artifact detection and cleaning of acquired data before analysis
Integration with electronic medical records and other patient data Whether to use all data or discard selectively or empirically Real-time analysis and feedback to the bedside Clinician acceptance and use of analyzed data
streams of physiological data. The informatics displays will be designed to be configured for optimal data interpretation, with the ability to alter the settings to focus in on short-duration periods of interest and highlight important moments of altered brain physiology or clinical neurological deterioration. These displays will be achievable and will serve as a source of quality control and research. Automated analytics will be incorporated into these displays thereby providing expert diagnostic information about the state of autoregulation (PRx) or intracranial compliance (MOCAIP) or some other feature, i.e., will allow exploration of the variability of a single value and trends, interactions between systems and the emergent order of variables. In so doing management can target the optimal range of physiology for a specific individual, i.e., ‘‘personalized intervention’’ rather than use a ‘‘one size fits all’’ approach as currently is done [34, 35]. Furthermore, care will become more proactive rather than reactive (which may be too late) because of an enhanced ability to predict deleterious events [36–38]. One futuristic informatics platform is the Ambient Intelligence (AMI) system that collects information from not only the patient but also from the environment and machine interfaces over time [39]. The AMI system permits data to be collected and streamed in real time, and then semi-automatically interpreted through the use automated algorithms that can be used to process the data. In a novel public–private partnership, a consortium of academic neurocritical care centers and Draper Laboratories (Cambridge, MA) have created an initial demonstration version of the next-generation of informatics for MMM. The IMEDS group, as it is called, envisions an open source system of informatics displays that will
123
Neurocrit Care
Fig. 2 Example of informatics display of multiple time-aligned data elements from ICP, Microdialysis, and Jugular Oximetry
enable simultaneous presentation of numerous data streams, and a platform for data analysis and manipulation. Figure 4 shows the initial demonstration zero version of the IMEDS system (data courtesy of Michael Schmidt, Columbia University). The data is time aligned and plotted to show variations in ICP and CPP. Prospective Studies to Evaluate Monitoring We do need to develop more evidence how brain monitors impact clinical outcome. To that end, small, randomized studies that focus on intermediate outcomes or biomarker outcomes seem to be a reasonable approach. For example, a study of the effectiveness of a brain monitor to accurately diagnose cerebral ischemia with validation of the monitor through complimentary use of brain imaging or a biomarker of ischemia would be a reasonable step. Some validation studies have already been done, but many questions remain about the sensitivity and specificity of these measures. These questions create an opportunity to enhance our understanding of these monitors and permits time for widespread experience with these monitors, experience which is necessary before embarking on definitive studies. There is a constant clamor for a Phase III randomized clinical trial (RCT) to prove that neuromonitoring or a
123
specific neuromonitor is beneficial. However, this largely reduces scientific methodology to one step—bias avoidance and confuses statistics with science (and physiology) by equating statistical precision with scientific exactness. Hence, few RCTs in critical care have been successful [40]. Alternatively successful RCTs have been refuted by subsequent trials [41], e.g., glucose control or suffer from practice misalignment [42]. Furthermore, a neuromonitor itself cannot be the subject of an RCT. Instead different management strategies can be compared. For example, while the BEST TRIP trial, one of very few and the most recent RCT to examine neuromonitoring is titled ‘‘A trial of intracranial-pressure monitoring in traumatic brain injury’’ it is not that [1]. Instead it is a trial of two management strategies for TBI that both rely on different monitoring strategies. The value of the monitor then is confused with the care given. And that is the problem: effective management may not exist or it is applied in a population-based manner when it only exists for a subset of trial patients or its use it associated with deleterious side effects. For example, Robertson et al. [43] examined ICP and CPP-based care in a RCT. They were able to demonstrate a reduction in secondary cerebral ischemia but outcome was similar because of pulmonary complications. These trial patients were treated with a ‘‘one size fits all’’ CPP approach. Today we are beginning to recognize the
Neurocrit Care
Fig. 3 Example of MMM diagnosing delayed cerebral ischemia after subarachnoid hemorrhage
Fig. 4 IMEDS demonstration Zero informatics display for MMM
physiologic importance of individual titration of CPP and ICP targets, i.e., defining an optimal CPP for each patient [7, 35]. This is more consistent with how we practice critical care since in the ICU we make decisions based on universal principles and practical wisdom that are customized for a particular patient. One RCT in which
neuromonitoring plays a role, BOOST-2 [44] has attempted to address this. BOOST-2 is a phase II TBI trial in which management strategies based on ICP and CPP are compared with those based on ICP, CPP, and PbtO2. This is a complex process of care trial and preliminary results demonstrate feasibility, safety, attainment of the primary endpoint, i.e., physiologic efficacy and enhanced outcome in those patients who have added PbtO2 based care [45]. Perhaps more important than the results of the trial is the information acquired to plan a Phase III RCT. The vast majority of neuroprotective trials, i.e., single drug trials have failed in ABI. Hence, it becomes important to: (1) understand what is happening in the patient, (2) think of care strategies rather than a single agent, and (3) develop personalized targeted approaches. To do this hightech monitoring and bio-informatics are necessary to better understand and essential to targeted therapy. The best study of neuromonitoring then may depend on registries, observational cohorts, or comparative effectiveness research [46]. In this context, the study of neuromonitoring has the obvious implication: examination of how the monitor performs but perhaps more importantly it can help identify novel therapeutic strategies. For that reason, it is an
123
Neurocrit Care Table 5 Requirements for multimodality monitoring Continuous monitoring Not to miss clinically significant events The frequency of monitoring needs to be higher than the duration of the events to be detected Comprehensive All of the necessary data for a particular monitoring goal needs to be collected simultaneously, time synchronized, and displayed in an integrated fashion Communicative Plot time synchronized trends on a single display Integrate waveforms, images, and other formats Statistical relationships
exciting and promising time to be practicing neurocritical care.
Conclusion The goal of neuromonitoring in intensive care is to enable the detection of harmful physiological events before they cause irreversible damage to the brain. Multimodality monitoring is inherent to the way we practice neurocritical care (Table 5). At its simplest level repeated neurologic exams and measurement of blood pressure and systemic O2 saturation for the purposes of making patient care decisions, is ‘‘Multi-Modality Monitoring.’’ At the other end of the spectrum is the integration of this information with imaging data and continuous neurospecific physiologic data obtained from a variety of diverse sources. The real questions that remain to be answered are: (1) are you getting the information you want (and need), (2) what monitoring tools can give you this information, and (3) is integrating information from multiple monitors better than using a single threshold for clinical decision making?
Appendix: Participants in the International Multidisciplinary Consensus Conference on Multimodality Monitoring Peter Le Roux, MD, FACS, Brain and Spine Center, Suite 370, Medical Science Building, Lankenau Medical Center, 100 East Lancaster Avenue, Wynnewood, PA 19096, USA. Tel: +1 610 642 3005; Fax: 610 642 3057 [email protected]
123
David K Menon MD PhD FRCP FRCA FFICM FMedSci Head, Division of Anaesthesia, University of Cambridge Consultant, Neurosciences Critical Care Unit Box 93, Addenbrooke’s Hospital, Cambridge CB2 2QQ, UK [email protected] Paul Vespa, MD, FCCM, FAAN, FNCS Professor of Neurology and Neurosurgery Director of Neurocritical Care David Geffen School of Medicine at UCLA Los Angeles, CA 90095 USA [email protected] Giuseppe Citerio, Director NeuroIntensive Care Unit, Department of Anesthesia and Critical Care Ospedale San Gerardo, Monza. Via Pergolesi 33, Monza 20900, Italy [email protected] Mary Kay Bader RN, MSN, CCNS, FAHA, FNCS Neuro/Critical Care CNS Mission Hospital Mission Viejo CA 92691, USA [email protected] Gretchen M. Brophy, PharmD, BCPS, FCCP, FCCM Professor of Pharmacotherapy & Outcomes Science and Neurosurgery Virginia Commonwealth University Medical College of Virginia Campus 410 N. 12th Street Richmond, Virginia 23298-0533 USA [email protected] Michael N. Diringer, MD Professor of Neurology, Neurosurgery & Anesthesiology Chief, Neurocritical Care Section Washington University Dept. of Neurology, Campus Box 8111 660 S Euclid Ave St Louis, MO 63110 USA [email protected] Nino Stocchetti, MD Professor of Anesthesia and Intensive Care Department of physiopathology and transplant, Milan University Director Neuro ICU Fondazione IRCCS Ca` Granda Ospedale Maggiore Policlinico Via F Sforza, 35 20122 Milan Italy e-mail [email protected]
Neurocrit Care
Walter Videtta, MD ICU Neurocritical Care Hospital Nacional ‘Prof. a. Posadas’ El Palomar - Pcia. de Buenos Aires Argentina [email protected] Rocco Armonda, MD Department of Neurosurgery MedStar Georgetown University Hospital Medstar Health, 3800 Reservoir Road NW Washington DC 20007 USA [email protected] Neeraj Badjatia, MD Department of Neurology University of Maryland Medical Center, 22 S Greene St Baltimore, MD, 21201 USA [email protected] Julian Boesel, MD Department of Neurology Ruprect-Karls University Hospital Heidelberg, Im Neuenheimer Feld 400, D-69120 Heidelberg, Germany [email protected] Randal Chesnut, MD, FCCM, FACS Harborview Medical Center, University of Washington Mailstop 359766 325 Ninth Ave, Seattle WA 98104-2499 USA [email protected] Sherry Chou, MD, MMSc Department of Neurology, Brigham and Women’s Hospital 75 Francis Street, Boston MA 02115 USA [email protected] Jan Claassen, MD, PhD, FNCS Assistant Professor of Neurology and Neurosurgery Head of Neurocritical Care and Medical Director of the Neurological Intensive Care Unit Columbia University College of Physicians & Surgeons 177 Fort Washington Avenue, Milstein 8 Center room 300, New York, NY 10032 USA [email protected]
Marek Czosnyka, PhD Department of Neurosurgery University of Cambridge, Addenbrooke’s Hospital, Box 167 Cambridge, CB20QQ United Kingdom [email protected] Michael De Georgia, MD Professor of Neurology Director, Neurocritical Care Center Co-Director, Cerebrovascular Center University Hospital Case Medical Center Case Western Reserve University School of Medicine 11100 Euclid Avenue Cleveland, Ohio 44106 [email protected] Anthony Figaji, MD, PhD Head of Pediatric Neurosurgery University of Cape Town 617 Institute for Child Health Red Cross Children’s Hospital Rondebosch, 7700 Cape Town, South Africa [email protected] Jennifer Fugate, DO Department of Neurology, Mayo Clinic, 200 First Street SW Rochester, MN 55905 [email protected] Raimund Helbok, MD Department of Neurology, Neurocritical Care Unit Innsbruck Medical University, Anichstr.35, 6020 Innsbruck, Austria [email protected] David Horowitz, MD Associate Chief Medical Officer University of Pennsylvania Health System, 3701 Market Street Philadelphia, PA, 19104 USA [email protected] Peter Hutchinson, MD Professor of Neurosurgery NIHR Research Professor Department of Clinical Neurosciences University of Cambridge
123
Neurocrit Care
Box 167 Addenbrooke’s Hospital Cambridge CB2 2QQ United Kingdom [email protected] Monisha Kumar, MD Department of Neurology Perelman School of Medicine, University of Pennsylvania, 3 West Gates 3400 Spruce Street Philadelphia, PA, 19104 USA [email protected] Molly McNett, RN, PhD Director, Nursing Research The MetroHealth System 2500 MetroHealth Drive, Cleveland, OH 44109 USA [email protected] Chad Miller, MD Division of Cerebrovascular Diseases and Neurocritical Care The Ohio State University 395 W. 12th Ave, 7th Floor Columbus, OH 43210 [email protected] Andrew Naidech, MD, MSPH Department of Neurology Northwestern University Feinberg SOM 710 N Lake Shore Drive, 11th floor Chicago, IL 60611 [email protected] Mauro Oddo, MD Department of Intensive Care Medicine CHUV University Hospital, BH 08-623 Faculty of Biology and Medicine University of Lausanne 1011 Lausanne, Switzerland [email protected] DaiWai Olson, RN, PhD Associate Professor of Neurology, Neurotherapeutics and Neurosurgery University of Texas Southwestern 5323 Harry Hines Blvd. Dallas, TX 75390-8897 USA [email protected] Kristine O’Phelan M.D. Director of Neurocritical Care Associate Professor, Department of Neurology
123
University of Miami, Miller School of Medicine JMH, 1611 NW 12th Ave, Suite 405 Miami, FL, 33136 USA [email protected] Javier Provencio, MD Associate Professor of Medicine Cerebrovascular Center and Neuroinflammation Research Center Lerner College of Medicine Cleveland Clinic, 9500 Euclid Ave, NC30 Cleveland, OH 44195 USA [email protected] Corina Puppo, MD Assistant Professor, Intensive Care Unit, Hospital de Clinicas, Universidad de la Repu´blica, Montevideo Uruguay [email protected] Richard Riker, MD Critical Care Medicine Maine Medical Center, 22 Bramhall Street Portland, Maine 04102-3175 USA [email protected] Claudia Robertson, MD Department of Neurosurgery Medical Director of Center for Neurosurgical Intensive Care, Ben Taub Hospital Baylor College of Medicine, 1504 Taub Loop, Houston, TX 77030 USA [email protected] J. Michael Schmidt, PhD, MSc Director of Neuro-ICU Monitoring and Informatics Columbia University College of Physicians and Surgeons Milstein Hospital 8 Garden South, Suite 331 177 Fort Washington Avenue, New York, NY 10032 USA [email protected] Fabio Taccone, MD Department of Intensive Care, Laboratoire de Recherche Experimentale Erasme Hospital, Route de Lennik, 808
Neurocrit Care
1070 Brussels Belgium [email protected] 17.
References 1. Chesnut RM, Temkin N, Carney N, et al. A trial of intracranialpressure monitoring in traumatic brain injury. N Engl J Med. 2012;367(26):2471–81. 2. Carlson AP, Yonas H. Portable head computed tomography scanner–technology and applications: experience with 3421 scans. J Neuroimaging. 2012;22(4):408–15. 3. Peace K, Wilensky EM, Frangos S, MacMurtrie E, Shields E, Hujcs M, Levine J, Kofke A, Yang W, Le Roux PD. The use of a portable head CT scanner in the intensive care unit. J Neurosci Nurs. 2010;42(2):109–16. 4. Le Roux P. Intracranial pressure after the BEST TRIP trial: a call for more monitoring. Curr Opin Crit Care. 2014;20(2):141–7. 5. Nangunoori R, Maloney-Wilensky E, Stiefel M, et al. Brain tissue oxygen-based therapy and outcome after severe traumatic brain injury: a systematic literature review. Neurocrit Care. 2012; 17(1):131–8. 6. Sala N, Suys T, Zerlauth JB, Bouzat P, Messerer M, Bloch J, Levivier M, Magistretti PJ, Meuli R, Oddo M. Cerebral extracellular lactate increase is predominantly nonischemic in patients with severe traumatic brain injury. J Cereb Blood Flow Metab. 2013;33(11):1815–22. 7. Aries MJ, Czosnyka M, Budohoski KP, Steiner LA, Lavinio A, Kolias AG, Hutchinson PJ, Brady KM, Menon DK, Pickard JD, Smielewski P. Continuous determination of optimal cerebral perfusion pressure in traumatic brain injury. Crit Care Med. 2012;40(8):2456–63. 8. Sivaganesan A, Manley GT, Huang MC. Informatics for neurocritical care: challenges and opportunities. Neurocrit Care. 2014; 20(1):132–41. 9. Hemphill JC, Andrews P, De Georgia M. Multimodal monitoring and neurocritical care bioinformatics. Nat Rev Neurol. 2011; 7(8):451–60. 10. http://www.researchandmarkets.com/research/kdnxn2/brain_moni toring. 11. Li C, Shutter L, Wu PM, Ahn CH, Narayan R. Potential of a simple lab-on-a-tube for point-of-care measurements of multiple analytes. Lab Chip. 2010;10:1476–9. 12. Li C, Wu PM, Jung W, Ahn CH, Shutter L, Narayan R. A novel lab-on-a-tube for multimodality neuromonitoring of patients with traumatic brain injury (TBI). Lab Chip. 2009;9:1988–90. 13. Li C, Wu PM, Hartings JA, Wu Z, Cheyuo C, Wang P, LeDoux D, Shutter LA, Ramaswamy BR, Ahn CH, Narayan RK. Micromachined lab-on-a-tube sensors for simultaneous brain temperature and cerebral blood flow measurements. Biomed Microdevices. 2012;14(4):759–68. 14. Keller E, Froehlich J, Muroi C, Sikorski C, Muser M. Neuromonitoring in intensive care: a new brain tissue probe for combined monitoring of intracranial pressure (ICP) cerebral blood flow (CBF) and oxygenation. Acta Neurochir Suppl. 2011;110(Pt 2):217–20. 15. Rosenthal G, Furmanov A, Itshayek E, Shoshan Y, Singh V. Assessment of a noninvasive cerebral oxygenation monitor in patients with severe traumatic brain injury. J Neurosurg. 2014;120(4):901–7. 16. Kim MN, Durduran T, Frangos S, Edlow BL, Buckley EM, Moss HE, Zhou C, Yu G, Choe R, Maloney-Wilensky E, Wolf RL, Grady MS, Greenberg JH, Levine JM, Yodh AG, Detre JA,
18.
19.
20.
21.
22.
23.
24.
25.
26. 27.
28.
29.
30.
31.
32.
Kofke WA. Noninvasive measurement of cerebral blood flow and blood oxygenation using near-infrared and diffuse correlation spectroscopies in critically brain-injured adults. Neurocrit Care. 2010;12(2):173–80. He Y, Fujii M, Inoue T, Nomura S, Maruta Y, Oka F, Shirao S, Owada Y, Kida H, Kunitsugu I, Yamakawa T, Tokiwa T, Yamakawa T, Suzuki M. Neuroprotective effects of focal brain cooling on photochemically-induced cerebral infarction in rats: analysis from a neurophysiological perspective. Brain Res. 2013;1497:53–60. Fazli S, Mehnert J, Steinbrink J, Curio G, Villringer A, Mu¨ller KR, Blankertz B. Enhanced performance by a hybrid NIRS-EEG brain computer interface. Neuroimage. 2012;59(1):519–29. Wilson JA, Shutter LA, Hartings JA. COSBID-M3: a platform for multimodal monitoring, data collection, and research in neurocritical care. Acta Neurochir Suppl. 2013;115:67–74. Hamilton DR, Sargsyan AE, Melton SL, Garcia KM, Oddo B, Kwon DS, Feiveson AH, Dulchavsky SA. Sonography for determining the optic nerve sheath diameter with increasing intracranial pressure in a porcine model. J Ultrasound Med. 2011;30(5):651–9. Cammarata G, Ristagno G, Cammarata A, Mannanici G, Denaro C, Gullo A. Ocular ultrasound to detect intracranial hypertension in trauma patients. J Trauma. 2011;71:779–81. Firsching R, Mu¨ller C, Pauli SU, Voellger B, Ro¨hl FW, BehrensBaumann W. Noninvasive assessment of intracranial pressure with venous ophthalmodynamometry. Clinical article. J Neurosurg. 2011;115(2):371–4. Querfurth HW, Lieberman P, Arms S, Mundell S, Bennett M, van Horne C. Ophthalmodynamometry for ICP prediction and pilot test on Mt. Everest. BMC Neurol. 2010;10:106. Ragauskas A, Bartusis L, Piper I, Zakelis R, Matijosaitis V, Petrikonis K, Rastenyte D. Improved diagnostic value of a TCDbased non-invasive ICP measurement method compared with the sonographic ONSD method for detecting elevated intracranial pressure. Neurol Res. 2014 (ahead of press). Chen JW, Gombart ZJ, Rogers S, Gardiner SK, Cecil S, Bullock RM. Pupillary reactivity as an early indicator of increased intracranial pressure: the introduction of the Neurological Pupil index. Surg Neurol Int. 2011;2:82. Zafar SF, Suarez JI. Automated pupillometer for monitoring the critically ill patient: a critical appraisal. J Crit Care. 2014;29(4):599–603. Gonzalez CA, Valencia JA, Mora A, Gonzalez F, Velasco B, Porras MA, Salgado J, Polo SM, Hevia-Montiel N, Cordero S, Rubinsky B. Volumetric electromagnetic phase-shift spectroscopy of brain edema and hematoma. PLoS ONE. 2013;8(5):e63223. Robertson CS, Zager EL, Narayan RK, Handly N, Sharma A, Hanley DF, Garza H, Maloney-Wilensky E, Plaum JM, Koenig CH, Johnson A, Morgan T. Clinical evaluation of a portable nearinfrared device for detection of traumatic intracranial hematomas. J Neurotrauma. 2010;27(9):1597–604. Ponce LL, Pillai S, Cruz J, Li X, Hannay HJ, Gopinath S, Robertson CS. Position of probe determines prognostic information of brain tissue pO2 in severe traumatic brain injury. Neurosurgery. 2012;70(6):1492–502. Swanson E, Mascitelli J, Stiefel M, MacMurtrie E, Levine J, Kofke WA, Yang W, Le Roux P. The effect of patient transport on brain oxygen in comatose patients. Neurosurgery. 2010; 66:925–32. Peace K, Maloney E, Frangos S, Shields E, Hujcs M, Levine J, Kofke A, Yang W, Le Roux P. Portable head CT scan and its effect on intracranial pressure, cerebral perfusion pressure and brain oxygen. J Neurosurg. 2011;114(5):1479–84. Norbash A, Klein LW, Goldstein J, Haines D, Balter S, Fairobent L, Miller DL, Multispecialty Occupational Health Group. The neurointerventional procedure room of the future: predicting
123
Neurocrit Care
33.
34.
35.
36.
37.
38.
39.
likely innovations in design and function. J Neurointerv Surg. 2011;3(3):266–71. Lee J, Scott DJ, Villarroel M, et al. Open-access MIMIC-II database for intensive care research. Conf Proc IEEE Eng Med Biol Soc. 2011;2011:8315–8. Oddo M, Levine J, Frangos S, Maloney-Wilensky E, Carrera E, Daniel R, Magistretti PJ, Le Roux P. Brain lactate metabolism in humans with subarachnoid haemorrhage. Stroke. 2012;43(5):1418– 21. Lazaridis C, Smielewski P, Steiner LA, Brady KM, Hutchinson P, Pickard JD, Czosnyka M. Optimal cerebral perfusion pressure: are we ready for it? Neurol Res. 2013;35(2):138–48. Hu X, Xu P, Asgari S, Vespa P, Bergsneider M. Forecasting ICP elevation based on prescient changes of intracranial pressure waveform morphology. IEEE Trans Biomed Eng. 2010;57(5):1070–8. Gu¨iza F, Depreitere B, Piper I, Van den Berghe G, Meyfroidt G. Novel methods to predict increased intracranial pressure during intensive care and long-term neurologic outcome after traumatic brain injury: development and validation in a multicenter dataset. Crit Care Med. 2013;41(2):554–64. Narotam PK, Morrison JF, Schmidt MD, Nathoo N. Physiological complexity of acute traumatic brain injury in patients treated with a brain oxygen protocol: utility of symbolic regression in predictive modeling of a dynamical system. J Neurotrauma. 2014; 31(7):630–41. Pignolo L, Riganello F, Dolce G, Sannita WG. Ambient intelligence for monitoring and research in clinical neurophysiology
123
40.
41. 42.
43.
44. 45.
46.
and medicine: the MIMERICA* project and prototype. Clin EEG Neurosci. 2013;44(2):144–9. Ospina-Tascon GA, Buchele GL, Vincent JL. Multicenter, randomized, controlled trials evaluating mortality in intensive care: doomed to fail? Crit Care Med. 2008;36:1311–22. Ioannidis JPA. Contradicted and initially stronger effects in highly cited clinical research. JAMA. 2005;294:218–28. Deans KJ, Minneci PC, Suffredini AF, Danner RL, Hoffman WD, Ciu X, Klein HG, Schechter AN, Banks SM, Eichacker PQ, Natanson C. Randomization in clinical trials of titrated therapies: unintended consequences of using fixed treatment protocols. Crit Care Med. 2007;35(6):1509–16. Robertson CS, Valadka AB, Hannay HJ, Contant CF, Gopinath SP, Cormio M, Uzura M, Grossman RG. Prevention of secondary ischemic insults after severe head injury. Crit Care Med. 1999;27(10):2086–95. Brain Tissue Oxygen Monitoring in Traumatic Brain Injury (TBI) (BOOST 2). http://clinicaltrials.gov/ct2/show/NCT00974259. Diaz-Arrastia R, Le Roux P. In: Proceedings of the 32nd Annual Symposium of the National Neurotrauma Society, San Francisco, CA, 2014. Maas AI, Menon DK, Lingsma HF, Pineda JA, Sandel ME, Manley GT. Re-orientation of clinical research in traumatic brain injury: report of an international workshop on comparative effectiveness research. J Neurotrauma. 2012;29(1):32–46.
REVIEW ARTICLE
The International Multi-disciplinary Consensus Conference on Multimodality Monitoring: Future Directions and Emerging Technologies Paul Vespa • David Menon • Peter Le Roux • and the Participants in the International Multi-disciplinary Consensus Conference on Multimodality Monitoring
Ó Springer Science+Business Media New York 2014
Abstract Neuromonitoring has evolved rapidly in recent years and there now are many new monitors that have revealed a great deal about the ongoing pathophysiology of brain injury and coma. Further evolution will include the consolidation of multi-modality monitoring (MMM), the development of next-generation informatics tools to identify complex physiologic events and decision support tools to permit targeted individualized care. In this review, we examine future directions and emerging technologies in neuromonitoring including: (1) device development, (2) what is the current limitation(s) of MMM in its present format(s), (3) what would improve the ability of MMM to enhance neurocritical care, and (4) how do we develop evidence for use of MMM? Keywords Secondary brain injury Monitor Informatics
The Participants in the International Multi-disciplinary Consensus Conference on Multimodality Monitoring are listed in ‘‘Appendix’’ section. P. Vespa Neurocritical Care, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA D. Menon Division of Anaesthesia, University of Cambridge, Cambridge, UK P. Le Roux (&) Brain and Spine Center, Suite 370, Medical Science Building, Lankenau Medical Center, 100 East Lancaster Avenue, Wynnewood, PA 19096, USA e-mail: [email protected]
Introduction Following acute brain injury (ABI), outcome is associated with both the primary insult whether it be traumatic brain injury (TBI), ischemic stroke, or aneurysm rupture among others and with a cascade of pathophysiologic events that evolve over time, i.e., secondary brain injury (SBI). These SBIs come in many different forms but their management is central to neurocritical care. This management is dependent, in large part on neuromonitoring. Traditionally, we have relied upon the clinical neurological examination to be our main neurological monitor and despite advances in monitoring devices it will always play a fundamental role in neurocritical care decisionmaking. Recent advances have seen the development of ‘‘objective scales’’ that permit serial assessment of consciousness, pain, sedation, and delirium among other functions to limit intra-and interobserver variability. We have tracked the clinical examination and made important decisions based on the changes in exam particularly when coupled with imaging findings. The importance of this is not to be underestimated [1] and will continue to evolve as imaging, particularly computed tomography (CT) and ultrasound (US), is brought to the bedside and used in point of care testing [2, 3]. However, in the last 20 years, we have learned that the clinical examination can frequently be nonspecific and unhelpful, may lag behind physiologic findings derived from a monitor and fails to inform substantial changes in neurologic function or final clinical outcome. Simultaneously, a substantial number of neurological monitors have been developed that provide specific information about various aspects of brain physiology, function, and structure. These specific data appear to be time sensitive, robust, informative, and deterministic or at least prognostic
123
Neurocrit Care
and have revealed a great deal about the ongoing pathophysiology of brain injury and coma. We have also learnt that there is no single ideal monitor [although we continue to strive to create one (Table 1)] and that more than one monitor should be used since the brain is a complex organ and no one single method can provide comprehensive information about the brain’s health [4], i.e., multimodality monitoring (MMM). Multimodality monitoring is compelling since the data are objective and provide discriminative dynamic information about human brain pathophysiology that can be quantified, trended, and evaluated. This concept of MMM—i.e., the simultaneous collection of data from multiple diverse sources associated with a single patient has evolved in recent years and it is safe to say that MMM is here to stay and likely will be the backbone of bedside physiologic monitoring in neurocritcial care in the foreseeable future. Accumulating evidence suggests that much of the information gained from MMM substantially augments our assessment of patients well beyond the clinical exam and can enhance outcome when used to guide patient management in a patient-specific, targeted fashion [4–7]. The current challenge is it is difficult to digest these data and the future may be less about new device development but more about data display, integration and analysis, and decision support [8, 9]. The reader is referred to the article by Schmidt et al. in this Supplement for a discussion on the emerging field of bioinformatics. What new technologies can we expect and what will the future of MMM be? This is a complex question that entails several considerations about the current capabilities, current limitations, technology development that is entangled with industry desire, commercial interests and legislative limitations, and desires about how MMM is integrated into our clinical practice that in large part depends on generating evidence that use of a monitor makes a difference. Here the question gets more complex because no monitor or combination of monitors makes a difference. Rather it is
the wise application of the data from monitoring the injured brain that can influence therapeutic decisions. We will consider the following as we discuss the future directions of neuromonitoring: (1) Devices and device development, (2) what is the current limitation(s) of MMM in its present format(s), (3) what would enhance the ability of MMM to be useful in changing clinical outcome, and (4) how do we develop evidence for use of MMM? Questions to consider when evaluating neuromonitors are listed in Table 2.
Devices and Device Development There are a wide range of devices used to monitor the brain and in 2012, the global brain monitoring devices market was valued at $1.08 billion and is expected to grow at a compound annual growth rate (CAGR) of 8.6% [10]. There are many reasons for this continued growth including: (1) technological advancements, (2) ease of operation, (3) device miniaturization, (4) rising awareness of the role of SBI not only in ABI but also in other disorders including cardiovascular diseases, sleep disorders, peri-operative care, and neurodegenerative diseases to name a few, (5) use of devices for reasons other than traditional ‘‘monitoring,’’ e.g., enhanced communication in the ‘‘locked-in syndrome’’ or a brain-computer interface (BCI), and (6) an increase in computing power. In addition, the introduction and advancement of wireless, non-invasive, and mobile devices including smart phone technology means that neuro-monitoring is no longer limited to the intensive care unit but also is used in the emergency room, preoperative and postoperative care, and during routine evaluations.
Table 2 Questions to consider when evaluating neuromonitors What is the device, i.e., what exactly does it measure Are there complimentary monitors that can be used in the same pathophysiologic process How to use it
Table 1 Features of an ‘‘ideal neuromonitor’’ Portable Provides point of care measurement High spatial resolution High temporal resolution Continuous or frequently repeatable Does not interfere with patient care Noninvasive Reliable and reproducible quantitative data
Who to use it or in who is the pathophysiologic process important Are we measuring what we think we are measuring Device accuracy, precision, sensitivity and specificity Limitations, technical problems, troubleshooting, and safety The limiting conditions in which accuracy or precision are lost Reproducibility of measurements Effects of observer bias Balance the desirable and undesirable consequences of tests or information from a monitor
Not operator dependent
Does data from a device (or of monitoring a specific pathophysiological process) make a contribution to patient care
Easy to perform; requires little training to use Suggest a cause and appropriate treatment
Deficits in knowledge and future directions Cost effectiveness and justification in clinical care
123
Neurocrit Care
Technologic advances that occur in these environments will influence critical care neuromonitoring and vice versa. Currently, there are a variety of invasive and noninvasive probes that are used for brain monitoring. In this supplement, we have explored pathophysiologic processes that are of interest to intensivists rather than individual devices. These various monitors each have a number of advantages but all have disadvantages or limitations that preclude or limit broad generalizability of use (see individual chapters in this Supplement). For the invasive monitors such as intracranial pressure (ICP), brain tissue oxygen (PbtO2), and brain microdialysis, the devices are by their nature invasive and carry the risk of intracranial bleeding and infection. The invasive devices therefore cannot be used in coagulopathic patients. In addition, they are not used in patients with mild or moderate injury. A question that remains is whether some of the devices used in severe injury may have their best role in moderate injury. The non-invasive devices such as near-infrared spectroscopy (NIRS), cEEG, and transcranial Doppler (TCD), suffer from nonspecificity and sampling restriction limitations. For example, cEEG is a powerful technique, but nonspecificity of changes as they relate to cerebral perfusion and metabolism, as well as the inability to detect important electrical events deep inside of the tissue and adjacent to brain hemorrhage, are important limitations. Better Probes and Monitors The near future (5–10 years) is likely to see the development of better probes and better monitors of currently identified processes rather than the identification of some new pathophysiologic process to evaluate. The exception to this may be the evolution of biomarkers or combinations of biomarkers. Development at present is following one or two avenues: (1) non-invasive tools that use near-infrared spectroscopy (NIRS), acoustic, or ultrasound signals among other methodologies or (2) incorporation of many monitors onto a single invasive device [11–16]. There are several monitors that are undergoing product development to enhance their capability. NIRS is one type of device that is being modified to provide information not only on brain oxygenation but also on cerebral blood flow (CBF) and metabolism [15]. The next-generation NIRS devices will be able to make noninvasive CBF measures and the use of NIRS to perform diffuse correlational spectroscopy enables measures of cortical CBF which have been validated against xenon CT CBF imaging [16]. A combined NIRS and depth EEG probe has been successfully tested in rodent models [17]. Outside of the ICU the combination of NIRS and EEG is used to enhance the BCI for neuroprosthetics [18]. Conceptually this makes sense since EEG and NIRS are sensitive to different cascades of
events that are linked to the same neural activities. cEEG techniques and software analysis programs are being modified to provide better indicators of seizures, and CBF. Depth electrode modifications are being considered that will enable the reliable detection of cortical spreading depolarizations (CSDs) [19] and seizures. Noninvasive ICP monitors are being developed and potentially could include assessment of optic nerve sheath diameter [20, 21], venous ophthalmodynamometry [22, 23], TCD analytics [24], pupillometry [25, 26], or modifications of NIRS. At present none of the non-invasive devices are able to replace their invasive counterpart and much work is still required. There are several novel diagnostic devices that may play a role in MMM in the future. One technology is called volumetric electromagnetic phase shift spectroscopy (VEPS). This device is shown in Fig. 1. This is a noninvasive device that creates a magnetic field surrounding the head, and can detect cerebral edema and hemorrhage. One could envision this as an adjunct to conventional imaging to track progressive brain edema. This device is not FDA approved yet and has only been studied to a limited extent in humans [27]. Another diagnostic device that is FDA approved is the Infrascanner. This is a handheld device that is capable of detecting intracerebral hemorrhages greater than 3.5 cc [28]. This device is envisioned to be used in a triage setting before conventional scanning, however, with further device development one could foresee it’s use in the ICU as a supplement to serial neurologic examination. The focus of this supplement has been on physiologic monitors. However, the concept of bedside imaging in the ICU being used as a monitor has already started to develop and is important to the concept of MMM. For example, probe position can influence data interpretation [29], hence a postinsertion CT scan can be very valuable in evaluating treatment effects. The use of portable CT scanners is a prime example of this [2, 3]. Importantly bringing imaging technology to the bedside can significantly decrease complications and physiologic derangements associated with patient transport and will become an important component of ICU care in the future [30, 31]. Some ICUs have CT, MRI, and PET directly adjacent to the ICU. Interventional suites that feature multimodality imaging during acute vascular interventions are now being planned and implemented [32].
Current Limitations The main limitation of multimodality monitoring, and of bedside neuromonitoring in general in neurocritical care, is the limited evidence, specifically level 1 evidence that guides how best to use the various devices, integrate them and most importantly whether the knowledge gained from them can have a positive effect on outcome. This limitation
123
Neurocrit Care Fig. 1 The VEPS brain edema online monitoring system
is discussed in much of the analysis in the selected chapters. This is not surprising given the inherent problems with creating a definitive study, including (1) the reality that disease-specific variables influence outcome to a great extent thus limiting the power of any study of goal directed treatment derived by brain monitoring to influence outcome, (2) the uncertain best treatments based on the reliable brain monitoring indicators of secondary injury, and (3) the lack of experience in using, interpreting, and utilizing goal directed therapy in neurocritical care. It is conceivable that answers may not come from randomized controlled studies of brain monitoring in a goal-directed therapy. Instead careful clinical observation may help provide greater insight into disease pathophysiology, understand mechanisms of disease, help design-targeted treatment strategies, and importantly develop new treatments. We should take a lesson from the experience of the pulmonary artery catheter studies of the past and not be anxious to ‘‘prove the monitor.’’ It is likely that we will one day be able to test these devices, but careful consideration needs to be applied and more understanding about the pathophysiology is required before we embark on such a study, i.e., it is not the monitor per se that needs study but rather how the data is used that requires study. That assumes effective therapies exist. The second main limitation is that we do not have an integrated electronic platform to present and manipulate the multiple data streams from the monitors that are in use.
123
Table 3 Developments that will enhance the role of monitoring in neurocritical care Data accuracy (+artifact rejection) Data integration and multivariate/nonlinear synthesis and analysis Data display and decision support Non-invasive options Cost effectiveness Practical solutions for the real world Industry standardisation and compatibility Precompetitive benefits for industry and societal good from industry
Most electronic health record systems in the ICU are capable of displaying tabular information and some limited graphics of 1 or 2 parameters but generally are recapitulations of the medical record. Furthermore, these systems cannot display an integrated data set of the neurologic monitors to enable a summary graphic display of the data. More importantly, these systems cannot post-process the information to permit analysis of the data using simple methods (e.g., regression analysis) or time-aligned trend analysis. Hence, the information is disparate and non-time aligned. This places limits on interpretation of the data, and limits the usability of these data to a smaller number of people who are accustomed to mentally integrate the information. This type of manual/cognitive integration is subject to bias, human error, and misinterpretation.
Neurocrit Care
Future Directions
Table 4 Challenges to neurocritical care informatics (modified from references [8, 9])
There are several important developments that will enhance the ability of MMM to be useful in changing clinical outcome (Table 3). In particular, two stand out: (1) enhanced informatics (data display, integration, and analysis), and (2) improved studies that demonstrate efficacy of the techniques, and adaptations to several of the monitors.
Data acquisition electronically as a standard in intensive care units
Informatics
Missing data due to artifact, disconnection, different time domains, etc.
Neurocritical care depends on the continuous, real-time measurement of a variety of physiologic parameters that are both systemic, e.g., cardiac function and neurospecific, e.g., ICP, PbtO2, and CBF, to identify SBIs. This data requires interpretation with non-continuous data and ordinal data including the clinical examination, laboratory analysis, and imaging, i.e., the type of data is diverse and in different formats. However, while the number of variables that can be measured has grown the ability to transform the data into meaningful therapeutic strategies remains crude in large part because we use a uni-variate reactive threshold approach for data interpretation rather than a multivariate approach that also uses trends. Consequently, next-generation MMM will include an informatics approach and improved electronic data technologies to collect and interpret the ever increasing amount of data that has become available. In addition, decision support tools will develop. Informatics is the process of acquiring, storing, and analyzing data for clinical decision-making. Ideally this also includes techniques such as decision trees and Dynamic Bayesian Networks to enhance decision support. The field of bio-informatics is rapidly expanding and over the next 5 years, we will likely see the development and implementation of several visualization and presentation interfaces in neurocritical care (perhaps specific to the field) that serve to integrate the data into a time-aligned stream of information. There are several obstacles to critical bio-informatics (Table 4) including the proprietary nature of medical devices and software and the presence of artifacts that limits central capture and storage of highdensity data. Hence, the future evolution of MMM will require collaboration between industry, intensivists, and informatics experts. Several groups are working on components that are necessary for such an integrated view [33]. This informatics approach will feature discreet data elements from many of our brain monitors, all time aligned, so that the clinician can more easily interpret the data. An example of this type of integration is shown in Figs. 2 and 3. These figures show integrated dashboards of information that feature anatomic imaging combined with longitudinal
Varying types of data (e.g., numeric, imaging, text, continuous, ordinal)
Interoperability of different monitoring devices to acquire data Standardization of global-controlled vocabularies of terminology Volume and resolution of data Regulatory aspects of data collection (e.g., HIPAA and privacy boards) Automated artifact detection and cleaning of acquired data before analysis
Integration with electronic medical records and other patient data Whether to use all data or discard selectively or empirically Real-time analysis and feedback to the bedside Clinician acceptance and use of analyzed data
streams of physiological data. The informatics displays will be designed to be configured for optimal data interpretation, with the ability to alter the settings to focus in on short-duration periods of interest and highlight important moments of altered brain physiology or clinical neurological deterioration. These displays will be achievable and will serve as a source of quality control and research. Automated analytics will be incorporated into these displays thereby providing expert diagnostic information about the state of autoregulation (PRx) or intracranial compliance (MOCAIP) or some other feature, i.e., will allow exploration of the variability of a single value and trends, interactions between systems and the emergent order of variables. In so doing management can target the optimal range of physiology for a specific individual, i.e., ‘‘personalized intervention’’ rather than use a ‘‘one size fits all’’ approach as currently is done [34, 35]. Furthermore, care will become more proactive rather than reactive (which may be too late) because of an enhanced ability to predict deleterious events [36–38]. One futuristic informatics platform is the Ambient Intelligence (AMI) system that collects information from not only the patient but also from the environment and machine interfaces over time [39]. The AMI system permits data to be collected and streamed in real time, and then semi-automatically interpreted through the use automated algorithms that can be used to process the data. In a novel public–private partnership, a consortium of academic neurocritical care centers and Draper Laboratories (Cambridge, MA) have created an initial demonstration version of the next-generation of informatics for MMM. The IMEDS group, as it is called, envisions an open source system of informatics displays that will
123
Neurocrit Care
Fig. 2 Example of informatics display of multiple time-aligned data elements from ICP, Microdialysis, and Jugular Oximetry
enable simultaneous presentation of numerous data streams, and a platform for data analysis and manipulation. Figure 4 shows the initial demonstration zero version of the IMEDS system (data courtesy of Michael Schmidt, Columbia University). The data is time aligned and plotted to show variations in ICP and CPP. Prospective Studies to Evaluate Monitoring We do need to develop more evidence how brain monitors impact clinical outcome. To that end, small, randomized studies that focus on intermediate outcomes or biomarker outcomes seem to be a reasonable approach. For example, a study of the effectiveness of a brain monitor to accurately diagnose cerebral ischemia with validation of the monitor through complimentary use of brain imaging or a biomarker of ischemia would be a reasonable step. Some validation studies have already been done, but many questions remain about the sensitivity and specificity of these measures. These questions create an opportunity to enhance our understanding of these monitors and permits time for widespread experience with these monitors, experience which is necessary before embarking on definitive studies. There is a constant clamor for a Phase III randomized clinical trial (RCT) to prove that neuromonitoring or a
123
specific neuromonitor is beneficial. However, this largely reduces scientific methodology to one step—bias avoidance and confuses statistics with science (and physiology) by equating statistical precision with scientific exactness. Hence, few RCTs in critical care have been successful [40]. Alternatively successful RCTs have been refuted by subsequent trials [41], e.g., glucose control or suffer from practice misalignment [42]. Furthermore, a neuromonitor itself cannot be the subject of an RCT. Instead different management strategies can be compared. For example, while the BEST TRIP trial, one of very few and the most recent RCT to examine neuromonitoring is titled ‘‘A trial of intracranial-pressure monitoring in traumatic brain injury’’ it is not that [1]. Instead it is a trial of two management strategies for TBI that both rely on different monitoring strategies. The value of the monitor then is confused with the care given. And that is the problem: effective management may not exist or it is applied in a population-based manner when it only exists for a subset of trial patients or its use it associated with deleterious side effects. For example, Robertson et al. [43] examined ICP and CPP-based care in a RCT. They were able to demonstrate a reduction in secondary cerebral ischemia but outcome was similar because of pulmonary complications. These trial patients were treated with a ‘‘one size fits all’’ CPP approach. Today we are beginning to recognize the
Neurocrit Care
Fig. 3 Example of MMM diagnosing delayed cerebral ischemia after subarachnoid hemorrhage
Fig. 4 IMEDS demonstration Zero informatics display for MMM
physiologic importance of individual titration of CPP and ICP targets, i.e., defining an optimal CPP for each patient [7, 35]. This is more consistent with how we practice critical care since in the ICU we make decisions based on universal principles and practical wisdom that are customized for a particular patient. One RCT in which
neuromonitoring plays a role, BOOST-2 [44] has attempted to address this. BOOST-2 is a phase II TBI trial in which management strategies based on ICP and CPP are compared with those based on ICP, CPP, and PbtO2. This is a complex process of care trial and preliminary results demonstrate feasibility, safety, attainment of the primary endpoint, i.e., physiologic efficacy and enhanced outcome in those patients who have added PbtO2 based care [45]. Perhaps more important than the results of the trial is the information acquired to plan a Phase III RCT. The vast majority of neuroprotective trials, i.e., single drug trials have failed in ABI. Hence, it becomes important to: (1) understand what is happening in the patient, (2) think of care strategies rather than a single agent, and (3) develop personalized targeted approaches. To do this hightech monitoring and bio-informatics are necessary to better understand and essential to targeted therapy. The best study of neuromonitoring then may depend on registries, observational cohorts, or comparative effectiveness research [46]. In this context, the study of neuromonitoring has the obvious implication: examination of how the monitor performs but perhaps more importantly it can help identify novel therapeutic strategies. For that reason, it is an
123
Neurocrit Care Table 5 Requirements for multimodality monitoring Continuous monitoring Not to miss clinically significant events The frequency of monitoring needs to be higher than the duration of the events to be detected Comprehensive All of the necessary data for a particular monitoring goal needs to be collected simultaneously, time synchronized, and displayed in an integrated fashion Communicative Plot time synchronized trends on a single display Integrate waveforms, images, and other formats Statistical relationships
exciting and promising time to be practicing neurocritical care.
Conclusion The goal of neuromonitoring in intensive care is to enable the detection of harmful physiological events before they cause irreversible damage to the brain. Multimodality monitoring is inherent to the way we practice neurocritical care (Table 5). At its simplest level repeated neurologic exams and measurement of blood pressure and systemic O2 saturation for the purposes of making patient care decisions, is ‘‘Multi-Modality Monitoring.’’ At the other end of the spectrum is the integration of this information with imaging data and continuous neurospecific physiologic data obtained from a variety of diverse sources. The real questions that remain to be answered are: (1) are you getting the information you want (and need), (2) what monitoring tools can give you this information, and (3) is integrating information from multiple monitors better than using a single threshold for clinical decision making?
Appendix: Participants in the International Multidisciplinary Consensus Conference on Multimodality Monitoring Peter Le Roux, MD, FACS, Brain and Spine Center, Suite 370, Medical Science Building, Lankenau Medical Center, 100 East Lancaster Avenue, Wynnewood, PA 19096, USA. Tel: +1 610 642 3005; Fax: 610 642 3057 [email protected]
123
David K Menon MD PhD FRCP FRCA FFICM FMedSci Head, Division of Anaesthesia, University of Cambridge Consultant, Neurosciences Critical Care Unit Box 93, Addenbrooke’s Hospital, Cambridge CB2 2QQ, UK [email protected] Paul Vespa, MD, FCCM, FAAN, FNCS Professor of Neurology and Neurosurgery Director of Neurocritical Care David Geffen School of Medicine at UCLA Los Angeles, CA 90095 USA [email protected] Giuseppe Citerio, Director NeuroIntensive Care Unit, Department of Anesthesia and Critical Care Ospedale San Gerardo, Monza. Via Pergolesi 33, Monza 20900, Italy [email protected] Mary Kay Bader RN, MSN, CCNS, FAHA, FNCS Neuro/Critical Care CNS Mission Hospital Mission Viejo CA 92691, USA [email protected] Gretchen M. Brophy, PharmD, BCPS, FCCP, FCCM Professor of Pharmacotherapy & Outcomes Science and Neurosurgery Virginia Commonwealth University Medical College of Virginia Campus 410 N. 12th Street Richmond, Virginia 23298-0533 USA [email protected] Michael N. Diringer, MD Professor of Neurology, Neurosurgery & Anesthesiology Chief, Neurocritical Care Section Washington University Dept. of Neurology, Campus Box 8111 660 S Euclid Ave St Louis, MO 63110 USA [email protected] Nino Stocchetti, MD Professor of Anesthesia and Intensive Care Department of physiopathology and transplant, Milan University Director Neuro ICU Fondazione IRCCS Ca` Granda Ospedale Maggiore Policlinico Via F Sforza, 35 20122 Milan Italy e-mail [email protected]
Neurocrit Care
Walter Videtta, MD ICU Neurocritical Care Hospital Nacional ‘Prof. a. Posadas’ El Palomar - Pcia. de Buenos Aires Argentina [email protected] Rocco Armonda, MD Department of Neurosurgery MedStar Georgetown University Hospital Medstar Health, 3800 Reservoir Road NW Washington DC 20007 USA [email protected] Neeraj Badjatia, MD Department of Neurology University of Maryland Medical Center, 22 S Greene St Baltimore, MD, 21201 USA [email protected] Julian Boesel, MD Department of Neurology Ruprect-Karls University Hospital Heidelberg, Im Neuenheimer Feld 400, D-69120 Heidelberg, Germany [email protected] Randal Chesnut, MD, FCCM, FACS Harborview Medical Center, University of Washington Mailstop 359766 325 Ninth Ave, Seattle WA 98104-2499 USA [email protected] Sherry Chou, MD, MMSc Department of Neurology, Brigham and Women’s Hospital 75 Francis Street, Boston MA 02115 USA [email protected] Jan Claassen, MD, PhD, FNCS Assistant Professor of Neurology and Neurosurgery Head of Neurocritical Care and Medical Director of the Neurological Intensive Care Unit Columbia University College of Physicians & Surgeons 177 Fort Washington Avenue, Milstein 8 Center room 300, New York, NY 10032 USA [email protected]
Marek Czosnyka, PhD Department of Neurosurgery University of Cambridge, Addenbrooke’s Hospital, Box 167 Cambridge, CB20QQ United Kingdom [email protected] Michael De Georgia, MD Professor of Neurology Director, Neurocritical Care Center Co-Director, Cerebrovascular Center University Hospital Case Medical Center Case Western Reserve University School of Medicine 11100 Euclid Avenue Cleveland, Ohio 44106 [email protected] Anthony Figaji, MD, PhD Head of Pediatric Neurosurgery University of Cape Town 617 Institute for Child Health Red Cross Children’s Hospital Rondebosch, 7700 Cape Town, South Africa [email protected] Jennifer Fugate, DO Department of Neurology, Mayo Clinic, 200 First Street SW Rochester, MN 55905 [email protected] Raimund Helbok, MD Department of Neurology, Neurocritical Care Unit Innsbruck Medical University, Anichstr.35, 6020 Innsbruck, Austria [email protected] David Horowitz, MD Associate Chief Medical Officer University of Pennsylvania Health System, 3701 Market Street Philadelphia, PA, 19104 USA [email protected] Peter Hutchinson, MD Professor of Neurosurgery NIHR Research Professor Department of Clinical Neurosciences University of Cambridge
123
Neurocrit Care
Box 167 Addenbrooke’s Hospital Cambridge CB2 2QQ United Kingdom [email protected] Monisha Kumar, MD Department of Neurology Perelman School of Medicine, University of Pennsylvania, 3 West Gates 3400 Spruce Street Philadelphia, PA, 19104 USA [email protected] Molly McNett, RN, PhD Director, Nursing Research The MetroHealth System 2500 MetroHealth Drive, Cleveland, OH 44109 USA [email protected] Chad Miller, MD Division of Cerebrovascular Diseases and Neurocritical Care The Ohio State University 395 W. 12th Ave, 7th Floor Columbus, OH 43210 [email protected] Andrew Naidech, MD, MSPH Department of Neurology Northwestern University Feinberg SOM 710 N Lake Shore Drive, 11th floor Chicago, IL 60611 [email protected] Mauro Oddo, MD Department of Intensive Care Medicine CHUV University Hospital, BH 08-623 Faculty of Biology and Medicine University of Lausanne 1011 Lausanne, Switzerland [email protected] DaiWai Olson, RN, PhD Associate Professor of Neurology, Neurotherapeutics and Neurosurgery University of Texas Southwestern 5323 Harry Hines Blvd. Dallas, TX 75390-8897 USA [email protected] Kristine O’Phelan M.D. Director of Neurocritical Care Associate Professor, Department of Neurology
123
University of Miami, Miller School of Medicine JMH, 1611 NW 12th Ave, Suite 405 Miami, FL, 33136 USA [email protected] Javier Provencio, MD Associate Professor of Medicine Cerebrovascular Center and Neuroinflammation Research Center Lerner College of Medicine Cleveland Clinic, 9500 Euclid Ave, NC30 Cleveland, OH 44195 USA [email protected] Corina Puppo, MD Assistant Professor, Intensive Care Unit, Hospital de Clinicas, Universidad de la Repu´blica, Montevideo Uruguay [email protected] Richard Riker, MD Critical Care Medicine Maine Medical Center, 22 Bramhall Street Portland, Maine 04102-3175 USA [email protected] Claudia Robertson, MD Department of Neurosurgery Medical Director of Center for Neurosurgical Intensive Care, Ben Taub Hospital Baylor College of Medicine, 1504 Taub Loop, Houston, TX 77030 USA [email protected] J. Michael Schmidt, PhD, MSc Director of Neuro-ICU Monitoring and Informatics Columbia University College of Physicians and Surgeons Milstein Hospital 8 Garden South, Suite 331 177 Fort Washington Avenue, New York, NY 10032 USA [email protected] Fabio Taccone, MD Department of Intensive Care, Laboratoire de Recherche Experimentale Erasme Hospital, Route de Lennik, 808
Neurocrit Care
1070 Brussels Belgium [email protected] 17.
References 1. Chesnut RM, Temkin N, Carney N, et al. A trial of intracranialpressure monitoring in traumatic brain injury. N Engl J Med. 2012;367(26):2471–81. 2. Carlson AP, Yonas H. Portable head computed tomography scanner–technology and applications: experience with 3421 scans. J Neuroimaging. 2012;22(4):408–15. 3. Peace K, Wilensky EM, Frangos S, MacMurtrie E, Shields E, Hujcs M, Levine J, Kofke A, Yang W, Le Roux PD. The use of a portable head CT scanner in the intensive care unit. J Neurosci Nurs. 2010;42(2):109–16. 4. Le Roux P. Intracranial pressure after the BEST TRIP trial: a call for more monitoring. Curr Opin Crit Care. 2014;20(2):141–7. 5. Nangunoori R, Maloney-Wilensky E, Stiefel M, et al. Brain tissue oxygen-based therapy and outcome after severe traumatic brain injury: a systematic literature review. Neurocrit Care. 2012; 17(1):131–8. 6. Sala N, Suys T, Zerlauth JB, Bouzat P, Messerer M, Bloch J, Levivier M, Magistretti PJ, Meuli R, Oddo M. Cerebral extracellular lactate increase is predominantly nonischemic in patients with severe traumatic brain injury. J Cereb Blood Flow Metab. 2013;33(11):1815–22. 7. Aries MJ, Czosnyka M, Budohoski KP, Steiner LA, Lavinio A, Kolias AG, Hutchinson PJ, Brady KM, Menon DK, Pickard JD, Smielewski P. Continuous determination of optimal cerebral perfusion pressure in traumatic brain injury. Crit Care Med. 2012;40(8):2456–63. 8. Sivaganesan A, Manley GT, Huang MC. Informatics for neurocritical care: challenges and opportunities. Neurocrit Care. 2014; 20(1):132–41. 9. Hemphill JC, Andrews P, De Georgia M. Multimodal monitoring and neurocritical care bioinformatics. Nat Rev Neurol. 2011; 7(8):451–60. 10. http://www.researchandmarkets.com/research/kdnxn2/brain_moni toring. 11. Li C, Shutter L, Wu PM, Ahn CH, Narayan R. Potential of a simple lab-on-a-tube for point-of-care measurements of multiple analytes. Lab Chip. 2010;10:1476–9. 12. Li C, Wu PM, Jung W, Ahn CH, Shutter L, Narayan R. A novel lab-on-a-tube for multimodality neuromonitoring of patients with traumatic brain injury (TBI). Lab Chip. 2009;9:1988–90. 13. Li C, Wu PM, Hartings JA, Wu Z, Cheyuo C, Wang P, LeDoux D, Shutter LA, Ramaswamy BR, Ahn CH, Narayan RK. Micromachined lab-on-a-tube sensors for simultaneous brain temperature and cerebral blood flow measurements. Biomed Microdevices. 2012;14(4):759–68. 14. Keller E, Froehlich J, Muroi C, Sikorski C, Muser M. Neuromonitoring in intensive care: a new brain tissue probe for combined monitoring of intracranial pressure (ICP) cerebral blood flow (CBF) and oxygenation. Acta Neurochir Suppl. 2011;110(Pt 2):217–20. 15. Rosenthal G, Furmanov A, Itshayek E, Shoshan Y, Singh V. Assessment of a noninvasive cerebral oxygenation monitor in patients with severe traumatic brain injury. J Neurosurg. 2014;120(4):901–7. 16. Kim MN, Durduran T, Frangos S, Edlow BL, Buckley EM, Moss HE, Zhou C, Yu G, Choe R, Maloney-Wilensky E, Wolf RL, Grady MS, Greenberg JH, Levine JM, Yodh AG, Detre JA,
18.
19.
20.
21.
22.
23.
24.
25.
26. 27.
28.
29.
30.
31.
32.
Kofke WA. Noninvasive measurement of cerebral blood flow and blood oxygenation using near-infrared and diffuse correlation spectroscopies in critically brain-injured adults. Neurocrit Care. 2010;12(2):173–80. He Y, Fujii M, Inoue T, Nomura S, Maruta Y, Oka F, Shirao S, Owada Y, Kida H, Kunitsugu I, Yamakawa T, Tokiwa T, Yamakawa T, Suzuki M. Neuroprotective effects of focal brain cooling on photochemically-induced cerebral infarction in rats: analysis from a neurophysiological perspective. Brain Res. 2013;1497:53–60. Fazli S, Mehnert J, Steinbrink J, Curio G, Villringer A, Mu¨ller KR, Blankertz B. Enhanced performance by a hybrid NIRS-EEG brain computer interface. Neuroimage. 2012;59(1):519–29. Wilson JA, Shutter LA, Hartings JA. COSBID-M3: a platform for multimodal monitoring, data collection, and research in neurocritical care. Acta Neurochir Suppl. 2013;115:67–74. Hamilton DR, Sargsyan AE, Melton SL, Garcia KM, Oddo B, Kwon DS, Feiveson AH, Dulchavsky SA. Sonography for determining the optic nerve sheath diameter with increasing intracranial pressure in a porcine model. J Ultrasound Med. 2011;30(5):651–9. Cammarata G, Ristagno G, Cammarata A, Mannanici G, Denaro C, Gullo A. Ocular ultrasound to detect intracranial hypertension in trauma patients. J Trauma. 2011;71:779–81. Firsching R, Mu¨ller C, Pauli SU, Voellger B, Ro¨hl FW, BehrensBaumann W. Noninvasive assessment of intracranial pressure with venous ophthalmodynamometry. Clinical article. J Neurosurg. 2011;115(2):371–4. Querfurth HW, Lieberman P, Arms S, Mundell S, Bennett M, van Horne C. Ophthalmodynamometry for ICP prediction and pilot test on Mt. Everest. BMC Neurol. 2010;10:106. Ragauskas A, Bartusis L, Piper I, Zakelis R, Matijosaitis V, Petrikonis K, Rastenyte D. Improved diagnostic value of a TCDbased non-invasive ICP measurement method compared with the sonographic ONSD method for detecting elevated intracranial pressure. Neurol Res. 2014 (ahead of press). Chen JW, Gombart ZJ, Rogers S, Gardiner SK, Cecil S, Bullock RM. Pupillary reactivity as an early indicator of increased intracranial pressure: the introduction of the Neurological Pupil index. Surg Neurol Int. 2011;2:82. Zafar SF, Suarez JI. Automated pupillometer for monitoring the critically ill patient: a critical appraisal. J Crit Care. 2014;29(4):599–603. Gonzalez CA, Valencia JA, Mora A, Gonzalez F, Velasco B, Porras MA, Salgado J, Polo SM, Hevia-Montiel N, Cordero S, Rubinsky B. Volumetric electromagnetic phase-shift spectroscopy of brain edema and hematoma. PLoS ONE. 2013;8(5):e63223. Robertson CS, Zager EL, Narayan RK, Handly N, Sharma A, Hanley DF, Garza H, Maloney-Wilensky E, Plaum JM, Koenig CH, Johnson A, Morgan T. Clinical evaluation of a portable nearinfrared device for detection of traumatic intracranial hematomas. J Neurotrauma. 2010;27(9):1597–604. Ponce LL, Pillai S, Cruz J, Li X, Hannay HJ, Gopinath S, Robertson CS. Position of probe determines prognostic information of brain tissue pO2 in severe traumatic brain injury. Neurosurgery. 2012;70(6):1492–502. Swanson E, Mascitelli J, Stiefel M, MacMurtrie E, Levine J, Kofke WA, Yang W, Le Roux P. The effect of patient transport on brain oxygen in comatose patients. Neurosurgery. 2010; 66:925–32. Peace K, Maloney E, Frangos S, Shields E, Hujcs M, Levine J, Kofke A, Yang W, Le Roux P. Portable head CT scan and its effect on intracranial pressure, cerebral perfusion pressure and brain oxygen. J Neurosurg. 2011;114(5):1479–84. Norbash A, Klein LW, Goldstein J, Haines D, Balter S, Fairobent L, Miller DL, Multispecialty Occupational Health Group. The neurointerventional procedure room of the future: predicting
123
Neurocrit Care
33.
34.
35.
36.
37.
38.
39.
likely innovations in design and function. J Neurointerv Surg. 2011;3(3):266–71. Lee J, Scott DJ, Villarroel M, et al. Open-access MIMIC-II database for intensive care research. Conf Proc IEEE Eng Med Biol Soc. 2011;2011:8315–8. Oddo M, Levine J, Frangos S, Maloney-Wilensky E, Carrera E, Daniel R, Magistretti PJ, Le Roux P. Brain lactate metabolism in humans with subarachnoid haemorrhage. Stroke. 2012;43(5):1418– 21. Lazaridis C, Smielewski P, Steiner LA, Brady KM, Hutchinson P, Pickard JD, Czosnyka M. Optimal cerebral perfusion pressure: are we ready for it? Neurol Res. 2013;35(2):138–48. Hu X, Xu P, Asgari S, Vespa P, Bergsneider M. Forecasting ICP elevation based on prescient changes of intracranial pressure waveform morphology. IEEE Trans Biomed Eng. 2010;57(5):1070–8. Gu¨iza F, Depreitere B, Piper I, Van den Berghe G, Meyfroidt G. Novel methods to predict increased intracranial pressure during intensive care and long-term neurologic outcome after traumatic brain injury: development and validation in a multicenter dataset. Crit Care Med. 2013;41(2):554–64. Narotam PK, Morrison JF, Schmidt MD, Nathoo N. Physiological complexity of acute traumatic brain injury in patients treated with a brain oxygen protocol: utility of symbolic regression in predictive modeling of a dynamical system. J Neurotrauma. 2014; 31(7):630–41. Pignolo L, Riganello F, Dolce G, Sannita WG. Ambient intelligence for monitoring and research in clinical neurophysiology
123
40.
41. 42.
43.
44. 45.
46.
and medicine: the MIMERICA* project and prototype. Clin EEG Neurosci. 2013;44(2):144–9. Ospina-Tascon GA, Buchele GL, Vincent JL. Multicenter, randomized, controlled trials evaluating mortality in intensive care: doomed to fail? Crit Care Med. 2008;36:1311–22. Ioannidis JPA. Contradicted and initially stronger effects in highly cited clinical research. JAMA. 2005;294:218–28. Deans KJ, Minneci PC, Suffredini AF, Danner RL, Hoffman WD, Ciu X, Klein HG, Schechter AN, Banks SM, Eichacker PQ, Natanson C. Randomization in clinical trials of titrated therapies: unintended consequences of using fixed treatment protocols. Crit Care Med. 2007;35(6):1509–16. Robertson CS, Valadka AB, Hannay HJ, Contant CF, Gopinath SP, Cormio M, Uzura M, Grossman RG. Prevention of secondary ischemic insults after severe head injury. Crit Care Med. 1999;27(10):2086–95. Brain Tissue Oxygen Monitoring in Traumatic Brain Injury (TBI) (BOOST 2). http://clinicaltrials.gov/ct2/show/NCT00974259. Diaz-Arrastia R, Le Roux P. In: Proceedings of the 32nd Annual Symposium of the National Neurotrauma Society, San Francisco, CA, 2014. Maas AI, Menon DK, Lingsma HF, Pineda JA, Sandel ME, Manley GT. Re-orientation of clinical research in traumatic brain injury: report of an international workshop on comparative effectiveness research. J Neurotrauma. 2012;29(1):32–46.
