Multi-modality Neuro-Monitoring: Conventional Clinical Trial Design
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REVIEW ARTICLE
Multi-modality Neuro-Monitoring: Conventional Clinical Trial Design Alexandros L. Georgiadis1 • Yuko Y. Palesch2 • David Zygun3 • J. Claude Hemphill III4 • Claudia S. Robertson5 • Peter D. Leroux6 • Jose I. Suarez1 • for the Second Neurocritical Care Research Conference Investigators
Published online: 2 April 2015 Springer Science+Business Media New York 2015
Abstract Multi-modal monitoring has become an integral part of neurointensive care. However, our approach is at this time neither standardized nor backed by data from randomized controlled trials. The goal of the second Neurocritical Care Research Conference was to discuss research priorities in multi-modal monitoring, what research tools are available, as well as the latest advances in clinical trial design. This section of the meeting was focused on how such a trial should be designed so as to maximize yield and avoid mistakes of the past. Keywords Neurocritical care Randomized controlled trials Intracranial pressure Multi-modal monitoring
Introduction The Second Neurocritical Care Research Conference was designed to cover recent advances to understand application of key technologies in neurocritical care and possible avenues for study designs to validate them. One of the sessions was dedicated to discussions related to conventional clinical trial design of multimodality monitoring. We present in this manuscript the summary statements of the lectures given. The following lectures were presented: (1) Sample size calculations (presented by Yuko Y Palesch, Ph.D.); (2) Can we demonstrate the efficacy of monitoring? (presented by David Zygun, M.D.); (3) Efficacy endpoints (presented by J Claude Hemphill III, M.D., Ph.D.); and (4) Patient selection and recruitment (presented by Claudia S. Robertson, M.D.).
The Second Neurocritical Care Research Conference Investigators are listed in ‘‘Appendix’’. & Alexandros L. Georgiadis [email protected]; [email protected] 1
Division of Neurocritical Care and Vascular Neurology, Department of Neurology, Baylor College of Medicine, 6501 Fannin Street, MS: NB320, Houston, TX 77030, USA
2
Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA
3
Departments of Critical Care Medicine, Clinical Neurosciences and Community Health Science, University of Calgary, Calgary, AB, Canada
4
Department of Neurology, UCSF School of Medicine, San Francisco, CA, USA
5
Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
6
Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, USA
Sample Size Calculations Trials can fail because the proposed intervention does not work, but in most cases, multiple factors combine to result in a false negative trial. These factors are often related to study design and/or trial execution. Two key elements of study design that influence sample size calculation are the effect size and control group (nuisance) parameters. Anticipating too large an effect of the proposed intervention and making incorrec
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