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Foundations for evidence-based intraoperative neurophysiological monitoring

Abstract:
In this review, we recommend means to enhance the evidence-base for intraoperative neurophysiological monitoring (IONM). We address two preliminary issues: (1) whether IONM should be evaluated as a diagnostic test or an intervention, and (2) the state of the evidence for IONM (as presented in systematic reviews, for example). Three reasons may be suggested to evaluate at least some IONM applications as interventions (or as part of an "interventional cascade"). First, practical barriers limit our ability to measure IONM diagnostic accuracy. Second, IONM results are designed to be correlated with interventions during surgery. Third, IONM should improve patient outcomes when IONM-directed intervention alters the course of surgery. Observational evidence for IONM is growing yet more is required to understand the conditions under which IONM, in its variety of settings, can benefit patients. A multi-center observational cohort study would represent an important initial compromise between the pragmatic difficulties with conducting controlled trials in IONM and the Evidence-Based Medicine (EBM) view that large scale randomized trials are required. Such a cohort study would improve the evidence base and (if justified) provide the rationale for controlled trials.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.clinph.2015.05.033

Authors

More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Primary Care Health Sciences
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Surgical Sciences
Role:
Author


Publisher:
Elsevier
Journal:
Clinical Neurophysiology More from this journal
Volume:
127
Issue:
1
Pages:
81-90
Publication date:
2015-07-23
Acceptance date:
2015-05-08
DOI:
ISSN:
1388-2457
Pmid:
26268581


Language:
English
Keywords:
Pubs id:
pubs:539781
UUID:
uuid:81003921-52b2-4bf3-98a5-301298bb76e6
Local pid:
pubs:539781
Source identifiers:
539781
Deposit date:
2016-09-08
ARK identifier:

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