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Jasiukaitis and Lyon (J Clin Monit Comput, https://doi.org/10.1007/s10877-018-0181-9 , 2018) described an motor evoked potential (MEP)amplitude trending system to detect MEP amplitude loss against a background of MEP variability. They found that the end of case value of a running R triggered by a set MEP amplitude loss criterion appeared to discriminate new injury from non-injury in a small sample of three patients. The present study examines the predictive capability of the running R in a larger sample of patients (21 injured and 19 non-injured). It also varies the amplitude loss criterion (50%, 65% and 80%) for triggering the running R and the numbers of points used in the moving linear regression (8, 12 and 16). 40 patients who had undergone correction for lumbar deformity were retrospectively examined. 21 of these woke up with a newly acquired radicular injury, 19 did not but were characterized by hypovolemic hemorrhage. All 40 patients had sufficient MEP amplitude loss sometime during their procedure to cause the monitoring specialist to report this to the surgeon and anesthesia. End-of-case running Rs were significantly larger in the injury group. Using an 80% amplitude loss criterion to trigger the running R proved to be too stringent, causing reduced sensitivity. The running R appeared to have equivalent sensitivity to that of conventional MEP amplitude loss ratios, but superior specificity within this monitoring challenged sample. The different number of points for the moving regressions did not have any significant effect. End-of-case R values greater than 60% appeared to be highly predictive of new post-operative deficit, while values less than 40% appeared to insure no new deficit. The proposed trending system can discriminate injury from non-injury outcomes when compressive radicular injury during correction for lumbar deformity is involved. This discrimination appears to be successful even when MEP amplitude loss for non-iatrogenic reasons (i.e., hemorrhage) is also occurring.
This article was published in the following journal.
Name: Journal of clinical monitoring and computing
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