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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
Stronger Correlations between Neurophysiological and Peripheral Disease Biomarkers Predict Better Prognosis in Two
Yori Gidron1, Marijke De Couck2, Tatjana Reynders2,3
1Dept. of Nursing, University of Haifa, Haifa 3498838, Israel.
Abstract:
: 'Mind-body' debates assume that better brain-body associations are healthy. This study examined whether degree of associations between a neurophysiological vagal nerve index and peripheral disease biomarkers predict prognosis in pancreatic cancer (PC) and multiple sclerosis (MS). Sample 1 included 272 patients with advanced PC. Sample 2 included 118 patients with MS. We measured the vagal nerve index heart rate variability (HRV) derived from electrocardiograms. We examined associations between HRV and patients' peripheral disease biomarkers: CA19-9 in PC and neurofilament light chain (NFL) in MS. Associations between HRV and each biomarker were examined separately in patients who survived or died (PC), and in those with and without relapse during 12 months (MS). In PC, HRV was significantly inversely related to the tumor marker CA19-9 in patients who later survived (r = -0.44, p < 0.05) but not in those who died (r = 0.10, NS). In MS, HRV was significantly and inversely related to NFL only in those who did not relapse (r = -0.25, p < 0.05), but not in those who relapsed (r = -0.05, NS). The degree of association between a neurophysiological vagal marker and peripheral disease biomarkers has prognostic value in two distinct diseases.
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