Huebner, Thomas; Schuepbach, W M Michael; Seeck, Andrea; Sanz, Ernst; Meier, Bernhard; Voss, Andreas; Pilgram, Roland (2010). Cardiogoniometric parameters for detection of coronary artery disease at rest as a function of stenosis localization and distribution. Medical & biological engineering & computing, 48(5), pp. 435-46. Heidelberg: Springer 10.1007/s11517-010-0594-1
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Cardiogoniometry (CGM), a spatiotemporal electrocardiologic 5-lead method with automated analysis, may be useful in primary healthcare for detecting coronary artery disease (CAD) at rest. Our aim was to systematically develop a stenosis-specific parameter set for global CAD detection. In 793 consecutively admitted patients with presumed non-acute CAD, CGM data were collected prior to elective coronary angiography and analyzed retrospectively. 658 patients fulfilled the inclusion criteria, 405 had CAD verified by coronary angiography; the 253 patients with normal coronary angiograms served as the non-CAD controls. Study patients--matched for age, BMI, and gender--were angiographically assigned to 8 stenosis-specific CAD categories or to the controls. One CGM parameter possessing significance (P < .05) and the best diagnostic accuracy was matched to one CAD category. The area under the ROC curve was .80 (global CAD versus controls). A set containing 8 stenosis-specific CGM parameters described variability of R vectors and R-T angles, spatial position and potential distribution of R/T vectors, and ST/T segment alterations. Our parameter set systematically combines CAD categories into an algorithm that detects CAD globally. Prospective validation in clinical studies is ongoing.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
04 Faculty of Medicine > Department of Cardiovascular Disorders (DHGE) > Clinic of Cardiology |
UniBE Contributor: |
Meier, Bernhard |
ISSN: |
0140-0118 |
Publisher: |
Springer |
Language: |
English |
Submitter: |
Factscience Import |
Date Deposited: |
04 Oct 2013 14:11 |
Last Modified: |
05 Dec 2022 14:01 |
Publisher DOI: |
10.1007/s11517-010-0594-1 |
PubMed ID: |
20300872 |
Web of Science ID: |
000276771800004 |
BORIS DOI: |
10.48350/1895 |
URI: |
https://boris.unibe.ch/id/eprint/1895 (FactScience: 203942) |
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