Cardiogoniometric parameters for detection of coronary artery disease at rest as a function of stenosis localization and distribution

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

Full text not available from this repository. (Request a copy)

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)

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:

04 May 2014 23:05

Publisher DOI:

10.1007/s11517-010-0594-1

PubMed ID:

20300872

Web of Science ID:

000276771800004

URI:

https://boris.unibe.ch/id/eprint/1895 (FactScience: 203942)

Actions (login required)

Edit item Edit item
Provide Feedback