Automated and Nomographic Analysis of Exercise Tests

Michael H. Sketch, Syed M. Mohiuddin, Chandra K. Nair, Aryan N. Mooss, Vincent Runco

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

A study was conducted to evaluate the validity and usefulness of a commercially available microprocessor for automated exercise ECG analysis and to develop a nomogram for estimating the severity of coronary artery disease. Results of visual analysis, automated analysis, and coronary arteriography were correlated for the 107 patients studied. Automated analysis was shown to be valid and useful. The ST integrals (area of ST depression) recorded after exercise were superior to those recorded during exercise because they manifested higher specificity and predictive value, even though their sensitivity was slightly lower. Using postexercise integrals, it was possible to differentiate mild and severe disease. From multipleregression analysis of ST integrals, duration of exercise, and the severity of coronary artery disease, a nomogram was derived to estimate severity of coronary artery disease.

Original languageEnglish (US)
Pages (from-to)1052-1055
Number of pages4
JournalJAMA: The Journal of the American Medical Association
Volume243
Issue number10
DOIs
StatePublished - Mar 14 1980

All Science Journal Classification (ASJC) codes

  • Medicine(all)

Fingerprint Dive into the research topics of 'Automated and Nomographic Analysis of Exercise Tests'. Together they form a unique fingerprint.

Cite this