A new method to incorporate age and gender into the criteria for the detection of acute inferior myocardial infarction

Joel Xue, Basel Taha, Shankara Reddy, R. Scott Wright, Thomas Aufderheide

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Recent studies have shown that younger women are more likely to die during and after hospitalization for acute myocardial infarction (MI) than older women and men of all ages. This may be partly due to incorrect diagnosis or late detection of acute MI in younger women. At high specificity levels (%#62;98%), the sensitivity of the initial ECG to detect acute MI may be as low as 30% when using traditional criteria by both physicians and computerized interpretation programs. This study examines if women of different age groups have a similar ECG presentation to men during acute inferior MI and if the diagnostic accuracies of the initial ECG are comparable. We analyzed chest pain ECGs from Mayo Clinic and Medical College of Wisconsin, which included 1,339 patients with acute inferior MI and 1,169 agematched controls with noncardiac chest pain. We subdivided all groups by age (below and above 60 years) and compared ECG parameters (ST elevation, ST depression, QRS duration, R-wave amplitude, Q-wave duration and amplitude, QT interval) between genders. For inferior MI patients under age 60, women had lower ST elevations at the J point in lead II than men (57 ± 91 μV vs. 86 ± 117 μV, P <. 02). This trend was reversed for patients over age 60 (lead aVF: 102 ± 126 μV vs. 84±117 μV, P <. 04; Lead III: 130±146 μV vs. 103±131 μV, P <. 007). A neural network method was used to identify the most significant group of ECG parameters for detecting acute MI. An adaptive fuzzy logic method was developed for adapting to the threshold differences among the different gender and age groups. The new algorithm improved the sensitivity of acute inferior MI detection by more than 25% relative to old algorithm, while maintaining the high specificity arotmd 98% for noncardiac chest pain patients.

Original languageEnglish (US)
Pages (from-to)229-234
Number of pages6
JournalJournal of Electrocardiology
Volume34
Issue number4
DOIs
StatePublished - Dec 11 2001

Keywords

  • Acute MI
  • Computerized ECG diagnosis
  • Fuzzy logic
  • Gender and age specific
  • Neural networks

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine

Fingerprint Dive into the research topics of 'A new method to incorporate age and gender into the criteria for the detection of acute inferior myocardial infarction'. Together they form a unique fingerprint.

Cite this