Importance of accounting for the variability of electrocardiographic data among diagnostically similar patients with inferior wall healed myocardial infarction

      In this report, we propose an objective method of deciding what is the permissible magnitude of deviation of a patient’s electrocardiogram (ECG) from those that are either normal or are typical of various abnormalities. In our method, we compare an individual patient’s digital electrocardiographic data with the pooled data from the ECGs of diagnostically uniform groups of patients. A key feature of our method is that it considers not only the numerical differences among these sets of data, but also the variability of the data. By doing so, our method empirically addresses the question: How much deviation of a patient’s ECG from normal and from various abnormal standards is diagnostically significant? To test the usefulness of the proposed method, we studied its ability to diagnose healed inferior myocardial infarction (IMI).
      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'


      Subscribe to American Journal of Cardiology
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect


      1. Steel RH, Torrie LR. Principles and Procedures of Statistics. New York: McGraw-Hill, 1980:54–56.

        • Willems J.L.
        • Arnaud P.
        • van Bemmel J.H.
        • Bourdillon P.J.
        • Brohet C.
        Assessment of the performance of electrocardiographic computer programs with the use of reference database.
        Circulation. 1985; 71: 523-534
        • Willems J.L.
        • Abreu-Lima C.
        • Arnaud P.
        • van Bemmel J.H.
        • Brohet C.
        • Degani R.
        • Denis R.
        • Gehring J.
        • Graham I.
        • van Herpen G.
        The diagnostic performance of computer programs for the interpretation of electrocardiograms.
        N Engl J Med. 1991; 325: 1767-1773
        • Kornreich F.
        • Startt/Selvester R.H.
        • Montague T.J.
        • Rautaharju P.M.
        • Saetre H.A.
        • Ahmad J.
        Discriminant analysis of the standard 12-lead ECG for diagnosing non-Q wave myocardial infarction.
        J Electrocardiol. 1985; 24: 163-172