title: Discriminant analysis of the standard 12-lead ECG for diagnosing non-Q wave myocardial infarction.
abstract: Discriminant analysis was performed on 12 standard lead data from 159 normal subjects (N) and 304 patients with first myocardial infarction (MI): the latter group consisted of 543 patients with acute non-Q wave MI (NQMI-group A), 68 patients with acute Q wave MI (QMI-group B) and 183 patients (group C) with recent (29) or old (154) QMI. A discriminant function was computed to separate optimally the larger group of QMI patients (group C) from N. A total of 7 features accounted for a specificity of 92% and a sensitivity of 89%. The classification model was then tested on patients with acute MI, regardless of the presence of Q waves (groups A and B); rates of correct classification were 72% for acute NQMI and 85% for acute QMI. The best measurements were voltages in the late portion of the T wave in aVR, V1 and V5, in early and late QRS in V2, at mid-QRS in lead II and in the second half of the P wave in V1. A weighted combination of these features with the coefficients of the discriminant function produced individual discriminant scores for each subject. Group-mean scores were 1.82 for N, -1.27 for acute QMI, -1.14 for old QMI and -.44 for acute NQMI, indicating that acute NQMI was "closer" to N than both acute and old QMI. QRS measurements from the 12-lead ECG were also used to derive the 45 criteria/33 point Selvester score in 53 patients with NQMI: 32% of NQMI were classified as MI with a score of 3 points or more (corresponding to a posterior probability greater than .50). These results were compared with those achieved by multivariate analysis using only QRS measurements: 56% of NQMI were classified as MI with a posterior probability threshold greater than .50. Associating a point score greater than or equal to 1 with criteria for ST-T abnormalities yielded a sensitivity of 72% at a specificity level of 95%. The results emphasize the presence of diagnostic information outside the initial part of QRS, the power of multivariate statistical procedures applied on continuous measurements and the potential benefit of discriminant scores for quantitative assessment of myocardial infarction.
authors.affiliation: Unit for Cardiovascular Research and Engineering, Free University Brussels (VUB), Belgium.
authors.forename: F
authors.initials: F
authors.lastname: Kornreich
authors.forename: R H
authors.initials: RH
authors.lastname: Selvester
authors.forename: T J
authors.initials: TJ
authors.lastname: Montague
authors.forename: P M
authors.initials: PM
authors.lastname: Rautaharju
authors.forename: H A
authors.initials: HA
authors.lastname: Saetre
authors.forename: J
authors.initials: J
authors.lastname: Ahmad
mesh_terms: D016002:Discriminant Analysis; D004562:Electrocardiography / Q000379:methods* / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009203:Myocardial Infarction / Q000175:diagnosis* / Q000453:epidemiology; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted