Discriminant Methods as Aids to the Diagnosis of Acute Coronary Heart Disease in the Emergency Room

Summary

Multivariate stepwise logistic regression and discriminant analyses were used to reduce emergency room data to the most relevant subset of variables that could improve the sensitivity and specificity of the diagnosis of acute coronary heart disease. Both procedures selected 5 out of 29 variables collected from 154 patients : abnormality of the ST segment in the electrocardiogram (ECG), shortness of breath, history of sublingual glyceryltrinitrate intake, chest pain duration >15 minutes, and previous history of a heart attack. The stepwise discriminant function selected additional variables: chest pain as the most important symptom, retrosternal site of chest pain and T wave abnormality on the ECG. The performance of the two methods was assessed by finding the classification matrix.

Multivariate, schrittweise logistische Regression und Diskriminanz-Analysen wurden angewandt, um Daten aus der Intensivstation auf die relevanteste Teilmenge von Variablen zurückzuführen, welche die Sensitivität und Spezifizität der Diagnose bei akuten koronaren Herzkrankheiten verbessern könnte. Bei beiden Verfahren wurden 5 von 29 bei 154 Patienten gesammelte Variable ausgewählt: Anomalität des ST-Segments beim Elektrokardiogramm (EKG), Kurzatmigkeit, sublinguale Glyzerintrinitrateinnahme in der Anamnese, Brustschmerzen während 15 Minuten und Herzanfall in der Vorgeschichte. Die schrittweise Diskriminanz ermittelte zusätzliche Variable: Brustschmerz als wichtigstes Symptom, retrosternaler Sitz des Brustschmerzes und T-Wellen-Anomalität im EKG. Die Leistung der beiden Methoden wurde durch Feststellung der Klassifikationsmatrix ermittelt.

Key-Words

Logistic Regression - Discriminant Analysis - Classification Matrix

Schlüssel-Wörter

Logistische Regression - Diskriminanzanalyse - Klassifikationsmatrix

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