DocumentCode
145545
Title
Using the Principles of Bayesian Statistics to Improve the Performances of Medical Diagnostic Tests
Author
Warner, Robert A.
Author_Institution
Tigard Res. Inst., Tigard, OR, USA
Volume
2
fYear
2014
fDate
10-13 March 2014
Firstpage
64
Lastpage
68
Abstract
The study analyzed diagnostic data from 432 patients evaluated in the emergency department for shortness of breath. Electronically recorded heart sounds and brain natriuretic peptide (BNP) were analyzed to determine whether left ventricular systolic dysfunction (LVSD) with heart failure caused each patient´s symptoms. In each patient´s computerized digital electrocardiogram, measurements of the duration of the QRS complex were made. As expected, the data show that the QRS complex duration itself does not detect LVSD with heart failure. However, for both the recorded heart sounds and the BNP data, the diagnostic sensitivities at 98% specificity for LVSD with heart failure are significantly greater in the subgroups with prolonged QRS complex duration than they are in the entire group of subjects. Evaluating QRS complex duration on the digital electrocardiogram can assess the prior probability of underlying heart disease and improves the performances of diagnostic tests for LVSD with heart failure.
Keywords
Bayes methods; brain; diseases; electrocardiography; medical diagnostic computing; statistical analysis; BNP data; Bayesian statistics principles; LVSD; QRS complex duration measurements; brain natriuretic peptide; breath shortness emergency department; computerized digital electrocardiogram; diagnostic data analysis; diagnostic sensitivities; heart failure; heart sounds; left ventricular systolic dysfunction; medical diagnostic test performance improvement; patient symptoms; prior probability; underlying heart disease; Accuracy; Diseases; Electrocardiography; Heart; Sensitivity; Sociology; Statistics; QRS duration; diagnostic accuracy; prior probability;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Science and Computational Intelligence (CSCI), 2014 International Conference on
Conference_Location
Las Vegas, NV
Type
conf
DOI
10.1109/CSCI.2014.96
Filename
6822305
Link To Document