Literature DB >> 781162

The concepts of sensitivity, specificity and accuracy in evaluation of electrocardiographic, vectorcardiographic and polarcardiographic criteria.

P M Rautaharju, H W Blackburn, J W Warren.   

Abstract

The concepts sensitivity and specificity are critically evaluated in the light of case studies drawn from electrocardiographic literature. These terms are often misused, and the meaning of these elementary statistical concepts is often misunderstood in studies on ECG, VCG and PCG criteria. Specificity figures reported in literature commonly refer to the fraction of true negatives with a negative test in normals. Limiting the test to two-group analysis and eliminating other disease categories tend to give overoptimistic values for specificity and diagnostic accuracy in general. It is pointed out that various performance indices for diagnostic accuracy depend heavily on the composition of the test groups and the fraction of test cases in each group. Sensitivity and specificity appear inadequate performance indices for evaluation of event detection schemes such as classification of ectopic beats. Alternative performance indices are considered, including the error ratio, association index, accuracy of positive test, accuracy of negative test, and overall diagnostic accuracy. Increased utilization of simple statistical tests for significance estimation in ECG criteria evaluation is suggested. The development and application of better diagnostic performance evaluation schemes based on concepts of cost of misclassification, entropy and information is encouraged.

Mesh:

Year:  1976        PMID: 781162     DOI: 10.1016/s0022-0736(76)80057-x

Source DB:  PubMed          Journal:  J Electrocardiol        ISSN: 0022-0736            Impact factor:   1.438


  3 in total

1.  Heart rate variability and sympathovagal balance: pharmacological validation.

Authors:  M Bootsma; C A Swenne; M J A Janssen; V Manger Cats; M J Schalij
Journal:  Neth Heart J       Date:  2003-06       Impact factor: 2.380

2.  Artificial neural networks for the diagnosis of atrial fibrillation.

Authors:  T F Yang; B Devine; P W Macfarlane
Journal:  Med Biol Eng Comput       Date:  1994-11       Impact factor: 2.602

3.  Mining for diagnostic information in body surface potential maps: a comparison of feature selection techniques.

Authors:  Dewar D Finlay; Chris D Nugent; Paul J McCullagh; Norman D Black
Journal:  Biomed Eng Online       Date:  2005-09-02       Impact factor: 2.819

  3 in total

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