Predicting the outcomes of electrophysiologic studies of patients with unexplained syncope: preliminary validation of a derived model. 1991

M Linzer, and E N Prystowsky, and G W Divine, and D B Matchar, and G Samsa, and F Harrell, and J C Pressley, and D B Pryor
Department of Medicine, Duke University Medical Center, Durham, North Carolina.

OBJECTIVE To develop and validate a predictive model that would allow clinicians to determine whether an electrophysiologic (EP) study is likely to result in useful diagnostic information for a patient who has unexplained syncope. METHODS One hundred seventy-nine consecutive patients with unexplained syncope who underwent EP studies at two university medical centers comprised the training sample. A test sample to validate the model was made up of 138 patients from the clinical literature who had undergone EP studies for syncope. METHODS Retrospective analysis of patients undergoing EP studies for syncope. The data collector was blinded to the study hypothesis; the electrophysiologist assessing outcomes was blinded to clinical and historical data. Clinical predictor variables available from the history, the physical examination, electrocardiography (ECG), and Holter monitoring were analyzed via two multivariable predictive modeling strategies (ordinal logistic regression and recursive partitioning) for their abilities to predict the results of EP studies, namely tachyarrhythmic and bradyarrhythmic outcomes. These categories were further divided into full arrhythmia and borderline arrhythmia groups. RESULTS Important outcomes were 1) sustained monomorphic ventricular tachycardia (VT) and 2) bradyarrhythmias, including sinus node and atrioventricular (AV) conducting disease. The results of the logistic regression (in this study, the superior strategy) showed that the presence of organic heart disease [odds ratio (OR) = 3.0, p less than 0.001] and frequent premature ventricular contractions on ECG (OR = 6.7, p less than 0.004) were associated with VT, while the following abnormal ECG findings were associated with bradyarrhythmias: first-degree heart block (OR = 7.9, p less than 0.001), bundle-branch block (OR = 3.0, p less than 0.02), and sinus bradycardia (OR = 3.5, p less than 0.03). Eighty-seven percent of the 31 patients with important outcomes at EP study had at least one of these clinical risk factors, while 95% of the patients with none of these risk factors had normal or nondiagnostic EP studies. In the validation sample, the presence of one or more risk factors would have correctly identified 88% of the test VT patients and 65% of the test bradyarrhythmia patients as needing EP study. CONCLUSIONS These five identified predictive factors, available from the history, the physical examination, and the initial ECG, could be useful to clinicians in selecting those patients with unexplained syncope who will have a serious arrhythmia identified by EP studies.

UI MeSH Term Description Entries
D008297 Male Males
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D011237 Predictive Value of Tests In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., has the disease), is referred to as the predictive value of a positive test; whereas, the predictive value of a negative test is the probability that the person with a negative test does not have the disease. Predictive value is related to the sensitivity and specificity of the test. Negative Predictive Value,Positive Predictive Value,Predictive Value Of Test,Predictive Values Of Tests,Negative Predictive Values,Positive Predictive Values,Predictive Value, Negative,Predictive Value, Positive
D012044 Regression Analysis Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable. Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D002304 Cardiac Pacing, Artificial Regulation of the rate of contraction of the heart muscles by an artificial pacemaker. Pacing, Cardiac, Artificial,Artificial Cardiac Pacing,Artificial Cardiac Pacings,Cardiac Pacings, Artificial,Pacing, Artificial Cardiac,Pacings, Artificial Cardiac
D004594 Electrophysiology The study of the generation and behavior of electrical charges in living organisms particularly the nervous system and the effects of electricity on living organisms.
D005260 Female Females
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D001145 Arrhythmias, Cardiac Any disturbances of the normal rhythmic beating of the heart or MYOCARDIAL CONTRACTION. Cardiac arrhythmias can be classified by the abnormalities in HEART RATE, disorders of electrical impulse generation, or impulse conduction. Arrhythmia,Arrythmia,Cardiac Arrhythmia,Cardiac Arrhythmias,Cardiac Dysrhythmia,Arrhythmia, Cardiac,Dysrhythmia, Cardiac
D012189 Retrospective Studies Studies used to test etiologic hypotheses in which inferences about an exposure to putative causal factors are derived from data relating to characteristics of persons under study or to events or experiences in their past. The essential feature is that some of the persons under study have the disease or outcome of interest and their characteristics are compared with those of unaffected persons. Retrospective Study,Studies, Retrospective,Study, Retrospective

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