Use of the logical analysis of data method for assessing long-term mortality risk after exercise electrocardiography.
BACKGROUND
Logical Analysis of Data is a methodology of mathematical optimization on the basis of the systematic identification of patterns or "syndromes." In this study, we used Logical Analysis of Data for risk stratification and compared it to regression techniques.


RESULTS
Using a cohort of 9454 patients referred for exercise testing, Logical Analysis of Data was applied to identify syndromes based on 20 variables. High-risk syndromes were patterns of up to 3 findings associated with >5-fold increase in risk of death, whereas low-risk syndromes were associated with >5-fold decrease. Syndromes were derived on a randomly derived training set of 4722 patients and validated in 4732 others. There were 15 high-risk and 26 low-risk syndromes. A risk score was derived based on the proportion of possible high risk and low risk syndromes present. A value > or =0, meaning the same or a greater proportion of high-risk syndromes, was noted in 979 patients (21%) in the validation set and was predictive of 5-year death (11% versus 1%, hazard ratio 8.3, 95% CI 5.9 to 11.6, P<0.0001), accounting for 67% of events. Calibration of expected versus observed death rates based on Logical Analysis of Data and Cox regression showed that both methods performed very well.


CONCLUSIONS
Using the Logical Analysis of Data method, we identified subsets of patients who had an increased risk and who also accounted for the majority of deaths. Future research is needed to determine how best to use this technique for risk stratification.
Lauer
Michael S
MS
Department of Cardiology of the Cleveland Clinic Foundation, Cleveland, Ohio 44195, USA. Lauerm@ccf.org
Alexe
Sorin
S
Pothier Snader
Claire E
CE
Blackstone
Eugene H
EH
Ishwaran
Hemant
H
Hammer
Peter L
PL
D002318:Cardiovascular Diseases / Q000175:diagnosis / Q000401:mortality*; D004562:Electrocardiography; D005080:Exercise Test; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D011379:Prognosis; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D012307:Risk Factors; D015996:Survival Rate; D013577:Syndrome