Pasquale Vergara1, Wendy S Tzou2, Roderick Tung3, Chiara Brombin4, Alessandro Nonis4, Marmar Vaseghi5, David S Frankel6, Luigi Di Biase7, Usha Tedrow8, Nilesh Mathuria9, Shiro Nakahara10, Venkat Tholakanahalli11, T Jared Bunch12, J Peter Weiss12, Timm Dickfeld13, Dhanunjaya Lakireddy14, J David Burkhardt15, Pasquale Santangeli6, David Callans6, Andrea Natale, Francis Marchlinski, William G Stevenson16, Kalyanam Shivkumar5, William H Sauer2, Paolo Della Bella1. 1. San Raffaele Hospital, Milan, Italy (P.V., P.D.B.). 2. University of Colorado, Aurora (W.S.T., W.H.S.). 3. University of Chicago Medical Center, IL (R.T.). 4. University Centre for Statistics in the Biomedical Sciences, Vita-Salute San Raffaele University, Milano, Italy (C.B., A.N.). 5. UCLA Cardiac Arrhythmia Center, UCLA Health System, Los Angeles, CA (M.V., K.S.). 6. Perelman School of Medicine at the University of Pennsylvania, Philadelphia (D.S.F., P.S., D.C., F.M.). 7. Albert Einstein College of Medicine/Montefiore Medical Center, New York (L.D.B.). 8. Brigham and Women's Hospital, Boston, MA (U.T.). 9. Baylor St Luke's Medical Center/Texas Heart Institute, Houston (N.M.). 10. Dokkyo Medical University Koshigaya Hospital, Saitama, Japan (S.N.). 11. University of Minnesota Medical Center, Minneapolis VA Medical Center, Minneapolis (V.T.). 12. Intermountain Heart Institute, Intermountain Medical Center, Murray, UT (T.J.B., J.P.W.). 13. University of Maryland Medical Center, Baltimore (T.D.). 14. University of Kansas Medical Center, Kansas City (D.L.). 15. Texas Cardiac Arrhythmia Institute, St David's Medical Center, Austin (J.D.B.). 16. Vanderbilt University Medical Center, Nashville, TN (W.G.S.).
Abstract
BACKGROUND: Several distinct risk factors for arrhythmia recurrence and mortality following ventricular tachycardia (VT) ablation have been described. The effect of concurrent risk factors has not been assessed so far; thus, it is not yet possible to estimate these risks for a patient with several comorbidities. The aim of the study was to identify specific risk groups for mortality and VT recurrence using the Survival Tree (ST) analysis method. METHODS: In 1251 patients 16 demographic, clinical and procedure-related variables were evaluated as potential prognostic factors using ST analysis using a recursive partitioning algorithm that searches for relationships among variables. Survival time and time to VT recurrence in groups derived from ST analysis were compared by a log-rank test. A random forest analysis was then run to extract a variable importance index and internally validate the ST models. RESULTS: Left ventricular ejection fraction, implantable cardioverter defibrillator/cardiac resynchronization device, previous ablation were, in hierarchical order, identified by ST analysis as best predictors of VT recurrence, while left ventricular ejection fraction, previous ablation, Electrical storm were identified as best predictors of mortality. Three groups with significantly different survival rates were identified. Among the high-risk group, 65.0% patients were survived and 52.1% patients were free from VT recurrence; within the medium- and low-risk groups, 84.0% and 97.2% patients survived, 72.4% and 88.4% were free from VT recurrence, respectively. CONCLUSIONS: Our study is the first to derive and validate a decisional model that provides estimates of VT recurrence and mortality with an effective classification tree. Preprocedure risk stratification could help optimize periprocedural and postprocedural care.
BACKGROUND: Several distinct risk factors for arrhythmia recurrence and mortality following ventricular tachycardia (VT) ablation have been described. The effect of concurrent risk factors has not been assessed so far; thus, it is not yet possible to estimate these risks for a patient with several comorbidities. The aim of the study was to identify specific risk groups for mortality and VT recurrence using the Survival Tree (ST) analysis method. METHODS: In 1251 patients 16 demographic, clinical and procedure-related variables were evaluated as potential prognostic factors using ST analysis using a recursive partitioning algorithm that searches for relationships among variables. Survival time and time to VT recurrence in groups derived from ST analysis were compared by a log-rank test. A random forest analysis was then run to extract a variable importance index and internally validate the ST models. RESULTS: Left ventricular ejection fraction, implantable cardioverter defibrillator/cardiac resynchronization device, previous ablation were, in hierarchical order, identified by ST analysis as best predictors of VT recurrence, while left ventricular ejection fraction, previous ablation, Electrical storm were identified as best predictors of mortality. Three groups with significantly different survival rates were identified. Among the high-risk group, 65.0% patients were survived and 52.1% patients were free from VT recurrence; within the medium- and low-risk groups, 84.0% and 97.2% patients survived, 72.4% and 88.4% were free from VT recurrence, respectively. CONCLUSIONS: Our study is the first to derive and validate a decisional model that provides estimates of VT recurrence and mortality with an effective classification tree. Preprocedure risk stratification could help optimize periprocedural and postprocedural care.
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