Risk assessment of @entity1619 event based on modeled XXXX .

@entity1 @entity1619 @entity1165 @entity2224 @entity1162
BACKGROUND: @entity1619 event is a well-known trigger of @entity1165 ( @entity1165 ) and @entity2224 ( @entity2224 ). We propose a method to estimate the risk of @entity1619 event from the inter-beat (RR) intervals based on modeled @entity1162 . METHODS: We retrospectively analyzed the Spontaneous @entity1165 Database and the HAWAI Registry, which include a total of 397 RR interval recordings from 116 implantable cardioverter defibrillator @entity1 . For each RR interval time series, QT intervals were estimated from the weighted average of preceding RR intervals using Bazett, Fridericia, and linear formulas. The risk score (RS) of each cycle was calculated to quantify the probability of @entity1619 event based on the timing of R-wave relative to the estimated T-end. We identified 52,440 ectopic beats (EBs) episodes, 280 nonsustained @entity1165 (NSVT) episodes, and 352 sustained @entity1165 / @entity2224 episodes. The RS of episode onset and the prematurity index (PMI) of the initiating beat were compared. RESULTS: Using different QT-RR models, @entity1619 events were respectively detected in 9% EB, 45% NSVT, 69% @entity1165 / @entity2224 (Bazett); in 6% EB, 41% NSVT, 65% @entity1165 / @entity2224 (Fridericia); and in 7% EB, 42% NSVT, 66% @entity1165 / @entity2224 (linear). No @entity1619 event was found in normal beats. Consistent among three QT-RR models, the RS of episode onset rises sharply from EB to NSVT and to @entity1165 / @entity2224 episodes. In contrast, no trend in PMI is found. CONCLUSIONS: The risk of @entity1619 can be estimated from RR intervals, based on modeled @entity1162 . An episode onset with higher RS has increased risk of developing into NSVT or @entity1165 / @entity2224 .
