UNLABELLED: To permit a more complete analysis of J-wire fracture in the Accufix series of atrial permanent pacemaker leads, the time to occurrence of all known fractures and injuries has been redefined relative to the duration of risk exposure, that is, according to the interval of time between implant and occurrence of the event. This redefinition permits application of a cumulative hazards model to the data, which previously has not been explored. Predictors of J-wire fracture can be tested using this method. This also permits parametric curve-fitting for determination of linearity or constancy of risk of events over time. RESULTS: Among 2,063 Multicenter Study (MCS) leads analyzed, 381 fractures of the J-wire were identified. Stratified analysis based on cumulative hazard curves identified a more open shape of the J-wire as predictive of fracture, which supports the results previously reported based on logistic regression analysis. Fitting a Weibull curve to the cumulative hazard of J-wire fracture gives a shape parameter equal to 0.85. This value indicates that the instantaneous hazard of J-wire fracture decreased over time from implant. CONCLUSIONS: (1) The cumulative hazard function can be used to examine predictors of J-wire fracture and preliminary findings support the previously identified predictor of J shape; (2) Based on these analyses, the rate of J-wire fracture appears to decrease slightly as time from implant increases.
UNLABELLED: To permit a more complete analysis of J-wire fracture in the Accufix series of atrial permanent pacemaker leads, the time to occurrence of all known fractures and injuries has been redefined relative to the duration of risk exposure, that is, according to the interval of time between implant and occurrence of the event. This redefinition permits application of a cumulative hazards model to the data, which previously has not been explored. Predictors of J-wire fracture can be tested using this method. This also permits parametric curve-fitting for determination of linearity or constancy of risk of events over time. RESULTS: Among 2,063 Multicenter Study (MCS) leads analyzed, 381 fractures of the J-wire were identified. Stratified analysis based on cumulative hazard curves identified a more open shape of the J-wire as predictive of fracture, which supports the results previously reported based on logistic regression analysis. Fitting a Weibull curve to the cumulative hazard of J-wire fracture gives a shape parameter equal to 0.85. This value indicates that the instantaneous hazard of J-wire fracture decreased over time from implant. CONCLUSIONS: (1) The cumulative hazard function can be used to examine predictors of J-wire fracture and preliminary findings support the previously identified predictor of J shape; (2) Based on these analyses, the rate of J-wire fracture appears to decrease slightly as time from implant increases.