Preventing Overdiagnosis of Implantable Cardioverter-Defibrillator Lead Fractures Using Device Diagnostics

Objectives tudy sought to use implantable cardioverter-defibrillator (ICD) diagnostics to discriminate ICD lead fractures from normally functioning leads with high impedance and from connection problems between the lead and header. ound agnostics facilitate identification of fractures, but there are no accepted criteria for discriminating fractures from other causes of high impedance and/or nonphysiological “noise” oversensing. s lyzed a development set of 91 leads to construct a stepwise algorithm based on ICD diagnostics. It included 40 fractures, 30 connection problems, and 21 functioning leads that triggered high-impedance alerts. Then we applied this algorithm to an independent test set of 100 leads: 70 fractures and 30 intact leads with connection problems that were misdiagnosed clinically as fractures. In the algorithm, either extremely high maximum impedance or noise oversensing with a normal impedance trend indicated a fracture. A short interval from surgery to impedance rise or prolonged stable impedance after an abrupt rise indicated a connection problem. A gradual impedance increase or stable, high impedance indicated a functioning lead. s test set, the algorithm correctly classified 100% of fractures (95% confidence interval [CI]: 95% to 100%) and 87% of connection problems that were misdiagnosed as fractures (95% CI: 70% to 95%). sions orithm using only ICD diagnostics identifies leads with oversensing or high impedance as fractures or connection problems with a high degree of accuracy.