Introduction: T-wave oversensing (TWOS) is the main cause of inappropriate shocks (IAS) in patients with a subcutaneous ICD (S-ICD). Sensing optimization during exercise post S-ICD implantation may prevent IAS caused by TWOS. In our tertiary center, sensing optimization after S-ICD implantation has been used as standard of care since 2014. Improved detection and sensing algorithms, like high pass filter designs, are expected to overcome the problem of TWOS, but the value of sensing optimization during exercise is unknown.
Hypothesis: Sensing optimization during exercise prevents TWOS-related IAS in patients implanted with an S-ICD.
Methods: Sensing optimization was performed within two months in all patients who underwent S-ICD implantation or replacement. Sensing was evaluated during maximal exercise and a new QRS morphology template was stored. The optimal sensing vector was determined based on absence of TWOS and optimal R-T ratio. Follow-up data on IAS was divided into a group before and a group after introduction of the high pass filter, and compared with data of S-ICD patients and IAS in our institution before 2014.
Results: We analyzed 65 patients (69% male, mean age 45 years, ischemic cardiomyopathy in 25%, genetic arrhythmia disease in 37%). Mean maximal heart rate (maxHR) was 142 bpm. A new template was stored in 61 patients (94%). TWOS was observed in 12 patient (18%), but not in the programmed sensing vector selected by the post implant automatic setup. The sensing vector was changed in nine patients (14%) (mean age 35 years, maxHR 163 bpm) based on drop in QRS amplitude in five patients, variable QRS amplitudes in two, an inferior R-T ratio in one and sensing of myopotentials in one. The IAS incidence caused by TWOS declined from 11.6% in 2012 to 2.0% and 0% before and after the introduction of the high pass filter, respectively.
Conclusions: There is a decrease in TWOS-related IAS. Sensing optimization during exercise may be an additional tool to overcome TWOS-related IAS in S-ICD patients. Future studies may identify patients, such as those capable of reaching high heart rates, who are most likely to benefit from sensing optimization during exercise.