Noise, artifact, and oversensing related inappropriate ICD shock evaluation: ALTITUDE noise study

Pacing Clin Electrophysiol. 2012 Jul;35(7):863-9. doi: 10.1111/j.1540-8159.2012.03407.x. Epub 2012 Apr 22.

Abstract

Background: Approximately 12-21% of implantable cardioverter defibrillator (ICD) patients receive inappropriate shocks. We sought to determine the incidence and causes of noise/artifact and oversensing (NAO) resulting in ICD shocks.

Methods: A random sample of 2,000 patients who received ICD and cardiac resynchronization therapy defibrillator shocks and were followed by a remote monitoring system was included. Seven electrophysiologists analyzed stored electrograms from the 5,279 shock episodes. Episodes were adjudicated as appropriate or inappropriate shocks.

Results: Of the 5,248 shock episodes with complete adjudication, 1,570 (30%) were judged to be inappropriate shocks. Of these 1,570, 134 (8.5%) were a result of NAO. The 134 NAO episodes were determined to be due to external noise in 76 (57%), lead connector-related in 37 (28%), muscle noise in 11 (8%), oversensing of atrium in seven (5%), T-wave oversensing in two (2%), and other noise in one (1%). The ICD shock itself resulted in a marked decrease in the level of noise in 60 of 134 (45%) NAO episodes, and the magnitude of this effect varied with the type of NAO (58% for external noise, 35% for muscle, 27% for lead/connector, and 0% for oversensing; P = 0.03). There was no significant difference in NAO likelihood based on type of lead (integrated bipolar 89/1,802 vs dedicated bipolar 9/140, P = 0.67).

Conclusions: External noise and lead/connector noise were the primary causes, while T-wave oversensing was the least common cause of NAO resulting in ICD shock. Noise/artifact decreased immediately after a shock in nearly half of episodes. The specific ICD lead type did not impact the likelihood of NAO.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Artifacts*
  • Defibrillators, Implantable / statistics & numerical data*
  • Electric Injuries / epidemiology*
  • Equipment Failure / statistics & numerical data*
  • Female
  • Humans
  • Incidence
  • Male
  • Risk Factors
  • Signal-To-Noise Ratio*
  • United States / epidemiology