Early Diagnosis of Defibrillation Lead Dislodgement
This study sought to develop and evaluate an algorithm for early diagnosis of dislodged implantable cardioverter-defibrillator (ICD) leads. Dislodged defibrillation leads may sense atrial and ventricular electrograms (EGMs), triggering shocks in the vulnerable period that induce ventricular fibrilla...
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Veröffentlicht in: | JACC. Clinical electrophysiology 2018-08, Vol.4 (8), p.1075-1088 |
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container_title | JACC. Clinical electrophysiology |
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creator | Zaman, Junaid A.B. Chua, Kelvin Sovari, Ali A. Gunderson, Bruce Gang, Eli S. Ploux, Sylvain Swerdlow, Charles D. |
description | This study sought to develop and evaluate an algorithm for early diagnosis of dislodged implantable cardioverter-defibrillator (ICD) leads.
Dislodged defibrillation leads may sense atrial and ventricular electrograms (EGMs), triggering shocks in the vulnerable period that induce ventricular fibrillation (VF).
We developed a 2-step algorithm by using experimental lead dislodgements (LDs) at ICD implantation and a control dataset of newly implanted, in situ leads. Step 1 consisted of an alert triggered by abrupt decrease in R-wave amplitude and increase in pacing threshold. Step 2 withheld therapy based on ventricular EGM evidence of LD identified from experimental LD behavior. We estimated the algorithm’s performance using a registry dataset of 3,624 new implantations and an atrial dislodgement dataset of 14 LDs at the atrium.
In the registry dataset, the algorithm identified 20 of 21 radiographic LDs (95%) at a median of 11 days before clinical diagnosis. Step 1 had positive predictive values of 57% for radiographic LD and 77% for surgical revision. The false positive rate was 0.4% after step 1 and ≤0.2% after step 2. In the atrial dislodgement dataset, step 1 identified all 14 LDs; step 2 would have prevented inappropriate therapy in all 7 patients with stored EGMs at LD, including 2 patients with fatal, shock-induced VF.
An ICD algorithm can facilitate early diagnosis of defibrillation LD. Additional data are needed to determine the safety of withholding shocks based on EGM evidence of LD.
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doi_str_mv | 10.1016/j.jacep.2018.03.015 |
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Dislodged defibrillation leads may sense atrial and ventricular electrograms (EGMs), triggering shocks in the vulnerable period that induce ventricular fibrillation (VF).
We developed a 2-step algorithm by using experimental lead dislodgements (LDs) at ICD implantation and a control dataset of newly implanted, in situ leads. Step 1 consisted of an alert triggered by abrupt decrease in R-wave amplitude and increase in pacing threshold. Step 2 withheld therapy based on ventricular EGM evidence of LD identified from experimental LD behavior. We estimated the algorithm’s performance using a registry dataset of 3,624 new implantations and an atrial dislodgement dataset of 14 LDs at the atrium.
In the registry dataset, the algorithm identified 20 of 21 radiographic LDs (95%) at a median of 11 days before clinical diagnosis. Step 1 had positive predictive values of 57% for radiographic LD and 77% for surgical revision. The false positive rate was 0.4% after step 1 and ≤0.2% after step 2. In the atrial dislodgement dataset, step 1 identified all 14 LDs; step 2 would have prevented inappropriate therapy in all 7 patients with stored EGMs at LD, including 2 patients with fatal, shock-induced VF.
An ICD algorithm can facilitate early diagnosis of defibrillation LD. Additional data are needed to determine the safety of withholding shocks based on EGM evidence of LD.
[Display omitted]</description><identifier>ISSN: 2405-500X</identifier><identifier>EISSN: 2405-5018</identifier><identifier>DOI: 10.1016/j.jacep.2018.03.015</identifier><identifier>PMID: 30139490</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Aged ; Aged, 80 and over ; Algorithms ; Defibrillators, Implantable - adverse effects ; Early Diagnosis ; Electrocardiography ; Female ; Humans ; Image Interpretation, Computer-Assisted ; implantable cardioverter-defibrillator ; lead dislodgement ; lead displacement ; lead migration ; Male ; Middle Aged ; Postoperative Complications - diagnosis ; Predictive Value of Tests ; Prosthesis Failure ; Radiography ; Ventricular Fibrillation</subject><ispartof>JACC. Clinical electrophysiology, 2018-08, Vol.4 (8), p.1075-1088</ispartof><rights>2018 American College of Cardiology Foundation</rights><rights>Copyright © 2018 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c359t-43c3602048a2beba076e9176ca8e9a72da89cfb3f1534b149e79a00ae083eab23</citedby><cites>FETCH-LOGICAL-c359t-43c3602048a2beba076e9176ca8e9a72da89cfb3f1534b149e79a00ae083eab23</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27903,27904</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30139490$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zaman, Junaid A.B.</creatorcontrib><creatorcontrib>Chua, Kelvin</creatorcontrib><creatorcontrib>Sovari, Ali A.</creatorcontrib><creatorcontrib>Gunderson, Bruce</creatorcontrib><creatorcontrib>Gang, Eli S.</creatorcontrib><creatorcontrib>Ploux, Sylvain</creatorcontrib><creatorcontrib>Swerdlow, Charles D.</creatorcontrib><title>Early Diagnosis of Defibrillation Lead Dislodgement</title><title>JACC. Clinical electrophysiology</title><addtitle>JACC Clin Electrophysiol</addtitle><description>This study sought to develop and evaluate an algorithm for early diagnosis of dislodged implantable cardioverter-defibrillator (ICD) leads.
Dislodged defibrillation leads may sense atrial and ventricular electrograms (EGMs), triggering shocks in the vulnerable period that induce ventricular fibrillation (VF).
We developed a 2-step algorithm by using experimental lead dislodgements (LDs) at ICD implantation and a control dataset of newly implanted, in situ leads. Step 1 consisted of an alert triggered by abrupt decrease in R-wave amplitude and increase in pacing threshold. Step 2 withheld therapy based on ventricular EGM evidence of LD identified from experimental LD behavior. We estimated the algorithm’s performance using a registry dataset of 3,624 new implantations and an atrial dislodgement dataset of 14 LDs at the atrium.
In the registry dataset, the algorithm identified 20 of 21 radiographic LDs (95%) at a median of 11 days before clinical diagnosis. Step 1 had positive predictive values of 57% for radiographic LD and 77% for surgical revision. The false positive rate was 0.4% after step 1 and ≤0.2% after step 2. In the atrial dislodgement dataset, step 1 identified all 14 LDs; step 2 would have prevented inappropriate therapy in all 7 patients with stored EGMs at LD, including 2 patients with fatal, shock-induced VF.
An ICD algorithm can facilitate early diagnosis of defibrillation LD. Additional data are needed to determine the safety of withholding shocks based on EGM evidence of LD.
[Display omitted]</description><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Algorithms</subject><subject>Defibrillators, Implantable - adverse effects</subject><subject>Early Diagnosis</subject><subject>Electrocardiography</subject><subject>Female</subject><subject>Humans</subject><subject>Image Interpretation, Computer-Assisted</subject><subject>implantable cardioverter-defibrillator</subject><subject>lead dislodgement</subject><subject>lead displacement</subject><subject>lead migration</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Postoperative Complications - diagnosis</subject><subject>Predictive Value of Tests</subject><subject>Prosthesis Failure</subject><subject>Radiography</subject><subject>Ventricular Fibrillation</subject><issn>2405-500X</issn><issn>2405-5018</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kMtKw0AUQAdRbKn9AkG6dJN455HHLFxIWx9QcKPgbphMbsqEJFNnUqF_47f4ZaZWu3R1L5dzX4eQSwoxBZre1HGtDW5iBjSPgcdAkxMyZgKSKBlKp8cc3kZkGkINMCAsZ1SckxEHyqWQMCZiqX2zmy2sXncu2DBz1WyBlS28bRrdW9fNVqjLr8-FDY0r19hi11-Qs0o3Aae_cUJe75cv88do9fzwNL9bRYYnso8ENzwFBiLXrMBCQ5aipFlqdI5SZ6zUuTRVwSuacFFQITGTGkAj5Bx1wfiEXB_mbrx732LoVWuDweGwDt02KAaSc8iTXAwoP6DGuxA8Vmrjbav9TlFQe2OqVj_G1N6YAq4GHUPX1e-CbdFieez58zMAtwcAhzc_LHoVjMXOYGk9ml6Vzv674BueI3y7</recordid><startdate>201808</startdate><enddate>201808</enddate><creator>Zaman, Junaid A.B.</creator><creator>Chua, Kelvin</creator><creator>Sovari, Ali A.</creator><creator>Gunderson, Bruce</creator><creator>Gang, Eli S.</creator><creator>Ploux, Sylvain</creator><creator>Swerdlow, Charles D.</creator><general>Elsevier Inc</general><scope>6I.</scope><scope>AAFTH</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>201808</creationdate><title>Early Diagnosis of Defibrillation Lead Dislodgement</title><author>Zaman, Junaid A.B. ; Chua, Kelvin ; Sovari, Ali A. ; Gunderson, Bruce ; Gang, Eli S. ; Ploux, Sylvain ; Swerdlow, Charles D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c359t-43c3602048a2beba076e9176ca8e9a72da89cfb3f1534b149e79a00ae083eab23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Algorithms</topic><topic>Defibrillators, Implantable - adverse effects</topic><topic>Early Diagnosis</topic><topic>Electrocardiography</topic><topic>Female</topic><topic>Humans</topic><topic>Image Interpretation, Computer-Assisted</topic><topic>implantable cardioverter-defibrillator</topic><topic>lead dislodgement</topic><topic>lead displacement</topic><topic>lead migration</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Postoperative Complications - diagnosis</topic><topic>Predictive Value of Tests</topic><topic>Prosthesis Failure</topic><topic>Radiography</topic><topic>Ventricular Fibrillation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zaman, Junaid A.B.</creatorcontrib><creatorcontrib>Chua, Kelvin</creatorcontrib><creatorcontrib>Sovari, Ali A.</creatorcontrib><creatorcontrib>Gunderson, Bruce</creatorcontrib><creatorcontrib>Gang, Eli S.</creatorcontrib><creatorcontrib>Ploux, Sylvain</creatorcontrib><creatorcontrib>Swerdlow, Charles D.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>JACC. Clinical electrophysiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zaman, Junaid A.B.</au><au>Chua, Kelvin</au><au>Sovari, Ali A.</au><au>Gunderson, Bruce</au><au>Gang, Eli S.</au><au>Ploux, Sylvain</au><au>Swerdlow, Charles D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Early Diagnosis of Defibrillation Lead Dislodgement</atitle><jtitle>JACC. Clinical electrophysiology</jtitle><addtitle>JACC Clin Electrophysiol</addtitle><date>2018-08</date><risdate>2018</risdate><volume>4</volume><issue>8</issue><spage>1075</spage><epage>1088</epage><pages>1075-1088</pages><issn>2405-500X</issn><eissn>2405-5018</eissn><abstract>This study sought to develop and evaluate an algorithm for early diagnosis of dislodged implantable cardioverter-defibrillator (ICD) leads.
Dislodged defibrillation leads may sense atrial and ventricular electrograms (EGMs), triggering shocks in the vulnerable period that induce ventricular fibrillation (VF).
We developed a 2-step algorithm by using experimental lead dislodgements (LDs) at ICD implantation and a control dataset of newly implanted, in situ leads. Step 1 consisted of an alert triggered by abrupt decrease in R-wave amplitude and increase in pacing threshold. Step 2 withheld therapy based on ventricular EGM evidence of LD identified from experimental LD behavior. We estimated the algorithm’s performance using a registry dataset of 3,624 new implantations and an atrial dislodgement dataset of 14 LDs at the atrium.
In the registry dataset, the algorithm identified 20 of 21 radiographic LDs (95%) at a median of 11 days before clinical diagnosis. Step 1 had positive predictive values of 57% for radiographic LD and 77% for surgical revision. The false positive rate was 0.4% after step 1 and ≤0.2% after step 2. In the atrial dislodgement dataset, step 1 identified all 14 LDs; step 2 would have prevented inappropriate therapy in all 7 patients with stored EGMs at LD, including 2 patients with fatal, shock-induced VF.
An ICD algorithm can facilitate early diagnosis of defibrillation LD. Additional data are needed to determine the safety of withholding shocks based on EGM evidence of LD.
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subjects | Aged Aged, 80 and over Algorithms Defibrillators, Implantable - adverse effects Early Diagnosis Electrocardiography Female Humans Image Interpretation, Computer-Assisted implantable cardioverter-defibrillator lead dislodgement lead displacement lead migration Male Middle Aged Postoperative Complications - diagnosis Predictive Value of Tests Prosthesis Failure Radiography Ventricular Fibrillation |
title | Early Diagnosis of Defibrillation Lead Dislodgement |
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