CREATIVE CONCEPTS

Cardiac Rhythm Device Identification Algorithm using X-Rays:CaRDIA-X

Sony Jacob, MD, Muhammad A. Shahzad, MD, Rahul Maheshwari, BS, Sidakpal S. Panaich, MD,Rajeev Aravindhakshan, MD

From the Division of Cardiology/Electrophysiology, Department of Internal Medicine, Harper University Hospital, Wayne

State University, Detroit, Michigan.

IntroductionA 75-year-old woman with a dual-chamber pacemaker wasseen in the cardiology clinic for possible device malfunc-tion. The patient’s device identification card revealed that apacemaker from “Manufacturer A” was implanted in 2001.However, device interrogation using the corresponding pro-grammer failed to communicate with the device. Given theage of the device, complete depletion of the battery wassuspected and the patient was thus referred for pacemakergenerator change.

On the day of the surgery in the holding area, uponinspection of the pacemaker implantation site, existence of2 healed scars side by side raised the suspicion of a previousgenerator change out or revision of leads. However, thepatient did not recall any such procedures; therefore all ofthe 5 major manufacturers were contacted. Manufacturer Aconfirmed the information in the identification card,whereas the others showed no record of the patient. Never-theless, the second scar at the device site still remained aquestion. Although the decision regarding the pacemakergenerator change was acceptable, the possibility of a mis-taken device manufacturer identity could not be completelyruled out. The patient’s chest X-ray with the pacemakerimage was compared with other patients’ X-rays withknown pacemakers for possible manufacturer identification.Similarities with one of the other manufacturer’s (“Manu-facturer B”) X-ray pacemaker image prompted device in-

KEYWORDS Radiological identification; Pacemaker; Implantable cardio-verter-defibrillator; Implantable loop recorder; Cardiac rhythm manage-ment devicesABBREVIATIONS ANC � alphanumeric codes; CaRDIA-X � CardiacRhythm Device Identification Algorithm using X-rays; CRMD � cardiacrhythm management device; EMR � electronic medical records; ICD � im-plantable cardioverter-defibrillator; IEAP � industry-employed allied pro-fessionals; ILR � implantable loop recorder; PM � pacemaker (HeartRhythm 2011;8:915–922)

Address reprint requests and correspondence: Dr. Sony Jacob, Assis-tant Professor, Division of Cardiology/Electrophysiology, Wayne StateUniversity, Harper University Hospital, 3990 John R street, Detroit, Mich-igan 48201. E-mail address: jacobsony@yahoo.com. (Received November

12, 2010; accepted January 4, 2011.)

1547-5271/$ -see front matter © 2011 Heart Rhythm Society. All rights reserved

terrogation using the corresponding programmer, whichrecognized a functioning device from Manufacturer B. Fur-ther investigation with Manufacturer B revealed that thepatient demographics had been erroneously documented atthe time of implantation, thereby causing the dilemma.

Clinical problemThe number of pacemakers (PMs), implantable cardio-verter-defibrillators (ICDs), and implantable loop record-ers (ILRs), collectively called cardiac rhythm manage-ment devices (CRMD), implanted each year hasincreased exponentially,1 and their management now ex-tends across a continuum of clinical care settings andproviders. Optimal care of such patients requires correctand timely identification of their implanted CRMD, es-pecially when device interrogation is warranted.2 This isperformed using manufacturer-specific device program-mers designed to communicate only with CRMDs fromthe corresponding manufacturer. The clinical vignettepresented above exemplifies one of the many devicemanagement conundrums that physicians may face dur-ing care of patients with implanted CRMD.

We surveyed over 50 physicians from different medicalspecialties in an inner-city hospital to assess the frequencyof patients with CRMDs encountered in their clinical prac-tice. Approximately 80% of the physicians acknowledgedfrequent such patient encounters, difficulties in CRMDmanufacturer recognition, and the need for a better CRMDidentification method. Additionally, a second survey com-posed of a 5-item, self-administered questionnaire was con-ducted among 105 industry-employed allied professionals(IEAP). A high proportion (49.4%) of the 75 respondentsindicated that they received �5 calls per month for deviceidentification, more commonly from emergency rooms(32%) and operating rooms (20%). A number of those calls(up to 3 to 4 per month) were directed to the wrong man-ufacturer IEAP, resulting in significant time delays (�20minutes per 35.3% of the respondents) because cross-check-ing with other manufacturers was needed. Additionally, anaverage of 1 to 2 times per month, a wrong device was

discovered only after attempting CRMD interrogation at the

. doi:10.1016/j.hrthm.2011.01.012

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916 Heart Rhythm, Vol 8, No 6, June 2011

patient bedside. All of these clearly indicate the magnitudeof this clinical problem and perhaps the need for an easy-to-use CRMD identification tool.

Current CRMD identification techniques andlimitationsAlthough several manufacturers were in the CRMD in-dustry over the years, mergers and acquisitions evolvedto the current 5 major manufacturers: Medtronic, St. JudeMedical, Boston Scientific, Biotronik, and Sorin (Figure1). Techniques to identify the CRMD from the abovemanufacturers include using the patient’s identificationcard, electronic medical records (EMR), manufacturers’patient registries, device-specific radiopaque alphanu-meric codes (ANC), and other nonconventional methods.Patients are provided with a CRMD identification card atthe time of device implantation, although they may nothave it at their disposal all the time. CRMD manufactur-ers also maintain their own in-house registry of patientsimplanted with their devices and provide 24-hour tele-phone technical support.3 However, manufacturer main-tained registries and hospital EMRs may sometimes bemisleading, particularly if the patient information hasbeen omitted or erroneously entered into the database, asseen in the clinical vignette above.

The radiopaque ANC marked into the device for identi-

Figure 1 Current device manufacturers. A chronological history of mformation of the current 5 major transnational manufacturers in the market trhythm management device, PM � Pacemaker, ICD � Implantable Card

fication4 is unique for each manufacturer. However, its

isibility is highly dependent on the X-ray image quality,nd its clinical utility has not been substantiated by anyublished study. Three physicians at our institution, blindedo any relevant patient data, reviewed more than 1,000-rays of patients with implanted CRMDs using the stan-ard-resolution hospital EMR system. The results revealed20% accuracy with significant interobserver and intraob-

erver variation in device identification due to their inabilityo clearly visualize the ANC on the chest X-rays. Thelinical value of ANC without high-resolution magnifica-ion is thus too low to justify its routine use in devicedentification.

Although the manufacturer-specified pacing mode andate response upon magnet application might be used todentify the pacemaker manufacturer, the magnet responsef different CRMDs is varied and complex to interpret. Arial-and-error method of interrogating a device using pro-rammers from all of the manufacturers until one of themecognizes the CRMD is another unconventional approach.owever, this not only is cumbersome, but also may failhen the CRMD battery is depleted. Furthermore, it mayave unwanted effects, including switching off defibrilla-ion therapy5 in certain ICD models.

Each of the previously described CRMD identificationtechniques is thus fraught with different problems. An ex-

nd acquisitions among CRMD manufacturers from 1949 leading to theraphs represent their U.S. and worldwide market shares. CRMD � cardiacDefibrillator.

ergers aoday. G

tensive literature search did not identify any published tech-

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917Jacob et al Radiological Identification of Cardiac Rhythm Devices

nique or algorithm for comprehensive identification of theCRMD and/or their respective manufacturers. Delays orerrors in device identification in various clinical situationsmay jeopardize timely patient care and may negativelyimpact health care costs. Hence, there is scope and need fora more reliable and easy to use CRMD identification tech-nique to facilitate timely, efficient, and cost-effective man-agement of patients implanted with CRMD.

Solution: Cardiac rhythm device identificationalgorithm using X-raysChest X-ray offers an untapped, easily available tool thatcan help reliable identification of the type and manufacturerof CRMD (Figure 2). Each CRMD has certain distinctivemorphological features that make its radiological identifi-cation possible. This prompted us to develop and validate analgorithm, Cardiac Rhythm Device Identification AlgorithmUsing X-rays (CaRDIA-X), for radiological identificationof CRMDs (Figure 3).

Development of the CaRDIA-X algorithmWe retrospectively analyzed over 2,200 chest X-rays ofpatients implanted with CRMDs from the 5 major manu-facturers. The study protocol was approved by the institu-tional review board. While systematically reviewing eachX-ray, unique morphological characteristics that help dis-tinguish the type and manufacturer of each CRMD were

Figure 2 A: Chest X-ray of a patient with a biventricular implantable carnd left ventricle (LV) leads connected to the header of the device. The RVSVC) coil. The subcutaneous (SC) coil is connected to the SVC port in throm the previous pacemaker implantation. B: Transoma Medical (Sleutransvenous leads. C, D: Side-by-side images of radiological and gross aefibrillators (St. Jude Medical PromoteTM).

identified. The information thus gathered was summarized

into tabular form, which was subsequently conceptualizedinto the CaRDIA-X algorithm.

Although it appears complex, CaRDIA-X is a simple yetcomprehensive stepwise CRMD identification algorithm.The first step is to see whether the patient has a deviceidentification card or knows the device manufacturer. Ifsuch information is not available, then access or obtain achest X-ray (step 2). Step 3 involves identifying the ra-diopaque manufacturer-specific ANC; if not identifiable,then proceed to step 4.

This step is crucial for determining the type of the deviceimplanted: ICD, pacemaker, or ILR. It involves the analysisof both the leads and the CRMD “can”. The tachytherapyleads that are unique to ICDs are distinguished from brady-therapy leads by the presence of single or dual endovascularor sometimes subcutaneous high-voltage defibrillation coils.These coils are characterized by thickened radiopaque por-tion of the lead body (Figure 2). However, caution must beused because rarely, a pace-sense component of a pre-existent tachytherapy lead from a previously implanted ICDmay be connected to a new pacemaker when an ICD is nolonger indicated. On the other hand, bradytherapy leadshave a uniform radiopaque body and represent a pacemakerlead. The newer magnetic resonance imaging–compatibleMedtronic bradytherapy leads have a characteristic ra-diopaque marking (Online Supplementary Figure 1 and Fig-

r-defibrillator (BiV ICD). Note the right atrium (RA), right ventricle (RV),as a combination of RV pace/sense lead, RV coil, and superior vena cava

. Another set of RA and RV abandoned pace sense leads can also be seenantable loop recorder (ILR). Note the flexible sensor (antenna) with noce of a pacemaker (Medtronic AdaptaTM) and implantable cardioverter-

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The CRMD casing (can) houses a battery (cell), capac-itor, circuitry, and connector pins and forms a specificpattern radiographically. This can, cell, capacitor, circuitry,and connector configuration (5-C configuration) or pattern,which is unique for each manufacturer’s device, supple-ments the ICD, PM or ILR identification pathways. Thebattery forms the main radiopaque shadow in any CRMD,whereas the capacitor, which is unique to an ICD, forms thesecond radiopaque shadow (Figure 2). Thus, a single ra-diopaque shadow is characteristic to PMs or ILRs. A singlesemilunar-shaped battery shadow confirms a PM, whereas asingle circular or quadrangular shadow represents an ILR.The presence of more than 1 radiopaque shadow and ahigh-voltage coil always confirms the presence of an ICD.Once the type of the device has been identified, proceed tostep 5 of the corresponding PM, ICD, or ILR pathway.

ILR pathwayThe presence of a flexible antenna confirms a Sleuth ILR(Transoma Medical). The St. Jude Medical (Confirm) andMedtronic (Reveal) ILRs lack any flexible antennae andradiographically bear resemblance to a cricket bat and USBflash drive, respectively.

ICD pathwayStep 5 is to assess the shape of the ICD battery: square(Biotronik or St. Jude Medical [UnifyTM/FortifyTM]), nearsquare with a curved side (St. Jude Medical), rectangle(Boston Scientific or Medtronic), pie-shaped (Boston Sci-entific) and other shapes (Sorin). In addition to the batteryshape, step 6 includes finding similarity of the shape of theICD can or portion of the device to common real-life ob-jects. A pie-slice or pie-chart shape is characteristic ofBoston Scientific ICDs, whereas a similarity to a U-shaped magnet confirms a Medtronic or the St. JudeMedical (UnifyTM/FortifyTM) ICDs. Other St. Jude Med-ical ICD models have an egg-shaped can. A similarity to acoronal section of a human brain may favor Sorin ICDs(Ovatio/Paradym), whereas Biotronik ICDs have similarityto a bird, as shown in the algorithm. A few older models ofICDs from Medtronic (Gem VR/DR), Guidant Ventak Miniand Sorin (Alto) resemble the shape of a hip flask.

Pacemaker pathwayStep 5 is to analyze the orientation of the header (Figures 2and 3) to the straight side of the semilunar battery within thecan. The header could either be parallel (Boston Scientificor Sorin) or perpendicular to the straight side of the battery(any manufacturer). In some other older Vitatron or Inter-medics models, it may be angled. In the next step, the shapeof the can could be compared with other common real-life

Figure 3 CaRDIA-X algorithm. The algorithm showing different stepsnot labeled. See text for detailed explanation. BiV � biventricular; CaRDIAhamber; DOI � Date of implantation; DF4 � New type ICD DF4 lea

mplantable loop recorder; PM � pacemaker; SC � single chamber; USB � uni

objects for easy identification as shown in the figure: sun-glasses (Boston Scientific), wine glass (Sorin), purse ormango shapes (St. Jude Medical), and a bird shape (Biotro-nik).

Some models of PMs have a very similar radiopaqueappearance, hence additional steps have been incorporatedinto the algorithm for when further discrimination betweenvarious PMs is difficult. When the header is perpendicularto the straight side of the battery, analyze the upper borderof the can. A nonstraight upper border may imply a St. JudeMedical (purse or mango shape) or a Biotronik (bird shape)PM. Additionally, the angle at the top of the can is muchmore pronounced in St. Jude Medical PMs as opposed toBiotronik PMs. However, if the upper border of the can istraight, the subtle differences in the lower right border ofhe PM can should be carefully analyzed (refer to pictorialescription in the algorithm). Furthermore, key distinctiveeatures described by us as “birth marks” are found to beharacteristic of PMs from different manufacturers in addi-ion to quite distinctive connector pin configurations uniqueo each manufacturer. For example ‘Medtronic Dots’, ‘St.ude Spot’, ‘Biotronik Halo’, and ‘Sorin Square’ (Figure 3).nline Supplementary Figure 1 and Figure 2 provide de-

ailed template shapes and corresponding X-ray images ofarious CRMDs to help further discriminate the CRMDs.

Validation of the CaRDIA-X algorithmStudy designBased on the results of our preliminary survey, the algo-rithm was validated among physicians who were most likelyto encounter patients with CRMDs in their practices. Fivespecialty groups of 3 physicians each (emergency room,cardiology, internal medicine, anesthesiology, and radiol-ogy) with an additional 6th nonclinical group of 3 graduatestudents for comparative analyses constituted the study par-ticipants. The validation was conducted in a 2-step process:CaRDIA-X training with pretraining and posttraining as-sessment phases and the final testing phase. All study par-ticipants were initially assessed using 25 selected X-rayimages (N � 12 ICDs, 12 PMs, and 1 ILR) to identify theCRMD type and manufacturer. Subsequently, each partici-pant group was given repetitive training by a single instruc-tor on how to use the CaRDIA-X algorithm to identify theCRMD. This was followed by posttraining assessment ses-sions until �85% correct CRMD identification wasachieved by all of the study participants in each group. Thisallowed for standardized measurement of training effective-ness and avoided a learning curve during final testing. In thefinal testing phase, participants were tested on another care-

y device identification. ICD, PM, and ILR pathways are incorporated butardiac Rhythm Device Identification Algorithm Using X-rays; DC � dualctor pin standard; ICD � implantable cardioverter-defibrillator; ILR �

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920 Heart Rhythm, Vol 8, No 6, June 2011

fully selected library of 208 X-rays, composed of ICD (N �98), PM (N � 100), and ILR (N � 10) images.

Each X-ray was presented in a random sequence duringpretraining and posttraining assessment sessions to all par-ticipants. All X-rays were DICOM (Digital Imaging andCommunications in Medicine) images accessed using thehospital EMR with a standard screen resolution and viewingdistance. The quality of the X-rays varied with each sample,during both training and testing sessions, to simulate areal-life clinical setting. Repeated images of various makesof the devices were presented to the readers, resulting inN � 3 � 6 exposures. This amplified the statistical poweror measuring the effectiveness of our training protocol andlso for detecting the effects of various device or readerarameters on CRMD identification during the final testinghase.

Statistical analysisThe study participants were expected to identify theCRMD type (ILRs, PMs, and ICDs) and manufacturerfrom the X-ray images. Only a correctly identified devicetype and manufacturer corresponded to a “correct iden-tification” in this context, whereas an incorrect identifi-cation of either the device type or the manufacturer wasa “false identification.” Sensitivity of detection of a spe-cific device was calculated as the proportion of correct

Figure 4 Scatterplot showing the CRMD identification test resultsagainst the false positivity rates for each of the devices in the study: STransoma Medical. CaRDIA-X � Cardiac Rhythm Device Identifica

ice, PM � Pacemaker, ICD � Implantable Cardioverter Defibrillator

identifications of the manufacturer from the whole set of

X-rays for the corresponding device type category. Falsepositivity rate was calculated as the proportion of in-stances in which a device/manufacturer was identifiedwhen a different device was presented. A scatterplot wasprepared with sensitivity versus false positivity for eachdevice/manufacturer.

Combined error rates or false negativity (proportion ofcases in which the reader identified the device as belongingto another manufacturer or even belonging to another devicetype altogether) were additionally calculated for ICDs andPMs for each group of readers. The chi-square test wasperformed to find the differences between reader categoriesin terms of identification of various manufacturers’ devices.A P value of .05 was considered statistically significant.Statistical analysis was performed using SPSS version 17(SPSS, Inc., Chicago, IL).

ResultsThere was significant improvement in the correct identi-fications between pretraining and posttraining assessmentsessions using 25 X-rays among all of the readers. Thescatterplot further compares the sensitivity and false pos-itivity in identification of the devices in the final testingsession (Figure 4). This directly indicates the strength ofCaRDIA-X in training the study subjects to confidentlydifferentiate the device type and manufacturer. Com-

aRDIA-X. The scatterplot of the sensitivity for device identificationMedical, Biotronik, Boston Scientific, Sorin Medical, Medtronic, andlgorithm Using X-rays; CRMD � cardiac rhythm management de-

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921Jacob et al Radiological Identification of Cardiac Rhythm Devices

arately among the 6 categories of readers. The internalmedicine group was the furthest in terms of accuracyfrom the radiology group, which showed the maximumaccuracy in identification (Figure 5). The difference incombined error rates among readers was significantlydifferent (P �.011) with regard to the pacemakers. How-ver, this was not so pronounced in the case of ICDs (P �077). Finally, an overall accuracy (all groups pooled) of6.9% was achieved using the CaRDIA-X algorithm.

DiscussionIdentification of implanted CRMDs sometimes presents asignificant clinical burden to the care providers and a chal-lenge to currently stretched health care costs. Radiographicimaging promises reliable and accurate identification ofimplanted CRMDs because a majority of the patients withCRMDs have a chest X-ray performed at some point in timeafter the device implantation. Although X-ray images havebeen previously used to differentiate CRMDs,6 CaRDIA-Xis the first comprehensive algorithm developed and tested.Radiological CRMD identification may lead to better pa-tient care by avoiding any delay in interrogating the devices.This will also reduce hospital costs and other indirect pa-tient expenditures in addition to service cost reduction forthe device manufacturers, because unnecessary IEAP visitscould be avoided. This is especially important in the currentdevice market economics, which reflect a mismatch be-tween the efforts to reduce CRMD prices and increasingservice costs faced by manufacturers.

To assess the comprehensibility of CaRDIA-X, a post-validation survey of the participants was conducted. Ananonymous, 4-item, self-administered questionnaire surveyassessed on a 5-point Likert scale was used for this purpose;50% of the 18 respondents agreed that the algorithm ap-

Figure 5 Combined error rates of CRMD identification using CaRDIA-X.The combined error rates (%) of different groups of readers are plotted forimplantable cardioverter-defibrillators (ICDs) and pacemakers (PMs) sepa-rately. The internal medicine group was the furthest from the radiology groupin terms of accuracy for differentiation of devices and/or manufacturers.Ane � anesthesiologists; Card � cardiologists; CaRDIA-X � Cardiac

hythm Device Identification Algorithm using X-rays; CRMD � cardiachythm management device; ER � emergency medicine; IM � internaledicine; NC � nonclinical group; Rad � Radiologists.

peared complex initially, but during the training session a p

high proportion (81.3%) of the respondents found it quiteeasy to understand and learn. All of the respondents agreedthat they were extremely comfortable in applyingCaRDIA-X for CRMD identification during testing.

An online version of CaRDIA-X, supplemented by acontinually updated library of both illustrations and radio-graphic images of new CRMD models by their respectivemanufacturers, will provide up-to-date information aboutnew and even future CRMD models in advance. The high-resolution downloadable CaRDIA-X algorithm, illustra-tions, and table would allow medical personnel to print largeposters for easy viewing in any clinical setting.

Study limitationsWill we be able to identify all CRMDs with ease usingCaRDIA-X? For most purposes, the answer is yes, butthere are some considerations that should be borne inmind while applying the algorithm. Quality of the chestX-rays, rotation, position or tilt of the device, and under-penetration or overpenetration of the X-ray images couldaffect the CaRDIA-X interpretation. Likewise, unavoid-able confounding factors such as stress, anxiety, andemergent situations encountered during real-life clinicalpractice may affect the accuracy of the algorithm. Addi-tionally, use of CaRDIA-X entails a certain degree ofpreliminary training for appropriate understanding andapplication of the algorithm that might not interest somemedical personnel.

Furthermore, CaRDIA-X is not designed to identifysome of the older CRMD models. However, as comprehen-sively elaborated in Figure 1, the current CRMD manufac-turers have been the only ones in the market for the last 13years.7-11 Although possible, given the average life of

RMDs, it is unlikely to see older device models. Otherlectronic implantable devices that resemble CRMDs, suchs newer investigational heart failure monitoring devices,T-segment monitoring devices, and other pacing or stim-lating devices (e.g., devices for refractory hypertension,hronic pain, etc.) have not been incorporated into CaR-IA-X. Rarely, physicians might encounter patients im-lanted with CRMDs from smaller local manufacturers inther countries, e.g., CCC (Uruguay) and Medico (Italy),hat are not included in our database.

Pacemakers were more frequently mistaken than ICDs in ourtudy. It was plausibly due to analogous outlines of the deviceans, header orientation, and similarities in the 5-C configuration.he most frequently mistaken devices in the study included somef the PM models from Biotronik and St. Jude Medical, whichhare similar shape and pattern. PMs from Biotronik, Bostoncientific, Sorin, and Medtronic with a straight upper border of thean were mistaken due to close resemblances both in can shape

and 5-C configuration. Among ICDs, newer St. Jude Medicaldevices (UnifyTM and FortifyTM) were mistaken for MedtronicCDs, which share a similar shape (U-shaped magnet). Despitehese considerations, a high overall accuracy and discriminabilityf the CaRDIA-X achieved during validation of the algorithm

romises precise identification of implanted CRMDs.

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Future directionsLarger and easily visible radiopaque alphanumeric identifi-ers (e.g., SJI for St. Jude Medical ICDs or MP for MedtronicPMs) if incorporated during device manufacturing will bethe simplest yet most logical innovation to identify CRMDs.However, during the interim, Automated CaRDIA-X (A-CaRDIA-X) utilizing edge-detection technology and patternrecognition algorithms permitting automated CRMD recog-nition from X-rays is a promising possibility. Mobile com-puting platforms supporting this technology could be devel-oped for handheld devices.

ConclusionIdentification of CRMDs is a common problem frequentlyencountered by physicians in various clinical settings. Ra-diological identification opens a new avenue, with teleradi-ology specifically holding promise as a reliable and rationalarbiter for precise, timely, and cost-effective CRMD recog-nition. It offers a readily available and more realistic ap-proach over the existing diagnostic armamentarium, therebyminimizing any wrongful assumptions that could negativelyimpact patient care. Although the next-generation EMRwould likely improve the situation, it would entail a con-certed multidisciplinary approach from the industry, hospi-tals, and physicians to achieve this goal.

AcknowledgementsWe thank Mary C Myrand (WSU School of Medicine),Matthew Keighley (Biotronik),Tony Murry (Boston Scien-tific), Jason Mckelvey and John Biolchini (Medtronic),

Steve Kozlowski and Jim Young (Sorin Group), Michael

Mault and Michael Freeland (St Jude Medical) for their helpduring the preparation of the CaRDIA-X table and illustra-tion.

AppendixSupplementary dataSupplementary data associated with this article can be found,in the online version, at doi:10.1016/j.hrthm.2011.01.012.

References1. Kurtz SM, Ochoa JA, Lau E, et al. Implantation trends and patient profiles for

pacemakers and implantable cardioverter defibrillators in the United States:1993–2006. Pacing Clin Electrophysiol 2010 Jun 1;33(6):705-11.

2. Jacob S, Cherian PK, Ghumman WS, Das MK. “Pseudo” Faraday cage: asolution for telemetry link interaction between a left ventricular assist device andan implantable cardioverter defibrillator. J Interv Card Electrophysiol 2010Sep;28(3):221-5..

3. Stevenson WG, Chaitman BR, Ellenbogen KA, et al. Clinical assessment andmanagement of patients with implanted cardioverter-defibrillators presenting tononelectrophysiologists. Circulation 2004;110:3866–3869.

4. Pinski SL, Trohman RG. Implantable cardioverter-defibrillators: implicationsfor the nonelectrophysiologist. Ann Intern Med 1995;122:770–777.

5. Porres JM, Lavineta E, Reviejo C, Brugada J. Application of a clinical magnetover implantable cardioverter defibrillators: is it safe and useful? Pacing ClinElectrophysiol 2008;31:1641–1644.

6. McMullan J, Valento M, Attari M, Venkat A. Care of the pacemaker/implantablecardioverter defibrillator patient in the ED. Am J Emerg Med 2007;25:812–822.

7. St. Jude Medical: History. 2010. Available at: http://www.sjm.com/mediaroom/mediaroom.aspx?section�History. Accessed January 18, 2010.

8. Boston Scientific: History. 2010. Available at: http://www.bostonscientific.com/templatedata/imports/HTML/AboutUs/History/history.html. Accessed January 18,2010.

9. Biotronik: Our History. 2010. Available at: http://www.biotronik.ir/ourhistory.htm.Accessed January 18, 2010.

0. Sorin Group: History. 2010. Available at: http://www.sorin-crm.com/uploads/Media/crmpres.pdf. Accessed January 18, 2010.

1. Medtronic: Our Story. 2010. Available at: http://www.medtronic.com/about-

medtronic/our-story/. Accessed January 18, 2010.