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REPLACE DARE (Death After Replacement Evaluation) Score
DOI: 10.1161/CIRCEP.114.001671 REPLACE DARE (Death After Replacement Evaluation) Score: Determinants of All-Cause Mortality After Implantable Device Replacement Or Upgrade from the REPLACE Registry Running title: Chung et al.; Mortality after CIED Replacements Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 Mina K. Chung, MD1; Richard G. Holcomb, PhD2; Suneet Mittal, MD D3; Jonathan Jona Jo nath na than th an S S.. Steinberg, Sttein ein Kevi Ke vinn Mi vi Mitc Mitchell, tche tc h ll RN7; he MD3; Marye J. Gleva, MD4; Theofanie Mela, MD5; Daniel Z. Uslan, MD6; Kevin JJeanne Je an anne nn E E.. Po Poole, oole, e, M MD D8 ffor orr tthe h R he REPLACE EPLA LA LACE ACE Investigators* Inv nves esti es tiga g tors ga rs* s* 1 Cleveland landd Clinic, Clin Cl in nic ic, Cleveland, C ev Cl e ellan a d, d OH; OH; 2Mi Minnetonka, M nnet nn e oonnkaa, MN et MN; N; 3Va Valley V llley Health lley Hea ealt ltth System Syst Sy stem st em m and and Columbia Col olum u b 4 Washington shhin ingt gton U gt University, niversit i ity, it y S St. t. L Louis, University College y Colle l ge off Physicians Phhysiiciians & Surgeons, Surgeons, New New York, Yorkk, NY; NY; Wa Massachusetts M sett se ttss General tt Gene Ge nera ne r l Ho Hosp Hospital sppit ital al & Harvard Har arva vard va rd Medical Med e ic ical a School, al Sch choo oo ol, l, Boston, Bos osto ton, to n, MA; MA A;; 6Division of MO; 5Massachuse BIOTRONIK, BIOTRO BIOT OTRO OT RO Infectious Diseases, Geffen Diseases D isea is ease sess David Dav avid id G effe ef fenn School fe Scho Sc hool ho ol of of Medicine Medi Me dici di cine ci ne at at UCLA, UCLA UC LA Los Los Angeles, Angeles Ange An gele less CA; le CA; 7BI 8 Lake Oswego, OR; University of Washington, Seattle, WA *List of Investigators provided in supplemental material. Correspondence: Mina K. Chung, MD Department of Cardiovascular Medicine, Cleveland Clinic 9500 Euclid Avenue, J2-2 Cleveland, OH 44195 Tel: 216-444-2290 Fax: 216-636-6951 E-mail: chungm@ccf.org Journal Subject Code: [120] Pacemaker, [22] Ablation/ICD/surgery 1 DOI: 10.1161/CIRCEP.114.001671 Abstract: Background - Identifying factors predictive of mortality may be important to decrease risk associated with cardiac implantable electrical device (CIED) replacement procedures. This study aimed to determine whether clinical factors and complications independently associate with death and to develop a mortality risk prediction tool after CIED replacement. Methods and Results - The prospective REPLACE Registry determined 6-month complication and mortality rates after CIED replacement with or without planned lead addition or revision. Vital status was collected. Kaplan-Meier survival and multivariable Cox proportional hazards Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 regression analyses were performed to identify patient, procedural, or complication variables p predictive of death. The REPLACE DARE (Death After Replacement Ev Evaluation) score was Eval alua al uati ua tion ti on)) sc on sco ore wa ore a constructed using hazard ratios, reflecting relative risk contributions off each variable, combined h va vari riab ri ab ble le,, co comb m into an additive died. d ve mortality ditive mort mo r al rt a ityy risk r sk score equation. At 6 months ri months 70/1744(4.0%) 70/17444(4. 4..0%) patients had died d Cox regression analysis found major anaalysis foun nd noo significant sig ig gni nifi fiicant association asssocia iatiion between ia beetwe w en we nm ajjor ccomplications o pllicatio om tio ions n aand ns ndd ddeath. eaath h However, rec failure NYHA class III/IV, antiarrhythmic drug rrecent cen ent heart rtt fa ailuree aadmission, dm mis issi s onn, NY N HA A cla asss II II/IV II/ II V, ant tiaarrhhytthm mic ic dru rugg us ru use, cerebrovascular disease, and chronic disease were independently with 6c ar diseas cula a e,, an as nd chroni niic kidney nic y dis issea e se se st sstage ag ge we w re inde deepe penden en entl nt y as associated w month mortality. r i y. The rtalit Th REPLACE RE EPL PLAC ACE AC E DARE DA ARE score was 22.0±1.4 .00±1.44 iinn survivors surrvi v vors rss versus 33.5±1.8 .5± 5±11.8 in non5± n survivors (p<0.001) Risk pp<0.001) <0 0.0 .001 01)) with wiith t predictive pre redi d ct di ctiv i e ROC ROC value=0.758 valu va lue= e 00..75 7588 (p<0.001). (p<0 (p <0.0 <0 .0001 01). ). R iissk off death dea eath th h was was 1.0% 1.0 .0% % for f DARE=0 and 55.6% for DARE=7. The hazard ratio was 1.8 for each change of 1 DARE unit. Conclusions - Comorbidities, but not complications, were significantly associated with mortality after CIED replacement. The REPLACE DARE Score is a novel tool which can identify patients with substantial mortality risk. Such patients should have the relative risk and benefit of their procedure considered carefully. Clinical Trial Registration - clinicaltrials.gov; Unique Identifier: NCT00395447. Key words: implantable cardioverter-defibrillator, pacemaker, risk prediction, risk score, mortality 2 DOI: 10.1161/CIRCEP.114.001671 Cardiac implantable electronic device (CIED) replacements encompass a broad spectrum of patients with variable comorbidities. Most patients with pacemakers (PMs) and implantable cardioverter defibrillators (ICDs) will undergo one or more generator replacements. However, certain patients with multiple comorbidities being considered for replacement or upgrade procedures may face prohibitive risk or limited prognosis negating potential benefits. Similar clinical judgment is reflected in the mandate to withhold primary prevention ICD implantation if life expectancy is estimated to be under one year.1 Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 Few studies have evaluated mortality and associated risk factors rs followingg CIED D replacement or upgrade procedures. Advanced age, comorbid conditions, ons, and andd procedure pro roce ceddure du e related rel complications o s might ons migh mi ghtt contribute gh c nttribute to mortality. The RE co REPL REPLACE P ACE regis registry, stry,, a prospective multice multicenter e study that evaluated eva eva valuated patients patieents undergoing underg un rggoingg device dev evicee replacement repllaccem men nt w with itth th or wi with without hou out pl planned lan a need le lead ead addition orr revision, revis isiion is on, n provided p ovid pr id ded d a uniqu unique quue oppo opportunity ort r unnit ity to to examine exa xami xa mine mi ne thi this hiss question. hi questionn.2 T qu The he obj objectives bjecti bj tiv ti i of the current analys analyses y es wer were re to iidentify d ntif de ifyy cl if clinical liniicall or pr pprocedural ocedural d l ffactors actorss tthat hat ar aaree associ associated iatted dw with ith aallcause 6-month mortality mortality DARE onth nth th mortalit rttalit lit and ndd tto develop ddee elop lo a mortalit rttalit lit risk riiskk tool, ttooll designated desii atted d tthe he RE REPLACE REPL PLAC ACE E DA (Death After Replacement Evaluation) risk score. Methods The prospective multicenter REPLACE Registry2 determined 6-month complication rates after CIED replacement without (Cohort 1) or with (Cohort 2) planned transvenous lead addition or revision. Patients with anticipated life expectancy of <6 months or those undergoing a planned lead extraction procedure were excluded. Major and minor complications were pre-specified and independently adjudicated.2 All deaths during the 6-month follow-up were identified. Although procedure-related death was a major complication for the original analysis, it was not considered a complication for the purposes of this analysis, since only a complication that occurred prior to 3 DOI: 10.1161/CIRCEP.114.001671 death qualified as a potential risk factor for mortality. The mortality analysis considered each cohort separately as well as in combination. The REPLACE study was approved by the ethics committee of each participating institution; all patients provided written informed consent. Mortality analyses The primary outcome for this analysis was 6-month all-cause mortality. Vital status was collected for 100% of subjects. Univariable analyses examining the association of factors with 6-month all-cause mortality were performed, using Chi-squared or Fisher’s exact tests for Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 categorical and two-group Student's t-tests for continuous variables. Variables considered for mortality analysis included age, sex, race, bo mass index, bbody dy m dy asss in as inde dex de New York Hea Heart eart ea rt A Association s oc ss o iaati t on (NYHA) functional class, cla lasss, heart failure failur u e ho hhospitalization spitalization within the previous 12 months, ejection fraction coronary 2m onths, left ventricular venttric icular ar eject cttio on fra acttionn ((LVEF), LV VEF F),, PM M dependence, dep pende d nce, pprior de rior or co oroon artery bypass disease, ass graft grraf aftt (C ((CABG) ABG) AB G) or valvee su surgery, y pperipheral e iphe er iph ral ar art artery tery ddisease, isea is e se, cerebr ea cerebrovascular broovascula br l r di dis recent myocardial infarction, myocardial infarction, chronic obstructive o dia ocard i l infa f rccti tion, remote myo y carddia i l inf farcti tion, i chroni h niic ob obst structive pulmonary st p lm pu mon onaryy disease (COPD), diabetes (CKD) OPD) OP D) di ab bett mellitus, mellit elli llitt s chronic ch h nii kidney kid ki kidne dn disease dis (CK CKD) D) stage ta as defined defi fi d bby the the National Kidney Foundation classification3, liver disease, smoking, medications, anticoagulants, surgical time, any major complication, and any minor complication. Additional analyses of age were also performed in device subgroups. Device type variables considered were: implanted generator type (single or dual chamber PM, single or dual chamber ICD, cardiac resynchronization therapy PM (CRT-P) and/or ICD (CRT-D), and intended upgrade type (single to dual chamber PM or ICD, PM or ICD to CRT-P or CRT-D). Cumulative survival rates were calculated according to the Kaplan-Meier method. Event times were measured from the time of the study replacement procedure. The significance of 4 DOI: 10.1161/CIRCEP.114.001671 differences in survival between variables considered was assessed with the log-rank test. As the last follow-up at 6 months was ±4 weeks, Kaplan-Meier curves are displayed to 210 days. Univariable associations of baseline and patient factors to mortality were examined to identify candidate predictors (factors with univariable p-value<0.2). Multivariable Cox proportional hazards regression modeling used both backward elimination and forward stepwise Cox regression analyses to validate the robustness of significant predictor variables with an adjusted p<0.05 needed for entry into the model and an adjusted p>0.1 for removal at any stage. Relative Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 risks were expressed as hazard ratios with associated confidence intervals. vals. Baseline values for all candidate predictor variables used in thee survival surv rviv i all analyses iv ana naly lysees were ly w determined d att time tiime zero zer ero (date (d date of original replacement replacemen ent procedure),, including en inclluding complications. The presence orr ab absence complications included baseline bsence of com omplliccatio ons were weree includ udded d on on the the same ssaamee basis basiss as other otther ba base elinee predictors, sincee al replacement alll study studdy complications comp mpli l cati tion ti ons were on re those tho h se adjudicated ho adj djud dj udic ud icat ic ated at ed to to be be related rellated ed to to the th he replacem repl lacem procedure andd were assum assumed um med d to ha hhave ve an onset coin coincident cide id nt with wit ithh the th he procedure, p occed pr edure, regardless reg gardl dles dl e s of when es symptoms associated iattedd with iith th tthe he complications pli licati tio were ere reported. reported rtted d Results were considered significant at p<0.05. Values are reported as mean±standard deviation, unless otherwise specified. Statistical analyses were performed with SPSS statistical software (Version 18, SPSS/IBM, Inc.). Mortality Risk Prediction Score Using the subject factors found to be predictive of mortality in the multivariable Cox regression analysis, the REPLACE DARE mortality risk prediction score was developed. Hazard ratios reflected the relative risk contribution of each variable and were combined in a final additive score equation: Mortality Risk Score = ((3.097^ HF) + (1.959^NYHA) + (1.425^(CKD-1)) + (1.901^AAD) + 5 DOI: 10.1161/CIRCEP.114.001671 (1.801^CEREB) + (1.238^(AGE - 1))) - 6. The six variables identified to be predictive of survival included: 1) HF [admitted for heart failure in previous 12 months (0=No; 1=Yes)]; 2) NYHA [NYHA Class (0=0,I, II; 1=III,IV)]; 3) CKD [chronic kidney disease stage (1-5)]; 4) AAD [Class I or III antiarrhythmic drug use (0=No; 1=Yes)]; 5) CEREB [history of cerebrovascular disease (0=No; 1=Yes)]; 6) AGE [age quartiles (1= <63; 2= 63-72; 3=73-79; 4=80+]. A value of "1" was subtracted from CKD stage and age quartiles for scaling purposes; the Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 equation was standardized so that a subject with no risk factors, lowestt CKD stage, youngest stage g , and d yo you age quartile had a value of zero. To evaluate robustness eva vaalu luat atee th thee ro obustness of the predictorss used used in the REPLACE RE EPL LAC A E DARE Score, a bootstrapping estimating intervals ing validation was in was pperformed erfoormed d est tim mattin ng the th variability vari va riaabilitty andd confidence ri conf n iden nf nce c int ntervvals va associated with predictors 10,000 sampling w h th thee pr pred dic i tors bbased ased d oon n 10,0 000 ssimulated imullated ted d trials tri rial alss created crrea eate t d bby y sam ampl am pling with ith h replacement the original REPLACE Study patients. n from nt f th he or rig gin i all R EPLA EP LA ACE ES tudy d ppopulation dy oppulattion off 11744 7444 pa 74 pati tiients. Results REPLACE enrolled 1744 subjects undergoing CIED replacement into Cohort 1 (N=1031) and Cohort 2 (N=713).2 The previously reported complication rates in Cohort 1 included 134 total major plus minor complications in 111 patients (10.8% patient level complication rate). Of these, 51 major complications occurred in 41 patients (4.0%) and 83 minor complications in 76 patients (7.4%). In Cohort 2, 227 total major plus minor complications occurred in 149 patients (20.9% patient complication rate). These included 163 major complications in 109 patients (15.3%) and 64 minor complications in 54 patients (7.6%). Mortality after CIED replacement At 6 months, 70 patients had died (4.0%), 37(3.6%) in Cohort 1 and 33(4.6%) in Cohort 2, 6 DOI: 10.1161/CIRCEP.114.001671 p=0.32. Mean time from CIED replacement procedure to death was 100.3±62.3 days (median 100.5 days, range 3-212; interquartile range, 49-151 days). No deaths occurred during the actual replacement procedure. Fifteen deaths occurred by 30 days (30-day total mortality 0.9%) of which 8 were adjudicated as a major complication due to the procedure in the original analysis.2 Among patients who had a major complication, 10/190(5.2%) patients died and among patients who had a minor complication, 1/130(0.8%) patients died. Relationship of Patient Characteristics to 6-Month Mortality Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 Baseline patient characteristics and univariable analyses by 6-month survival urvival status (Table (Taabl blee 1) showed that patients who died were older, more likely to have diabetess me mellitus, ell llit itus it us, COPD, COPD CO PD,, PD c la cula larr di ddisease, seeas ase, pperipheral eripheral vascular disease, disease se, CKD, se CKD, prior CABG C BG CA B or valve surgery, prior p cerebrovascular forr heart failure failurre within wiith hin the the pas a t 122 months, monnth hs, and nd hhigher iiggherr NYHA NYHA HA ffunctional unctio io onal cclass lasss (a a admission fo past (all Averag ag ge ag age was ap approximat atel at ely 4 ye year rs higher h gh hi her iin n su ubj bjeccts who whho died die iedd (p=0.023). (p=0 (p 0.023 023 2 ). ) p<0.05). Average approximately years subjects 144% (N=248) (N=2 (N =2 2488) off sub bje jects iin n the h R E LA EP ACE E Registry Reg gistr trry had had been b en hhospitalized be ospi pita pi tali ta l ze li z d for f Although onlyy 14% subjects REPLACE re within iithin thiin tthe th he preceding di 112 2 months nth ths th these patients ti ts accounted acco nt nted ted d for f 43% 43% (N=30) ((N N 30 30)) off tthe th h 70 heart failure months, observed deaths. Patients who died were also more likely to be on an antiarrhythmic drug and on diuretics. Defibrillation testing was not significantly associated with higher mortality (p=0.40). Kaplan-Meier survival curves by clinical characteristics are shown in Supplemental Figures 1 and 2. There was also a significant and consistent increase in the risk of death associated with CKD stage from 2.3% (5/215 patients) for stage 1 to 16.0% (4/25 patients) for stage 5 (Supplemental Figure 2A). Relationship of CIED Type and Replacement Procedure to 6-Month Mortality In univariate analyses of survival status at 6 months (Table 1), patients with a CRT-P or CRT-D implanted had a higher observed mortality than those receiving a PM or ICD (CRT 6.2%, PPM 7 DOI: 10.1161/CIRCEP.114.001671 2.8%, ICD, 2.7%; between groups, p=0.003). Kaplan-Meier survival analyses (Figure 1), confirmed worse survival in patients who had CRT devices implanted compared with PMs or ICDs without CRT (p<0.001) and in patients upgraded to a CRT device (p=0.003). A significant difference by cohort was not demonstrated (p=0.27). Relationship of Complications to 6-Month Mortality Univariable associations of complications with mortality (Supplemental Table 1A) showed sixmonth mortality was 4.0% in patients without any major or minor complications during the study Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 and 4.3% in those who experienced any complications (p=0.73). Of the he 146 patients p tients with pa witth one o or more major complication, 6.8% of patients died. In contrast, among the 1598 patients who he 159 5998 pa pati tien ti entts ts w ho did not experience major (p=0.08). least e ce a m ence ajor aj or ccomplication, omplication, 3.8% died (p om p=0 =0.08). Of the 1300 ppatients atients who had at le e one minor complication, with 1614 with complication, 0.8% 0.8% % diedd compared comp mparred w ith 44.3% .3% 3% % ooff 16 6144 ppatients atien ntss w ith nno o mi minorr complications Deaths with complications shown Supplemental o (p=0.06). ons (p= (p =0.06). ) D eatths in patients paati tients w ithh major it majo j r co jo com mpli l cati li tion ti ons are sh on how own in S uppllem m Table 1B. Kapl Kaplan-Meier survival analysis major complications shown plan-Me pl M ie ierr survi ivall analy lysiis by occurrence off majo ly j r comp jo mp pliicatiions iiss sh show o n in Figure 1D and in Figure ndd bby any an ((major+minor) majj +miin ) complications li ti in Supplemental S pplemental pll tall Fi Fig re 33. Cox Proportional Hazards Regression Analysis Candidate variables associated with mortality with univariable p<0.2 were considered in Cox regression models. A total of 26 baseline variables were identified as candidates for inclusion in the multivariable models. As this was a large set of potential predictors relative to the number of mortality events, attention was paid to the direction and consistency of the effect of individual variables across sets of predictor variables. Both forward and backward stepwise elimination was used to confirm a robust set of predictors. Cox multivariable regression (Table 2) identified 5 significant predictors of survival time: admission for heart failure in the prior 12 months, NYHA class III/IV, antiarrhythmic drug use, cerebrovascular disease, and CKD stage. Although there 8 DOI: 10.1161/CIRCEP.114.001671 was some statistical evidence that the effect of these baseline predictors were time-dependent in an examination of the proportional hazards assumption, the interactions of time with the predictors had associated hazard ratios nearly equal to unity in each case (0.99 – 1.01) and were not included in the final model. Age and CKD were highly correlated (p<0.001) with a linear regression predicted age increase of 5.88 years per increase of each CKD stage. Age in quartiles met model parameter retention criteria and was retained in the final model (p=0.065) for risk score generation. Notably, neither the occurrence of a prior major or minor complication was a Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 significant multivariate predictor of mortality. None of the following factors were retained retaine nedd in the ne final Cox regression model: prior major complications, prior major or min minor nor ccomplications, ompl plic licat atio ionns io ns upgrade to CR CRT, RT, upgrade uppgr g ad adee to t an ICD, or device typee iimplanted. mplanted. Analyses of Age Device Subgroups of A ge in Devic ice Su Sub bgro roups ro Additional analyses performed whether significant analy lyse ly sess of age were perf se rfor rf ormedd to or to determine determiine wh de det whet ethher ad et advanced d aage g was a si ge igni predictor off mortali CIED mortality lity li ty iinn cohort cohort or CI IED ssubgroups. ubgr bg oups p . Age Ag di ddistribution isttribu b tiion by by cohort coho h rtt iiss shown show sh ownn in ow Supplemental ntal nt tall Figure Fig re 4A. Fi 4A Kaplan-Meier Kaplan K apll M Meier eii ssurvival r i all analyses anal all ses (Supplemental (S pplemental pll tall Figure Fig re 4B-J) Fi 4B JJ)) showed sho sh h that age was a significant univariate predictor of mortality in patients with implanted CRT devices (p=0.019). Multivariable Cox regression analyses (Supplemental Table 2) showed that age in quartiles was a significant predictor of mortality in the implanted CRT, upgrade to CRT, upgrade to CRT or ICD, and Cohort 2 subgroups, though not a significant predictor of mortality in the upgrade to ICD subgroup. The REPLACE DARE Mortality Risk Score Using the subject factors found to be predictive of survival in the multivariable Cox regression analysis in the total cohort, a mortality risk prediction score was developed. Included for analyses were 1662 subjects with complete data. The analysis included 95% of all patients and 9 DOI: 10.1161/CIRCEP.114.001671 96% of all deaths (67 of 70 patient deaths). Eighty-two subjects (5%) with missing GFR were excluded. The observed REPLACE DARE Mortality Risk Score had a mean value of 2.056±1.409 (range 0-7.32). Frequency distribution of the risk scores is shown in Figure 2A. Results of bootstrapping the Cox regression analyses in 10,000 simulated trials of the full REPLACE Study population (N=1744 patients) (Supplemental Tables 3A and 3B) demonstrated negligible bias of the originally estimated REPLACE DARE Score components (<4%), nearly identical p-values for statistical significance, and comparable coverage of the associated 95% Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 confidence intervals for the estimated hazard ratios. The performance of the derived mortality risk score (ability to predi predict dictt survival) di sur urvi viiva val) l) was was examined in number i a nu numb mber mb er off eevaluations. valuations. First, mean vvalues alues among ssurvivors urvi viivors and deaths (Table (Tabb 3A) demonstrated significant (p<0.001) with near doubling ted a highly sign te gnifiicaant difference diifferrence ce (p<0 <0.001 01) wi w th a ne ear do ear oubbliing off the t e risk th riisk score scorr between non-survivors survivors. Next, REPLACE o urv on-su rviv iv ivors v andd surviv i orss. N ext, tthe he RE REPL PL LAC ACE E DARE DARE Score Score variable var aria ar iaable was entered entte into a stepwise Cox regression the wise Co C x regr gres gr e siion with wit i h th he variables variiab bles pr ppreviously evio i usly l iidentified ly d nt de ntif ifiedd as if a ppredictors redi d ctorss (Table di (Taable 3B). (T After adjustment variable, stment st t ntt for f the the REPLACE REP EPLA LACE CE DARE DAR ARE E Score S ariable iabl bl none off tthe he other th predictors dictt were er retained. The REPLACE DARE Score variable was uniquely selected with either a forward stepwise or backward elimination approach. A third observation was that the score behaved in a monotonic fashion over the range of risk. [Figure 2B] The score values were rounded to simple integers for illustration, although using the score values rounded to the first decimal, in practice, could provide further resolution. Thus, for a subject at lowest risk (Score=0), the observed mortality in the REPLACE Study was 1.0% while mortality increased to 55.6% for a Score=7. The hazard ratio associated with the REPLACE-DARE Score was 1.795 for each change of one unit. The associated Kaplan-Meier survival graph by REPLACE-DARE Score is shown in Figure 2C. 10 DOI: 10.1161/CIRCEP.114.001671 Finally, a receiver operating characteristic (ROC) analysis characterized the sensitivity and specificity of the REPLACE DARE Score in predicting subjects who died (Figure 2D). The REPLACE DARE Score had a statistically significant predictive area under the curve value (c statistic = 0.758, p<0.001). LVEF was available for 56% of subjects, but prior admission for HF in the past 12 months in the REPLACE study was a better predictor of all-cause death than LVEF in cases where LVEF was available. When Cox regression analysis was limited to cases with Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 LVEF, hazard ratio estimates for the 6 identified predictors were comparable for parable to those fo or th tthe entire population, but LVEF was not a significant predictor: Prior admission dmisssio i n for forr HF hazard fo hazzar ha za ratio = 2.55, change When 5 p= 0.005; 5, 0.005 005 0 ; LVEF LV VEF hazard ratio=0.99 forr eevery very 10% cha hangge in LVEF, p=0.899. W adjusted for variables, significantly prediction or oother or ther variabl les, LV LVEF F ddid id nnot ot si ignif iffican ntly contribute co ont ntriibuutee to the th he pr predic ctiion o ooff aall-cause lll-cc death; thus,, LV LVEF was into mortality VEF w as not nott included inclludedd in int to the he mo m rtal t lit ityy score. scor ore. or Discussion n Although mortality rates have been well studied after initial PM or ICD implants, survival outcomes have not been well defined after device replacement procedures. Prior reported 1-year all-cause mortality rates after initial ICD implants in randomized clinical trials range from 2.610.7%4-7 and after PM implants 5.4-8.4%.8-10 In the REPLACE Registry, no deaths occurred during or within 24 hours of the replacement procedure. This sub-study demonstrated that allcause 6-month mortality after CIED replacement was 4%: 3.0% after PM, 4.7% after ICD and 6.2% after CRT device implants. Surprisingly, although major complications occurred in 8.6% of all patients followed in the REPLACE Registry and were associated with a strong trend toward higher 6-month mortality in univariate analyses, significant associations of complications with 6month survival were not observed in adjusted analyses. This may reflect the higher disease 11 DOI: 10.1161/CIRCEP.114.001671 burden of patients who experienced complications. Comorbid conditions, such as heart failure, kidney and cerebrovascular disease, rather than complications, were identified as the most likely contributors to mortality after CIED replacement procedures. Our study highlights the impact of heart failure as a significant predictor of 6-month mortality. Both prior admission for heart failure in the previous 12 months and NYHA functional class III/IV significantly predicted mortality. Prior heart failure admission significantly predicted mortality across CRT and upgrade subgroups. Although only 14% of subjects in the REPLACE Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 Registry had been hospitalized for heart failure within the preceding 12 2 months, these ppatients atie at i ie accounted for 43% of the observed deaths. Similarly 31% of the patients nts had had NYHA NYHA ffunctional unnct cti cti class III/IV heart failure deaths. V he ear artt fa ail i ur u e bu bbutt accounted for 60% of the the h observed de eaths h . The higher risk hs associated with complication mortality witth heart failure faillure is is concordant conncorddan ant with with ana aanalyses nallysses sess of acute acutee ccom om mplic ication cattion an aand dm mortalit orrtaalit risk analyses from National Cardiovascular Registry o the om the Na N tionall C ardi d ovas asccular as cu Data Data R egiisttry of eg o ICD ICD iimplants. m lants.111 Th mp The use off pri prior i heart failure re admission ad dmiissiion rather raath her than tha h n LVEF LV VEF F in in the th he riskk score mayy prove proove to to be b more clinically cllin nic i al a ly y uuseful and accessible. study, only patients; ible ibl ib le As As seen in in the the REPLACE REP EPLA LACE CE st t d LVEF LVEF was as available a ailable ilabl ble for f onl nll 56 56% % off patie ati tie re-assessment of LVEF is often not routinely performed prior to device replacement procedures. Moreover, LVEF was correlated with other variables, including prior admission for HF, and did not contribute independent information when the other variables were present in the model. That higher CKD stage was strongly associated with mortality after device replacement was not unexpected. Renal disease, and in particular end stage kidney failure requiring dialysis, has been associated with higher mortality rates and infections in patients with PMs and ICDs.12-14 In fact, the risk of excess mortality becomes evident at even a moderate level of renal dysfunction (<60 ml/min/1.73 m2).12 In our current prospective study, we found CKD to be a strong risk factor for mortality. 12 DOI: 10.1161/CIRCEP.114.001671 Patients with normal renal function (>90 ml/min/1.73 m2) and those with only mild CKD (60-89 ml/min/1.73 m2) had a 2 and 2.5% 6-month mortality, respectively. In contrast, mortality was 2fold higher with moderate (30-59 ml/min/1.73 m2), 4-fold higher with severe CKD (15-29 ml/min/1.73 m2), and nearly 8-fold higher with end-stage CKD. Remarkably, these differences in mortality as a function of CKD stage became evident by the first month following the CIED generator change. Future investigation should be directed towards identification of the mechanisms of death and reduction of mortality in CIED patients with moderate-end stage CKD. Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 Other significant factors associated with mortality were cerebrovascular ovascular diseasee aand n nd antiarrhythmic drug use. Present in 16% of the cohort, cerebrovascularr disea disease ease se w was as aassociated s oc ss ociia iat iat o the the deaths d at de a hs h and and n is not an unexpected risk sk factor for mortality. mo ortal allit ity. In the National with 27% of cular Data Reg cu gisstry y ((NCDR) NCDR NC CD ) ICD IC CD Regi giistry y, cerebrovascular ceere rebr brrovvasscularr ddisease isseaase wa w gniifii Cardiovascular Registry Registry, wass a sig significant 1 adv dvver erse see eve nts t or ddeath eath h rrelated elated el l d ttoo primary priimaryy pr pr rev even nti tionn IICD C iimplantation. CD mpla lant la ntation.15 nt predictor off adverse events prevention Antiarrhythmic h ic ddrug hmi rugg usee hhas as been been associated associatted d wi with ith hi higher high gh her ri risk iskk off m mortality orta tali ta liity t in pa ppatients tiients ts w with ith structural hheart e t di diseasee16 and ndd ma may bbe associated ciiatted d with ithh hi it higher gh h non non-cardiovascular cardio rdi dio asc lar l mortalit mortality. tali litt 17 A significant proportion of the REPLACE population was burdened with structural heart disease, including heart failure, which may predispose to proarrhythmia risks. Also, antiarrhythmic drug use may serve as a marker for higher disease burden, including atrial fibrillation or ICD shocks, both factors that have been associated with higher risk of mortality.18, 19 In the total cohort older age showed a trend toward higher mortality after CIED replacement (adjusted p=0.065) with the oldest quartile (age 80) being at highest risk for 6month mortality. Higher age quartile was a significant predictor of mortality in the implanted CRT, upgrade to CRT, upgrade to CRT or ICD, and Cohort 2 (planned lead revision or addition) subgroups, suggesting that older age may be a consideration when contemplating device 13 DOI: 10.1161/CIRCEP.114.001671 upgrades or CRT. The REPLACE DARE mortality risk prediction score was developed as a tool for risk stratification in patients undergoing CIED replacement. The 6 variables can be entered into an on-line calculator application at http://www.replacedare.org/. The score yielded significant predictive capability to discriminate survivors and non-survivors at 6 months after CIED replacement. The components of the REPLACE DARE score highlight the potential importance of considering heart failure status, advanced CKD stage, cerebrovascular disease, advanced age, Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 and use of antiarrhythmic therapy when considering risks for CIED replacements p acements or upgrades. pl upgr up grad gr a This risk analysis may also be useful to assess risk in patients contemplating plating ngg tthe he rrisk-benefit he iissk-b -ben en nefi efi pr rim imar aryy pprevention reve veention ICD device replacement, replaceeme m nt, but who no llonger onger meet conventional conventioo balance forr prim primary for ICD impl lan ntattioon. indicationss for implantation. m mplica atio tiions Clinical implications d g the ding th he predictors p ed pr dicctors off morbidity morbbiditty andd mortality mortalit li y after affte t r generator g neerato ge torr repl to placemen pl nts hhas as Understanding replacements ntt interest. iinterest ntt t 20 Th These iss issues is es are particularly partic ti llarl arll relevant rele le ant ntt tto elderly eld elderl lderll patients ti ts or th those with generated recent significant comorbidities seeking to decide whether the benefits outweigh risks of device upgrade or replacement. Since REPLACE did not enroll patients who did not undergo CIED replacement, these analyses cannot fully address these issues. Older age was a significant predictor of mortality in upgrade and CRT subgroups and was highly correlated with other high risk factors, such as CKD stage. The REPLACE DARE mortality risk prediction score stratified mortality risk in the 6 months after CIED replacement, including identifying a small subgroup with >50% mortality at 6 months. Evaluation of appropriateness for a CIED replacement procedure may be particularly important in these very high risk patients, as device implantation is not recommended for 14 DOI: 10.1161/CIRCEP.114.001671 patients with a life expectancy of less than one year in current device-based therapy guidelines. Thus, the REPLACE DARE score may serve as a useful tool to identify very high risk patients in whom reevaluation of antiarrhythmic drugs, optimization of heart failure and renal function, and/or reassessment of CIED replacement may be appropriate. Limitations Although this sub-analysis of the REPLACE registry was retrospective, the REPLACE data, including mortality, were collected prospectively. The study was also not powered to detect Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 significant differences in short-term mortality in all subgroup analyses. s. Although g the REPLACE REP EPL L DARE Score significantly identified patients with varying risk for mortality, rtalitty, y iincluding nclu nc l di lu ding ngg a vvery e high risk group, r up, the rou the Score Score ree will require external validation valid idaation in otherr populations. id poppulations. The highestt risk cohort was aalso clinical impact lso small, and an nd thee llargest arg gest cl lin i iccal imp mp pacct is llimited i itted ttoo thiss high im hig gh riskk cohort. coh ohoort. Conclusions n ns Six-month aall-cause REPLACE Registry Significant ll-ca caus usee mortality mo orttallit i y in in tthe h pprospective he roosp spec pecti t vee R ti EPLA EP LACE LA CE R egis eg gistr try y was was 4% 4%.. S ignifica ig cantt comorbidities, including heart failure, kidney, cerebrovascular disease, and aget80 years old, rather than complications, were identified as the most likely contributors to mortality after CIED replacement procedures. The REPLACE DARE Score identified subjects at high and low risk for mortality in the 6 months after CIED replacement. Reevaluation of antiarrhythmic drugs, optimization of heart failure and renal function, and/or reassessment of CIED replacement would seem appropriate in patients with very high scores. Funding Sources: The REPLACE Registry was sponsored by BIOTRONIK Conflict of Interest Disclosures: M.K. Chung has been an unpaid speaker and participant in industry-supported research for Medtronic, Boston Scientific Corp., St. Jude Medical, and 15 DOI: 10.1161/CIRCEP.114.001671 Zoll/LifeCor, and is an unpaid REPLACE study steering committee member (Biotronik). R. G. Holcomb has received support from Biotronik, Medtronic, and Boston Scientific Corp. S. Mittal is a consultant for Biotronik, Boston Scientific, Medtronic, Tyrx, and St. Jude Medical. J. Steinberg is a consultant for Medtronic, St. Jude Medical, Cameron Health, Biosense-Webster, Sanofi-Aventis, Janssen, and Ambucor; he receives research support from Medtronic, BiosenseWebster, Lifewatch, and Glaxo-Smith-Kline. M.J. Gleva has received support from Biotronik and Medtronic. T. Mela has received speaker honoraria from Medtronic, Boston Scientific, Biotronik, and St. Jude Medical. D.Z. Uslan has received honoraria from Boston Scientific. K. Mitchell is an employee of Biotronik. J.E. Poole has received honoraria from Medtronic, Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 Boston Scientific Corp., Biotronik, St. Jude Medical; consultant for Boston Scientific Corp., p and Physio Control. References: s s: 1. 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J Am Coll Cardiol. 2008;51:e162. 2. Poole JE, Gleva MJ, Mela T, Chung MK, Uslan DZ, Borge R, Gottipaty V, Shinn T, Dan D, Feldman LA, Seide H, Winston SA, Gallagher JJ, Langberg JJ, Mitchell K, Holcomb R. Complication rates associated with pacemaker or implantable cardioverter-defibrillator generator replacements and upgrade procedures: Results from the replace registry. Circulation. 2010;122:1553-1561. 3. K/DOQI clinical practice guidelines for chronic kidney disease: Evaluation, classification, and stratification. Am J Kidney Dis. 2002;39:S1-266. 4. Kadish A, Dyer A, Daubert JP, Quigg R, Estes NA, Anderson KP, Calkins H, Hoch D, Goldberger J, Shalaby A, Sanders WE, Schaechter A, Levine JH. Prophylactic defibrillator implantation in patients with nonischemic dilated cardiomyopathy. N Engl J Med. 2004;350:2151-2158. 16 DOI: 10.1161/CIRCEP.114.001671 5. AVID Investigators. 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N Engl J Med. nt Med d. 20 2012;3 ;36 366:2 291-2 -293.. 18 DOI: 10.1161/CIRCEP.114.001671 Table 1: Baseline Clinical and Device Procedure Characteristics at time of CIED Replacement: Univariable Associations with Survival Status at 6 Months Alive 96.0% (N=1674/1744) Dead 4.0% (N=70/1744) 70.0±13.7 95.8%(1133) 96.4%(541) 96.2%(1474) 94.8%(200) 28.3±6.3 94.1%(482) 96.8%(1192) 93.4%(268) 96.5%(1406) 93.1%(255) 996.5%(1419) 96 .5%(1419) 5%(1419) 92.5%(196) 92.5%(1 ( 96) 996.5%(1478) 6.5 5%(1 (147 4 8)) 47 73.8±12.7 4.2%(50) 3.6%(20) 3.8%(59) 5.2%(11) 27.2±5.8 5.9%(30) ( ) 3.2%(40) 3.2% 3. 2% %(4 ( 0) 6.6%(19) 6 6% 6. 6%(1 (19) (1 9) 3.5%(51) 3.5% 5%(5 5% (51) (5 1) 6.9%(19) 6 9% 9%(1 (19) (1 9) 3.5%(51) 3 5%(51) 7.5%(16) 7.5%(1 ( 6) 3.5%(54) 3.5% 3. 5%(5 5% (54) (5 4 4) 95.0 0%( % 574)) 95.0%(574) 96.5%(1100) 96 6.5 5%(1 ( 10 100 0) 5.0% 5. 0 (30) 0 0) 5.0%(30) 3.5%(40) 3.5% 5%(4 5% (40) (4 0 94.7%(604) 94 4.7 7%( % 60 6 4) 96.7%(1070) 96 .7% 7%(1 (107 070) 0) 97.7%(561) 97.7 97 7%(5 561 61)) 98.6%(209) 97.1%(406) 92.6%(478) 83.3%(20) 5.3%(34) 5. 5 3%(3 3% (34) (3 4) 33.3%(36) .3% 3%(3 3% (36) 6) 2.3%(13) 2.3% 3%(1 ( 3) (1 1.4%(3) 2.9%(12) 7.4%(38) 16.7%(4) 87.9%(218) 97.3%(1456) 36.6±16.4 97.7%(210) 97.6%(652) 94.7%(648) 91.4%(64) 84.0%(21) 12.1%(30) 2.7%(40) 31.8±17.5 2.3%(5) 2.4%(16) 5.3%(36) 8.6%(6) 16.0%(4) 96.8%(30) 96.0%(1644) 86.7%(13) 96.1%(1661) 3.2%(1) 4.0%(69) 13.3%(2) 3.9%(68) 1.000 93.7%(340) 96.6%(1334) 94.6%(211) 96.2%(1463) 95.7%(1191) 6.3%(23) 3.4%(47) 5.4%(12) 3.8%(58) 4.3%(54) 0.016 P value CLINICAL CHARACTERISTICS Age, years Gender Race Male Female White Non-White Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 Body mass index Diabetes mellitus + Chronic pulmonary disease + Cerebrovascular disease + Peripheral vascular a cu ascu c la l r diseas disease se + Remote myocardial cardial infarctionn > ca >4 4 we w weeks eeks + Prior Coronary r art ry artery rtter e y by bypass ypa pass ss oorr vvalve alve al ve ssurgery u ge ur gery ry (638) + (6 (638 38)) 38 (1106) - (1 (110 106) 6) NYHA Classs (0-II vs. III-IV) III I -IV II IV V) 0 I II III IV Admission for heart failure within past 12 months + Left ventricular ejection fraction Chronic kidney disease stage 1 2 3 4 5 Liver disease Mild + Moderate or severe + Medications Any Class I or III antiarrhythmic drug + Amiodarone + Beta-adrenergic blocker + 0.023 0.60 0.35 0.13 0.015 0.020 0.. 0.011 0 0.009 0. 0.16 0 0.042 0. <0.001 <0 0 <0.001 19 0.052 0.001 0.12 0.27 0.35 DOI: 10.1161/CIRCEP.114.001671 + Digoxin + Diuretic + Statin + Angiotensin converting enzyme inhibitor + Angiotensin receptor blocker + Warfarin + Aspirin + Clopidogrel or ticlopidine + Calcium channel blocker Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 96.8%(483) 97.9%(229) 95.7%(1445) 95.7%(487) 96.1%(1187) 94.9%(1015) 97.6%(659) 96.1(958) 95.9%(716) 96.4%(803) 95.6%(871) 95.0%(285) 96.2%(1389) 95.5%(682) 96.3%(992) 95.6%(816) 96.4%(858) 96.9%(222) 95.8%(1452) 3.2%(16) 2.1%(5) 4.3%(65) 4.3%(22) 3.9%(48) 5.1%(54) 2.4%(16) 3.9%(39) 4.1%(31) 3.6%(30) 4.4%(40) 5.0%(15) 3.8%(55) 4.5%(32) 3.7%(38) 4.4%(38) 3.6%(32) 3.1%(7) 3.1%(7 ( ) 4.2%(63) 4..2% 4 2%(6 (63) (6 3) 96.4%(488) 9 .4%(488) 96 4%(488) 995.8%(1182) 5.8%(1182) 3.6%(18) 3 6%(18) 4.2%(52) 0.59 0 96.7%(816) 96.7%( %(8 %( 816) 95.7%(619) 95.7 7%(619) 94.5%(239) 9 .5 94 5%(2 (239 39)) 39 3.3%(28) 3.3%(28 8) 4.3%(28) 4.3 3%(288) 5.5%(14) 5.5% 5%(1 5% ( 4) (1 0.24 0 97.2%(597) 97 7.2 .2%( % 59 %( 5 7) 97.3%(461) 97 .3%( 3%(46 461 1) 93.8%(604) 93.8 93 8%(6 604 04)) 2.8%(17) 2.8 2. 8%( %(17 17)) 17 22.7%(13) .7 7%( %(13 13)) 66.2%(40) .2% 2%(4 ( 0) (4 0.003 0. 93.8%(557) 97.1%(1117) 6.2%(37) 2.9%(33) 0.001 96.4%(994) 95.4%(680) 93.4%(368) 96.7%(1306) 93.8%(407) 96.7%(1267) 79.2% (19) 96.2% (1655) 78.3% (18) 96.2% (1656) 3.6%(37) 4.6%(33) 6.6%(26) 3.3%(44) 6.2%(27) 3.3%(43) 20.8% (5) 3.8% (65) 21.7% (5) 3.8% (65) 0.32 100.0%(58) 98.6%(214) 96.4%(829) 95.6%(845) 0%(0) 1.4%(3) 3.6%(31) 4.4%(39) 0.15 0.69 0.006 0.81 0.46 0.33 0.46 0.39 00.59 DEVICE PROCEDURE CHARACTERISTICS Pacemaker dependent ependent epend nden den entt + - Pre-procedure re device re deevice type Pacemaker ema ema maker ICD D CRT-P, T CRT-D T-P, CRT RT--D Device Implanted a d anted Pacemaker e ke emake kerr ICD D CRT-P, T CRT-D T-P, D Device Implanted d-C CRT-D CRT-D implanted Non-CRT-D Cohort 1 (without planned lead revision) 2 (with planned lead revision) Upgrade to CRT + LV/CS lead addition/revision + Any epicardial lead addition + LV epicardial lead addition + Existing single upgraded to dual chamber device + Defibrillation testing done Not Done 0.005 0.01 0.002 0.002 1.00 0.40 CRT=cardiac resynchronization therapy device; CRT-D=cardiac resynchronization therapy defibrillator; CRTP=cardiac resynchronization therapy pacemaker; ICD=implantable cardioverter-defibrillator; NYHA=New York Heart Association 20 DOI: 10.1161/CIRCEP.114.001671 Table 2: Cox Proportional Hazards Regression Model Hazard Ratio 95% Confidence Interval P value Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 Prior admission for heart failure (in 12 months) 3.097 1.795-5.344 <0.001 New York Heart Association class III or IV 1.959 1.122-3.418 0.018 Antiarrhythmic drug use 1.901 1.141-3.169 0.014 Chronic Kidney Disease Stage 1.425 1.053-1.930 1.930 0.022 0..0222 Cerebrovascular disease 1.801 1.052-3.084 3.0844 00.032 0. 03 032 Age in Quartiles r il rtil iles e es 1.238 1.2338 0.987-1.552 0 987-1.552 0. 0.065 5 21 DOI: 10.1161/CIRCEP.114.001671 Table 3: REPLACE DARE Mortality Risk Score. A. Comparison of mean score values by survival status. B. Cox regression analysis including the score variable. A. REPLACE DARE Score Survivor N 1595 Nonsurvivor 67 Mean Standard Deviation Standard error of mean 1.993 1.359 0.034 3.534 1.758 0.215 2-sided t-test p-value <0.001 Nonparametric Mann-Whitney test p-value <0.001 Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 B. REPLACE ED DARE ARE S Score core co ree p value Hazard Ha aza zard Ratio 995% 95 % Confidence Int Interval <0.001 <0 <0.0 0.00011 1.795 1.79 95 11.567-2.057 1. 56756 7--2. 7-2. 2 0557 Variables no not n ot iinn thee equation equaatiionn after eq afterr adjustment adju ad just ju sttment stm ment n for forr REPLACE REPL RE PL LAC ACE E DARE DARE R Sc Score corre Score Scor Sc orre P va valu value luee lu Prior admission s ssion for heart hear he hear artt fa fail failure ilur il u e ((in ur in 112 2 mo m mos) s) s) 0.13 0. 0.138 1388 13 00.711 0. 0.71 .71 7111 New York Heart Association class III or IV 0.051 0.822 Antiarrhythmic drug use 0.147 0.702 Chronic Kidney Disease Stage 0.301 0.583 Cerebrovascular disease 0.191 0.662 Age in Quartiles 0.143 0.705 22 DOI: 10.1161/CIRCEP.114.001671 Figure Legends: Figure 1: Kaplan-Meier survival curves by (A) REPLACE Cohort; Cohort 1=without planned lead revision, Cohort 2=with planned lead revision. (B) Implanted CIED Type. (C) CRT or ICD Upgrade. (D) Occurrence of Any (Major or Minor) Complication. (E) Occurrence of Prior Major Complication. Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 Figure 2: The REPLACE DARE Score. A. Frequency of REPLACE DARE risk scores. s.. B. B. Distribution of all-cause 6-month mortality across REPLACE DARE risk sc scores. scor ores es. C. C. Kaplan Kapl Ka plan pl a Meier survival the REPLACE Operating ival al bby y th he RE EPLACE DARE Score. D. The Th Receiver O peera r ting Characteristic ((ROC) curve for the REPLACE DARE Score. ROC value he R EPLACE D ARE RE Sco core. RO co R C va alu ue 00.758, .7758, 8, p<0.001 p< <00.001 01 23 Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 A Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 B Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 C Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 D Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 A Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 B Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 C Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 D REPLACE DARE (Death After Replacement Evaluation) Score: Determinants of All-Cause Mortality After Implantable Device Replacement Or Upgrade from the REPLACE Registry Mina K. Chung, Richard G. Holcomb, Suneet Mittal, Jonathan S. Steinberg, Marye J. Gleva, Theofanie Mela, Daniel Z. Uslan, Kevin Mitchell and Jeanne E. Poole Downloaded from http://circep.ahajournals.org/ by guest on November 18, 2016 Circ Arrhythm Electrophysiol. published online September 14, 2014; Circulation: Arrhythmia and Electrophysiology is published by the American Heart Association, 7272 Greenville Avenue, Dallas, TX 75231 Copyright © 2014 American Heart Association, Inc. All rights reserved. Print ISSN: 1941-3149. Online ISSN: 1941-3084 The online version of this article, along with updated information and services, is located on the World Wide Web at: http://circep.ahajournals.org/content/early/2014/09/14/CIRCEP.114.001671 Data Supplement (unedited) at: http://circep.ahajournals.org/content/suppl/2014/09/14/CIRCEP.114.001671.DC1.html Permissions: Requests for permissions to reproduce figures, tables, or portions of articles originally published in Circulation: Arrhythmia and Electrophysiology can be obtained via RightsLink, a service of the Copyright Clearance Center, not the Editorial Office. Once the online version of the published article for which permission is being requested is located, click Request Permissions in the middle column of the Web page under Services. Further information about this process is available in the Permissions and Rights Question and Answerdocument. Reprints: Information about reprints can be found online at: http://www.lww.com/reprints Subscriptions: Information about subscribing to Circulation: Arrhythmia and Electrophysiology is online at: http://circep.ahajournals.org//subscriptions/ 1 DATA SUPPLEMENT TABLE I. A. Complications: Univariable Associations with Survival Status at 6 Months. B. Deaths in Patients with Major Complications after CIED Replacement A. Complications: Univariable Associations with Survival Status at 6 Months. Alive Dead 96.0% 4.0% (N=1674/1744) (N=70/1744) Prior Major complication + 93.2%(136) 6.8%(10) 96.2%(1538) 3.8%(60) Prior Minor complication + 99.2%(129) 0.8%(1) 95.7%(1545) 4.3%(69) Any prior complication + 95.7%(245) 4.3%(11) 96.0%(1429) 4.0%(59) P value 0.077 0.058 0.733 2 B. Deaths in Patients with Major Complications after CIED Replacement MAJOR COMPLICATIONS N (%) Unplanned lead addition/revision 1/29 (3.4%) Cardiac perforation 1/5 (20.0%) Pneumothorax 1/4 (25.0%) Peri-op cardiac arrest 2/2 (100.0%) Major hemodynamic instability 0/4 (0%) Peri-op respiratory failure 0/1 (0%) Deep venous thrombosis 0/6 (0%) Pulmonary embolism 0/1 (0%) Infection 0/14 (0%) Prolonged hospitalization 5/23 (21.7%) Malfunction, reopen pocket 2/58 (3.4%) Pocket revision Major hematoma 0/7 (0%) 3/21 (14.3%) Non-healing pocket 0/2 (0%) Hospital admission 1/16 (6.3%) Pneumonia, UTI 1/1 (100%) Drug reaction 0/1 (0%) Coronary venous dissection 0/1 (0%) Peripheral embolus 0/1 (0%) Other 2/9 (22.2%) 3 SUPPLEMENTAL TABLE II. Cox Regression Analyses by Upgrade or CRT Subgroups Implanted CRT Group (n = 644) Hazard Ratio 95% Confidence Interval P value Age (quartiles) 1.664 1.225, 2.261 0.001 Diabetes mellitus 1.967 1.025, 3.778 0.042 Prior admission for HF (in 12 mos) 4.522 2.288, 8.937 <0.001 Antiarrhythmic drug use 2.016 1.039, 3.911 0.038 Upgrade to CRT (n = 394) Hazard Ratio 95% Confidence Interval P value Age (quartiles) 1.495 1.022, 2.188 0.038 Prior admission for HF (in 12 mos) 4.395 1.806, 10.694 0.001 Upgrade to ICD (n = 206) Hazard Ratio 95% Confidence Interval P value Diabetes mellitus 5.194 1.039, 25.965 0.045 Prior admission for HF (in 12 mos) 7.310 1.462, 36.543 0.015 Upgrade to CRT or ICD (n = 461) Hazard Ratio 95% Confidence Interval P value Age (quartiles) 1.470 1.013, 2.134 0.043 NYHA class III/IV 3.328 0.686, 16.150 0.136 Prior admission for HF (in 12 mos) 3.820 1.627, 8.973 0.002 Upgrade to CRT 0.073 0.008, 0.621 0.017 LV lead attempt 0.031 1.317, 377.376 0.031 Cohort 2 (n = 713) Hazard Ratio 95% Confidence Interval P value Age (quartiles) 1.497 1.074, 2.089 0.017 NYHA class III/IV 3.175 1.068, 9.440 0.038 Prior admission for HF (in 12 mos) 4.034 1.847, 8.810 <0.001 Moderate or severe liver disease 7.922 1.049, 59.841 0.045 4 SUPPLEMENTAL TABLE III. Bootstrapping Predictors of Mortality. A. Cox Model Coefficients. Results demonstrate that there was low estimated bias associated with the original estimates of model coefficients (-1.9% to 3.3%), and that the significant levels associated with the bootstrap estimates were nearly identical to the original. All identified variables would have been retained in the original model, where the criterion for retention was a p-value of 0.10 or less. B. Estimated Hazard Ratios. The 95% confidence intervals for the bootstrap estimates of hazard ratios [Exp(B)] were consistent (that is, had similar coverage) to the original estimates. A. Cox Model Coefficients Coefficient Variable Standard Error (SE) P-value B Bias (%) Original Bootstrap Original Bootstrap Prior Admit HF 1.130 .004 (0.4%) .278 .273 <0..001 <0.001 NYHA Class .672 .009 (1.3%) .284 .285 .018 .018 CKD Stage .354 -.004 (-1.1%) .155 .177 .022 .042 Antiarrhythmic Rx .643 -.007 (-1.1%) .261 .270 .014 .012 Cerebrovasc Dis .589 -.011 (-1.9%) .274 .291 .032 .033 Age in Quartiles .213 .007 (3.3%) .115 .121 .065 .069 B. Estimated Hazard Ratios Hazard Variable 95% Lower Bound 95% Upper Bound Ratio Exp(B) Original Bootstrap* Original Bootstrap* Prior Admit HF 3.097 1.795 1.831 5.344 5.307 NYHA Class 1.959 1.122 1.130 3.418 3.501 CKD Stage 1.425 1.053 .989 1.930 1.982 Antiarrhythmic Rx 1.901 1.141 1.096 3.169 3.149 Cerebrovasc Dis 1.801 1.052 .986 3.084 3.056 Age in Quartiles * Percentile method 1.238 .987 .988 1.552 1.586 5 FIGURE I. Kaplan-Meier survival curves by occurrence of (A) Prior Heart Failure Hospitalization in the prior 12 months; (B) New York Heart Association Functional Class; (C) Antiarrhythmic Drug Use; and (D) Cerebrovascular Disease. (A) 6 (B) 7 (C) 8 (D) 9 FIGURE II. Chronic kidney disease and survival after CIED replacement. A. All-Cause 6month mortality (%) by chronic kidney disease stage (GFR, mL/min/1.73 m2). B. Kaplan-Meier survival analyses by chronic kidney disease. A. All-Cause 6-month mortality (%) by chronic kidney disease stage (GFR, mL/min/1.73 m2). 10 B. Kaplan-Meier survival analyses by chronic kidney disease. 11 FIGURE III. Kaplan-Meier Survival Analysis by Occurrence of Any (Major or Minor) Prior Complication 12 FIGURE IV. Quartile of Age and Survival After CIED Replacement. A. Distribution of age by REPLACE Cohort. Kaplan-Meier Survival by Age in: B. All Subjects. C. By REPLACE Cohort 1. D. REPLACE Cohort 2. E. Patients with Implanted Pacemakers. F. Patients with implanted ICDs, not including CRT-D ICDs. G. Patients with Implanted CRT devices (CRT-P and CRT-D). H. Patients Upgraded to a CRT CIED. and J. Patients Upgraded to an ICD. A. Distribution of age by quartile and REPLACE Cohort. 13 B. Kaplan-Meier Survival by Age Quartile in All Subjects 14 C. Kaplan-Meier Survival by Age Quartile in REPLACE Cohort 1. 15 D. Kaplan-Meier Survival by Age Quartile in Cohort 2. 16 E. Kaplan-Meier Survival by Age in Patients with Implanted Pacemakers. 17 F. Kaplan-Meier Survival by Age in Patients with Implanted ICDs, excluding CRT-Ds. 18 G. Kaplan-Meier Survival by Age in Patients with Implanted CRT devices (CRT-P and CRT-D). 19 H. Kaplan-Meier Survival by Age in Patients Upgraded to a CRT device.
