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ORIGINAL CONTRIBUTION

Sex and Racial Differences in the Use ofImplantable Cardioverter-Defibrillators AmongPatients Hospitalized With Heart Failure

Adrian F. Hernandez, MD, MHS

Gregg C. Fonarow, MD

Li Liang, PhD

Sana M. Al-Khatib, MD, MHS

Lesley H. Curtis, PhD

Kenneth A. LaBresh, MD

Clyde W. Yancy, MD

Nancy M. Albert, PhD

Eric D. Peterson, MD, MPH

MORE THAN 350000 PEOPLEdie annually as a result ofsudden cardiac death,and a major risk factor

for sudden cardiac death is heart fail-ure with left ventricular systolic dys-function.1-3 Half of all deaths fromheartfailure are sudden events thought to beattributable primarily to lethal arrhyth-mias.1 Several large randomized clini-cal trials have shown that implantablecardioverter-defibrillator (ICD) therapyreduces mortality in heart failure pa-tients with left ventricular systolic dys-function.4-6 Thus, evaluation of sys-tolic function is recommended in allpatients with heart failure, and ICDtherapy is recommended for patientswithsystolic dysfunction who meetcer-tain criteria.7,8

Previous studieshaveshown thatdis-parities by sex and race often exist inthe use of innovative or costly cardio-vascular technologies as they emerge,and these disparities can persist foryears.9,10 Recognition of disparities by

sex and race has prompted the Insti-tute of Medicine and the AmericanHeart Association (AHA) to increaseawareness throughout the public andamong clinicians, payers, and policy

makers, and to undertake efforts to re-duce these disparities.11,12

In this study, we examined the over-all use of ICD therapy in patients withheart failure who were at risk for sud-den cardiac death. Second, we exploredwhether there were significant sex andracial disparities in ICD use among eli-gible patients.

METHODSData Source

The data were obtained from the GetWith the Guidelines Program, which is

AuthorAffiliations: DukeClinical ResearchInstitute (DrsHernandez, Liang, Al-Khatib, Curtis,and Peterson) andDepartment of Medicine (Drs Hernandez, Al-Khatib,Curtis, andPeterson), Duke UniversitySchoolof Medi-cine, Durham, North Carolina;University of CaliforniaLos Angeles Medical Center (Dr Fonarow); Masspro,Waltham,Massachusetts (Dr LaBresh); Baylor Heart andVascular Institute,Dallas,Texas(Dr Yancy);and Cleve-land Clinic, Cleveland, Ohio (Dr Albert).Corresponding Author: Adrian F. Hernandez, MD,MHS,Duke Clinical ResearchInstitute,PO Box17969,Durham, NC 27715 ([email protected]).

Context Practice guidelines recommend implantable cardioverter-defibrillator (ICD)therapy for patients with heart failure and left ventricular ejection fraction of 30% orless. The influence of sex and race on ICD use among eligible patients is unknown.

Objective To examine sex and racial differences in the use of ICD therapy.

Design, Setting, and Patients Observational analysis of 13 034 patients admit-ted with heart failure and left ventricular ejection fraction of 30% or less and dis-charged alive from hospitalsin theAmerican Heart Associations GetWith the GuidelinesHeart Failure quality-improvement program. Patients were treated between January2005 and June 2007 at 217 participating hospitals.

Main Outcome Measures Use of ICDtherapy or planned ICD therapy at discharge.

Results Among patients eligible for ICD therapy, 4615 (35.4%) had ICD therapy atdischarge (1614 with new ICDs, 527 with planned ICDs, and 2474 with prior ICDs).ICDs were used in 375 of 1329 eligible black women (28.2%), 754 of 2531 whitewomen(29.8%),660of 1977 black men(33.4%),and2356 of 5403 white men(43.6%)(P .001). After adjustment for patient characteristics and hospital factors, the ad-justed odds of ICD use were 0.73 (95% confidence interval, 0.60-0.88) for black men,0.62 (95% confidence interval, 0.56-0.68) for white women, and 0.56 (95% confi-dence interval, 0.44-0.71) for black women, compared with white men. The differ-

ences were not attributable to the proportions of women and black patients at par-ticipating hospitals or to differences in the reporting of left ventricular ejection fraction.

Conclusions Less than 40% of potentially eligible patients hospitalized for heart fail-ure received ICD therapy, and rates of use were lower among eligible women andblack patients than among white men.

JAMA. 2007;298(13):1525-1532 www.jama.com

See also pp 1517 and 1564.

2007 American Medical Association. All rights reserved. (Reprinted) JAMA, October 3, 2007Vol 298, No. 13 1525

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an ongoing, voluntary, observationaldata collection and continuous quality-improvement initiative that beganin 2000 and has been describedpreviously.13-15 Participating hospitalsuse the point-of-service, interactive,

Internet-based Patient ManagementTool (Outcome Sciences, Inc, Cam-bridge, Massachusetts) and submitclinical information regarding in-hospital care and outcomes of pa-tients hospitalized for coronary arterydisease, stroke, or heart failure. Theheart failure module, initiated from theOrganized Program to Initiate Life-Saving Treatment in Hospitalized Pa-tients With Heart Failure (OPTIMIZE-HF) in January 2005, serves as the mainanalysis data set and includes patientshospitalized with heart failure.16 Par-

ticipating institutions are instructed tosubmit patient informationon consecu-tive eligible patients into the Get Withthe Guidelines database.

All participating institutions were re-quired to comply with local regula-tory and privacy guidelines and to sub-mit the program protocols for reviewand approval by their institutional re-view board. Because data were used pri-marily at the local site for quality im-provement, sites were granted a waiverof informed consent under the com-

mon rule. The Duke Clinical ResearchInstitute servesas the data analysis cen-ter and has an agreement to analyze theaggregate deidentified data for re-search purposes.

Trainedpersonnel abstractedthe datausing standardized definitions. Admis-sions staff, medical staff, or both re-cordedself-reportedrace/ethnicity, usu-ally asthepatient wasregistered. Patientswere assigned to race/ethnicity catego-ries using options defined by the elec-tronic case report form. Other variables

included demographic and clinical char-acteristics, medical history, previoustreatments, contraindications for evi-dence-based therapies, and in-hospitaloutcomes. Datacollection regardingICDtherapyincludedprior implantation,newimplantation, or planned implantation af-ter hospital discharge; documentedcon-traindications for ICD therapy, defined

as any reason documented by a physi-cian for not using ICD therapy or spe-cific contraindications, such as the pa-tient is not receiving optimal medicaltherapy, hashadan acute myocardial in-farction within 40 days, has recent-

onset heart failure, or has another life-t h r e a t e n i n g i l l n e s s t h a t w o u l dcompromise 1-year survival with goodfunctional status. Documentation of rea-sonsfornot placingan ICD werealsocol-lected, including economic, social, andreligious reasons, nonadherence, andother reasons for refusal.

The Internet-based system per-formed edit checks to ensure the com-pleteness of the reported data. In ad-dition, data quality was monitored andreports were generated to confirm thecompleteness and accuracy of the sub-

mitted data. Only sites and variableswith a high degree of completeness wereused in the analyses.

Study Population

From January 2005 throughJune 2007,59 965 patients with heart failure weredischarged alive from participatinghos-pitals. Our study was based on a finalcohort of 13 034 patients eligible forICDtherapyfrom217 hospitals.Amongthe excluded patients, 5924 who hadnew-onset heart failure were excluded

because they were not eligible for ICDtherapy for primary prevention; 14 514were excluded for the following rea-sons: 407 left against medical advice,1518 transferred to another acute carefacility, 1237 were discharged to hos-pice, 10 456 were discharged to a skillednursing facility, and 896 were dis-charged to a rehabilitation center; 7077patients were excluded because therewas no documentation of left ventricu-lar ejection fraction (LVEF); 18 768 pa-tients with LVEF of greater than 30%

were excluded to confine the analysisto patients who met criteria for class Irecommendations for ICD therapybased on current American College ofCardiology (ACC)/AHA heart failureguidelines17; and 648 patients with acontraindication or other reason docu-mented by a physician for not receiv-ing ICD therapy were excluded.

Outcome Measures

Themain outcome measure was theuseof ICD therapy or documented plansforthe placement of an ICD after hospitaldischarge among eligible patients withLVEF of 30% or less. For the purposes

of the analysis, we also included pa-tients in the numerator if they hadpriorICD therapy. Performance measures as-sessed were the provision of dischargeinstructions, use of an angiotensin-converting enzyme inhibitor or angio-tensin receptor blocker in patients withleft ventricular systolic dysfunction, andsmoking cessation counseling for eli-gible patients, which are the core mea-sures of quality used by the Centers forMedicare & Medicaid Services.7,8 Ad-ditional indicators of evidence-basedcare included in the analysis were the

use of-blockers in left ventricular sys-tolic dysfunction, anticoagulation foratrial fibrillation, and aldosterone an-tagonists for left ventricular dysfunc-tion, which are class I therapies in theACC/AHA heart failure guidelines.

Because documentation of LVEF isa nationalperformance indicator for pa-tients with heart failure and a prereq-uisite for ICD eligibility, we con-ducted a sensitivity analysis thatincluded patients with no LVEF docu-mentation.7,8We also evaluated ICDuse

among eligible patients who did nothave depression, stroke, or anemia andamong eligible patients aged youngerthan 70 years.

Statistical Analyses

Using 2 tests for categorical variablesand Wilcoxon rank sum tests for con-tinuous variables, we compared thebaseline characteristics of patients whoreceived ICD therapy with the charac-teristics of patients who did not re-ceive ICD therapy. We report medi-

ans and interquartile ranges forcontinuous variables and percentagesfor categorical variables. We also ex-amined patient characteristics for thebroader population of patients withandwithout documentation of LVEF.

We used multivariatelogistic regres-sion analysis to identify important fac-tors associated with ICD use. We used

SEX AND RACIAL DIFFERENCES IN ICD USE

1526 JAMA, October 3, 2007Vol 298, No. 13 (Reprinted) 2007 American Medical Association. All rights reserved.



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the generalized estimating equationsmethod to adjust for clustering withinhospitals.18 The initial model in-cluded variablesfor age, sex, race(whitevs black), geographic region where thedata were collected, systolic blood pres-

sure, and medical diagnoses includingacute renal failure, anemia, atrial fibril-lation, cerebrovascular accidentor tran-sient ischemic attack, chronic obstruc-tive pulmonarydisease, coronary arterydisease, depression, diabetes mellitus,hyperlipidemia, hypertension, ische-mic heart disease, peripheral vasculardisease, renal insufficiency, and smok-ing. In addition, we tested for interac-tions between sex and race. Factors forwhich P was greater than or equal to.05 were removed from the logistic re-gression model.

We also performed analyses to de-termine if observed racial or sex differ-ences in ICD use were attributable inpart to the hospitals in which the pa-tients received care. First, we exam-ined differences in ICD use based onthe proportion of black patients andwomen at each hospital. Second, weused a hierarchical model with hospi-tal as a random effect and patient base-line characteristics as fixed effects. Thishierarchical model takes into accountthefact that ICD use for patients within

the same hospital may be correlated,and allows us to examine differencesin ICD use among patients withinhospitals.

We performed sensitivity analyses toexamine the robustness of the find-ings. Weexamined newor planned ICDuse by sex and racial subgroups. Weused the generalized estimating equa-tions method to adjust for clusteringwithin hospitals to determine ad-justed oddsratios (ORs) for ICD use forsex and racial subgroups. We then ex-

amined frequency of ICD use in im-portant patient subgroups based on lackof comorbid conditions, Medicare en-rollment, symptoms of dyspnea, andpredicted 1-year mortality using a pre-viously validated model.19

A P value of less than .05 was con-sidered statistically significant for alltests. All analyseswereperformed using

SAS software version 8.2 (SAS Insti-tute, Cary, North Carolina).

RESULTS

Of the 13 034 patients eligible for ICDtherapy, 4615 (35.4%) received an ICD

(1614 patients with a new ICD, 527with a planned ICD, and 2474 with aprior ICD). TABLE 1 shows the base-line characteristics of the study popu-lation. Women represented 27.2% ofpatients who received ICD therapy and3 7 . 8 % o f p a t i e n t s w h o d i d n o t(P .001). Black patients represented23.0%of patients with ICDtherapy and28.0% of patients without (P .001).The frequency for ICD use was high-est for white men, with 43.6% of those5 4 0 3 el i g i b l e r ecei v i ng an I CD(P .001). The frequency for ICD use

was 28.2% of 1329 eligible blackwomen, 33.4% of 1977 eligible blackmen, and 29.8% of 2531 eligible whitewomen.

Contraindications to ICD therapywere documented for 648 (4.7%) oth-erwise potentially eligible patients.Documented reasons included 24 eco-nomic, 20 social, 44 nonadherence, 1religious, 140 other reasons providedby patients, and 441 reasons providedby physicians, which included not re-ceiving optimal medical therapy, acute

myocardial infarction within the pre-vious 40 days, and recent onset of heartfailure. There were no significant dif-ferencesfor documented contraindica-tions by sex or race (4.0% for whitemen, 5.2% for black men, 4.6% forwhitewomen, and4.0% for blackwom-en; P=.12).TABLE 2 shows other measures of

heart failure quality of care. Provisionof discharge instructions, use of an an-giotensin-converting enzyme inhibi-tor or angiotensin receptor blocker,and

smoking cessation counseling weresimilar between patients with andwith-out ICD therapy. Use of-blockers, an-ticoagulation for atrial fibrillation, andaldosterone antagonists was higher inpatients with ICD therapy comparedwith those without ICD therapy.TABLE 3 shows factors that were as-

sociated with ICD use among eligible

heart failure patients in the general-ized estimating equationsmodel andthehierarchical model with site as a ran-dom effect. The 2 models had similarORs, but with some variation in con-fidence intervals (CIs) between the

models. In both models, women wereapproximately 40%lesslikely than mento receive ICD therapy and black pa-tients were approximately 30% lesslikely than whitepatients to receive ICDtherapy.

In generalized estimating equationmodels after adjustment for both pa-tient and hospital factors including ad-justment for age, insurance, systolicblood pressure, medical history vari-ables (anemia, atrial fibrillation, chronicdialysis, hypertension, hyperlipidemia,ischemic heart disease, smoking), and

geographic region, 3 groups of patientswere significantly less likely than whitemen to receive ICD therapy: black men(OR, 0.73; 95% CI, 0.60-0.88;P=.001),white women (OR, 0.62; 95% CI, 0.56-0.68; P .001), and black women (OR,0.56; 95% CI, 0.44-0.71; P.001).

Sensitivity Analyses

Because there maybe differences in ratesof new ICD placements vs prior ICDplacements, we examined overall fre-quencies across sex and racial groups,

and calculated adjusted ORs for new orplanned ICDs. The frequency for new orplanned ICD implantations after dis-chargewas 25.8% of 4109 eligible whitemen, 18.3% of 2176 white women,17.5% of 1595 black men, and 13.0% of1096 black women (P.001).After ad-justment for patientcharacteristics(age,insurance, systolic blood pressure, ane-mia,chronicdialysis,hyperlipidemia, hy-pertension, renal insufficiency, pulmo-nary disease, and smoking status), theadjustedORsfor ICD usecompared with

white men were 0.59 (95% CI, 0.47-0.74;P.001) forblack men, 0.73 (95%CI, 0.64-0.82; P .001) for whitewomen, and 0.43 (95% CI, 0.33-0.56;P.001) for black women.

To assess whether racial differencesin ICD use were attributable to patienttreatment site, hospitals were dividedinto tertiles of black patients hospital-





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ized for heart failure (5%, 5%-15%,and15%), and differences in ICDuseremained significant in hospitals with ahigher proportion of black patients. Inthe lowest tertile, 30.7% of white pa-tients (896 of 2922) received ICD

therapy, compared with 21.6% of blackpatients (19 of 88;P=.07). In themiddletertile, therates were 43.2% of white pa-tients (983 of 2274) and 32.7% of blackpatients (119 of 364; P .001). In thehighest tertile, the rates were 44.6%(1266 of 2837) for white patients and

31.5% (907 of 2880) for black patients(P.001).

Similarly, sex differences in ICD usewere not attributable to the proportionof women treated for heart failure at thehospital level. After dividing hospitals

into tertiles of women hospitalized forheart failure (45%, 45%-55%, and55%), differences in ICD use re-mained. In the lowest tertile, 33.6% ofeligible women received ICD therapy(469 of 1398) compared with 46.0% ofeligible men(1592 of 3464;P.001). In

the highest tertile, 20.5% (74 of 361) ofeligible women received ICD therapycompared with 29.3%(142of 484)ofeli-gible men (P=.004).

We also examined ICD therapy fordifferent groups of patients who phy-

sicians may consider are better candi-dates based on lack of comorbid con-ditions, similar insurance, or similarsymptoms. Among patients agedyounger than 70 years without ane-mia, cerebrovascular disease, or de-pression, the frequency of ICD therapy

Table 1. Baseline Patient Characteristicsa

CharacteristicTotal

(N = 13 034)ICD

(n = 4615)No ICD

(n = 8419) P Value

Age, median (IQR), y 69 (57-78) 68 (58-76) 70 (57-80) .001

Women 34.1 27.2 37.8 .001

Race/ethnicityBlack 26.2 23.0 28.0

Hispanic 6.1 4.1 7.3 .001

White 63.1 69.1 59.8

InsuranceMedicare 49.5 51.2 48.6

Medicaid 7.5 7.0 7.8.001

Other 37.2 38.8 36.3

No insurance 5.8 3.0 7.4

Systolic blood pressure, median (IQR), mm Hg 129 (112-148) 122 (108-140) 133 (115-153) .001

Body mass index, median (IQR)b 27.3 (23.6-32.3) 27.4 (24.0-32.2) 27.2 (23.4-32.3) .02

HistoryAnemia 9.8 9.2 10.1 .12

Atrial fibrillation 22.7 26.8 20.4 .001

Cerebrovascular disease 11.2 12.3 10.6 .03

Depression 6.9 7.8 6.4 .002

Diabetes mellitusInsulin-dependent 20.9 20.4 21.2 .26

Noninsulin-dependent 14.7 16.6 13.7 .001

Chronic dialysis 2.8 2.0 3.2 .001

Hyperlipidemia 35.4 44.4 30.5 .001

Hypertension 61.1 61.8 60.7 .21

Ischemic heart disease 65.6 71.3 62.5 .001

Peripheral vascular disease 9.4 10.9 8.6 .001

Pulmonary disease 22.6 24.2 21.8 .001

Renal insufficiency (creatinine 2.0 mg/dL) 15.9 17.7 15.0 .001

Smoker 22.5 19.9 23.9 .001

Left ventricular ejection fraction, median (IQR), % 22 (18-27) 20 (16-25) 23 (20-28) .001

Geographic regionNortheast 20.9 20.1 21.3

South 26.8 36.0 21.8.001

Midwest 34.8 32.3 36.2

West 17.5 11.7 20.7

Hospital bed size, median (IQR) 330 (251-553) 382 (274-590) 324 (232-449) .001

Abbreviations: ICD, implantable cardioverter-defibrillator; IQR, interquartile range.SI conversion factor: to convert creatinine to mol/L, multiply by 88.4.a Data are presented as percentages unless otherwise indicated. Data are based on patients with available data for each characteristic.b Body mass index is calculated as weight in kilograms divided by height in meters squared.





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remained different across all groups:44.3% of white men (801 of 1810),33.1% of black men (411 of 1241),38.1% of white women (248 of 651),and 29.8% of black women (200 of 672;P.001).For patients enrolled in Medi-

care, ICD use was significantly differ-entacross groups basedon sexand race.ICD use among Medicare beneficia-ries was 44.8% for white men (1532 of3420), 36.5% for black men (271 of742), 27.9% for white women (481 of1724), and 28.4% for black women(154 of 542;P .001). The overall rateof ICD use stratified by severity of heartfailure symptoms based on dyspnea atrest or minimal exertion was 32.5%. Insex and racial subgroups, these rateswere 40.3% for white men (1185 of2942), 30.5% for black men (361 of

1183), 25.0% for white women (356 of1424), and 25.7% for black women(211 of 820; P .001).

Because prognosis may also influ-ence ICD use, we examined ICD usebasedonpredicted 1-yearmortality usingtheEFFECTmodel.19 ICD use was 38.1%for low-risk patients, 37.7% for interme-diate-risk patients, and 35.0% for high-risk patients (P=.26). In low-risk pa-tients, the rate ofICD use was 46.7% forwhite men, 32.9% for blackmen, 36.1%for white women, and 29.6% for black

women(P.001). In intermediate-riskpatients, the ICD frequency was 46.7%for white men, 36.9% for black men,26.4% for white women, and 30.1% forblackwomen (P.001). In high-riskpa-tients, the rate ofICD use was 42.8% forwhite men, 41.4% for blackmen, 20.2%for white women, and 26.9% for blackwomen (P.001).

Racial and sex differences in ICD usedid not appear attributable to differ-ences in reporting of LVEF. The fre-quency of missing LVEF was 17.9%

overall, 15.8% among white men, 10.8%among black men, 20.7% among whitewomen, and 13.8% among blackwomen. After exclusion of patientswhowere transferred, discharged to hos-pice, rehabilitation, or a skilled nurs-ing facility, left against medical advice,or had documented contraindicationsfor ICD therapy, there were 37 873

patients with heart failure, including13 034 patients with LVEF of 30% orless, 17 951 patients with LVEF ofgreater than 30%, and6888patientswithno documented LVEF. If a broader per-formance measure is defined as either

documentation of LVEF greater than

30% or an ICD present at discharge ineligible patients, then the failure rate ornonconformity rate was 74.1%. Thisnonconformity rate varied from 65.2%(4903 of7519) amongwhite men, 70.4%(1678of2384)amongblackmen,82.8%

(4146 of 5008) among white women,

Table 2. Quality-of-Care Measures for Patients With or Without ICD Therapy a

Overall ICD No ICD P Value

Discharge instructions (n = 12 329) 81.7 82.2 81.4 .25

Angiotensin-converting enzyme inhibitor or angiotensinreceptor blocker for left ventricular systolicdysfunction (n = 11 003)

85.9 86.6 85.6 .13

Smoking cessation counseling (n = 2773) 90.4 91.1 90.0 .38

-Blocker for left ventricular systolic dysfunction(n = 12 435)

89.2 91.5 87.9 .001

Anticoagulation for atrial fibrillation (n = 2773) 66.9 73.5 62.1 .001

Aldosterone antagonist (n = 12 539) 28.6 36.3 24.4 .001

Abbreviation: ICD, implantable cardioverter-defibrillator.a Data are presented as percentages unless otherwise indicated.

Table 3. Factors Associated With Implantable Cardioverter-Defibrillator Use (or Planned Use)at Discharge Among Eligible Patients With Heart Failurea

Characteristicb

Generalized EstimatingEquations Model

Hierarchical Model WithSite as a Random Effect

Odds Ratio (95%Confidence Interval) P Value

Odds Ratio (95%Confidence Interval) P Value

Age, per 10-y increase 0.83 (0.80-0.86) .001 0.81 (0.78-0.84) .001

Sex and raceWomen 0.62 (0.56-0.68) .001 0.58 (0.52-0.65) .001

Black men v s white men 0.73 (0.60-0.88) .001 0.68 (0.59-0.79) .001

Other men vs white men 0.74 (0.63-0.87) .001 0.71 (0.59-0.86) .001

Black women interaction b 1.25 (0.98-1.60) .08 1.32 (1.07-1.61) .008

Other women interactionb 1. 46 ( 1. 14-1.86) .003 1.55 ( 1. 13-2.12) . 007

LocationMidwest vs West 1.37 (0.84-2.24) .21

Northeast vs West 1.13 (0.65-1.95) .66

South vs West 1.70 (1.03-2.80) .04

InsuranceOther vs no insurance 1.92 (1.46-2.53) .001 2.07 (1.66-2.58) .001

Medicare vs no insurance 2.17 (1.65-2.85) .001 2.37 (1.89-2.98) .001

Medicaid vs no insurance 1.81 (1.33-2.47) .001 1.93 (1.50-2.49) .001

Systolic blood pressure,per 10-mm Hg increase

0.89 (0.88-0.91) .001 0.89 (0.87-0.90) .001

Anemia 0.76 (0.64-0.90) .03 0.75 (0.65-0.86) .001

Atrial f ibrillation 1.13 (1.01-1.27) .03 1.14 (1.03-1.26) .01

Chronic dialysis 0.67 (0.53-0.85) .001 0.66 (0.51-0.86) .002

Diabetes mellitus 0.91 (0.83-0.99) .03

Hyperlipidemia 1.40 (1.26-1.55) .001 1.46 (1.33-1.60) .001

Hypertension 0.89 (0.81-0.99) .03 0.89 (0.81-0.98) .02

Ischemic heart d is ease 1.35 (1.19-1.52) .001 1.41 (1.28-1.56) .001

Smoking 0.72 (0.65-0.80) .001 0.69 (0.62-0.76) .001a Empty table cells denote nonsignificance.b Listed variables are significant factors in the finalmodel that influencedimplantable cardioverter-defibrillatoruse. Vari-

ables in the initial model included age, female sex, race, interaction of race and sex, systolic blood pressure, insur-ance(Medicare, Medicaid,other, andno insurance), medical history variablesincluding anemia, atrial fibrillation, cere-brovascular accident/transient ischemic attack, depression, diabetes mellitus, dialysis,hypertension,hyperlipidemia,chronic obstructive pulmonary disease, peripheral vascular disease, renal insufficiency, smoker, and geographic re-gion (West, Northeast, Midwest, South).





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and 77.6% (1426of 1837)among blackwomen (P .001).

COMMENT

This study is the first, to our knowl-edge, to examine ICD use among eli-

gible patients with LVEF of 30% orless who were hospitalized with heartfailure. There are 3 main findings: (1)the overall frequency of ICD use wasl o w am o ng po tenti al l y el i g i b l epatients; (2) women were significantlyless likely than men to receive ICDtherapy, independent of other charac-teristics; and (3) black patients weresignificantly less likely than whitepatients to receive ICD therapy inde-pendent of other characteristics. Con-sequently, the rate of ICD use waslowest among black women.

In the Multicenter Automatic Defib-rillator Implantation Trial II (MADIT-II) and the Sudden Cardiac Death inHeart Failure Trial (SCD-HeFT), therelative risk reductions in all-causemor-tality with ICD therapy were 31% and23%, respectively, supporting the no-tion that physicians should carefullyconsider the potential benefit of ICDtherapy in eligible patients.4,20 These andother studies led the 2005 ACC/AHAguidelines for heart failure to includeICD therapy for primary prevention of

sudden cardiac death in patients withischemic (class I, evidence A) andnonischemic heart disease (class I, evi-dence B)and LVEFof 30% or lesswhoare receiving long-term optimal medi-cal therapy and have a reasonable ex-pectation of survival with good func-tional status of greater than 1 year.17

Furthermore, the Centers for Medi-care & Medicaid Services agreed in2005 to reimburse ICD therapy for pa-tients with ischemic or nonischemicheart disease, LVEF of less than 35%,

and New York Heart Association classII or III heart failure.21 Based on thesecriteria, our findings suggest that ICDtherapy is significantly underused in pa-tients hospitalized with heart failure,with approximately 35% of eligible pa-tients receiving ICD therapy or plannedICD therapy at the time of hospital dis-charge.

The rate of ICD use observed in thisstudy may over- or underestimate ICDuse among all potentially eligible pa-tients. LVEF measurement is an im-portant quality metric among patientswith heart failurebecause it helps to in-

formmany treatmentdecisions, includ-ing the use of ICD therapy. We foundthatapproximately20%of patientswithheart failure did not have an LVEF re-corded. If one considers failure to meetthe ICD performance measure to alsoinclude patients who do nothave docu-mentation of LVEF, then the noncon-formity rate is over 70%. If a signifi-cant proportion of eligible patients whodid not have a plan for ICD implanta-tion documented, but then under-went ICD implantation after dis-charge, the nonconformity rates would

be lower than reported in this study.We found sig nif icant sex dif fer -

ences in ICD use. Cardiovascular dis-ease is the leading cause of death forwomen, and survival among womenwith heart failure has not improved sub-stantially over the last 2 decades.1,22

Nevertheless, ICD use among poten-tially eligible women lagged far be-hind ICD use among men, with womenapproximately 40% less likely to havean ICD. Although women are often un-derrepresented in clinicaltrials, and less

than 30% of participants in the majorICD trialsfor primary prophylaxis werewomen, the ACC/AHA guidelines rec-ommend equal treatment for men andwomen.4,17,23-25 Admittedly, publishedtrials are underpowered to adequatelyassess the efficacy of ICDs specificallyin subgroups of women, and future re-search should specificallytarget womenwith heart failure at risk for suddendeath. To date, clinical trials have notshown major interactions based onsex for efficacy. For example, the

MADIT-II trial had 192 women (16%)showing similar mortality and similarICDeffectiveness when compared withmen.24 Therefore, until there is signifi-cant contrary evidence, eligible womenwith heart failure and LVEF of less than30% should be considered for ICDtherapy as primary prophylaxis perACC/AHA guidelines.

Similarly, black patients are morelikely than white patients to have heartfailure and are at higher risk for sud-den cardiac death.3 However, we foundblack patients were approximately 30%less likely than white patients to re-

ceive ICD therapy. In addition, dispari-ties existed regardless of the propor-tion of black patients admitted at eachhospital. For black patients, the avail-able data on ICD efficacy comes fromsmaller subgroups than women. In apost hoc analysis of the 102 black pa-tients in the Multicenter UnsustainedTachycardia Trial (MUSTT), survivalfor black patients randomly assigned tono electrophysiologically guidedtherapy was better than for black pa-tients receiving electrophysiologicallyguided therapy. However, the differ-

ence waspartially explained by a higherICD implantation rate in white pa-tients (50% vs 28%; P=.03). The SCD-HeFT trial did not report any signifi-cant sex or race interactions with themain results of mortality benefit withprimary ICD placement, althoughwomen and non-white subgroups hadhazard ratios with wide confidence in-tervals extending past unity.4

The ACC/AHA heart failure guide-lines acknowledge that certain patientcohorts have been underrepresented in

randomized clinical trials, and sub-group analyses are limited with regardto whether benefit of therapies is uni-form. However, the guidelines explic-itly state that the recommendationsshouldbe followed in theabsence of de-finitive evidence to thecontrary andthatblack patients should receive equaltreatment.17

There are several potential factorsthat may explain the disparities ob-served in this study. System inequitiesmay exist in the identification of eli-

gible patients and delivery of ICDtherapy. Physicians may consider cer-tain subgroups more prominently dueto a large number of white men in clini-caltrials.Patientsmayalso differ in pref-erences for ICD therapy across sex andrace subgroups, although Groeneveldet al26 found that black patients andwhite patients have similar prefer-





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ences for innovative technologies suchas implantable devices. In addition, an-other commonly proposed reason forICD use disparity among black pa-tients is that they tend to receive careat poorer quality centers.27 However,af-

ter adjusting for hospital characteris-tics in the hierarchical models, wefound that race persisted as a signifi-cant predictor of lower ICD use.

Other studies have shown that ICDsare underused in women and black pa-tients. Gauri et al28 examined Medi-care claims for patients with ischemiccardiomyopathy and found that womenwere 60% less likely than men to re-ceive ICD therapy for primary preven-tion. In the same study, black patientswere 31% less likely than white pa-tients to receive ICD therapy. These es-

timates are slightly higher than thosein the present study, most likely be-cause the analysis relied on Medicareclaims data, which do not contain in-formationabout LVEF andthus didnotallow for identification of patients withdepressed LVEF who were truly eli-gible for ICD therapy.

In addition to eliminating sex andra-cial disparities, future research shouldimprove knowledge about the cost-effectiveness and availability of ICDtherapy. Several studies have shown

ICD therapy to be cost-effective, butquestions remain regarding the broadapplication of current evidence be-cause of the total estimated costs to ma-jor payers and society.29-31 Future stud-ies should help to further define thecategory of eligible heart failure pa-tients who will derive a significant ben-efit from ICD therapy. In addition,greater attention should help guide thenecessity and utility of added featuresto insure that costs of ICD use do notescalate and possibly worsen dispari-

ties in care.The analysis also found that ische-micheartdiseasewas a major factorasso-ciated with ICD use. This finding maybe due to thelonger history of evidencefor ICD therapy among patients withischemicheartdisease,or to otherrelatedfactorsthat physicians recognize as sig-nifying a high risk for sudden cardiac

death. However,SCD-HeFT showedthatICDtherapy conferreda survivaladvan-tage onpatients with ischemic heart dis-easeand patientswithnonischemicheartdisease.4 Factors associated with lowerICD use, such as age or comorbid dis-

eases, may be related to the potentialinfluence of comorbid disease on func-tional status and long-term life expec-tancy.As noted,guidelines suggest thatphysiciansconsiderfunctional status andreasonable expected survival for at least1 year. However, even among patientsaged younger than 70 years withoutdepression, anemia, or history of cere-brovascular disease, ICD use was sub-optimal.

This study has several limitations.First, the data were from a voluntary,hospital-based quality-improvement

program. Given that randomized trialsof ICD therapy for primary preven-tionenrolled outpatients, assessment ofICD use among only patients hospital-ized with heart failure can be ques-tioned. However, we confined theanalysis to patients who would havequalified for ICD therapy prior to hos-pitalization (ie, patients with a historyof chronic heart failure and no docu-mented contraindications to ICDtherapy). Second, this program may in-clude hospitals with a higher likeli-

hood of following evidence-based rec-ommendations. Thus, theresults of thisstudy may be conservative comparedwith overallcommunity practice. Third,the data were reported through a stan-dardized case report, but therapies orcontraindications to therapiesmay havebeen underreported. Although we con-trolled for insurance status, we do nothave data for out-of-pocket expenseswhich could affect patient decisionsforICD therapy. Also, documentation ofLVEF was not available for all pa-

tients. However, by assuming that pa-tients without a documented LVEFwere eligible for ICD therapy, the dis-parities observed would be greater. Fi-nally, because we did not have accessto outpatient follow-up information, wewere unable to delineatebenefitsof ICDusein reducing mortality risk or thead-verse consequences of underuse and

disparities in the use of ICD therapy forprimary prevention of sudden cardiacdeath.

CONCLUSIONS

Eligiblehospitalizedpatients withheart

failure and LVEFof 30% or less are dis-charged frequentlywithout ICDtherapyor planned ICD therapy, and signifi-cant disparities exist for women andblack patients. Further research isneeded to understand the reasons forthe disparities at the patient, physi-cian, and hospital levels. Programs forawareness and promotion of evidence-based use of medical devices in heartfailure are needed overall and for theimportant subgroups studiedhere. Pub-licly reported measures regarding ICDtherapy should be considered.

Author Contributions: Dr Hernandez had full accessto all of the data in the study and takes responsibilityfor the integrity of the data and the accuracy of thedata analysis.Study concept and design : Hernandez, Fonarow,Peterson.Acquisition of data: Fonarow, Peterson.Analysis and interpretation of data: Hernandez,Fonarow, Liang, Al-Khatib, Curtis, LaBresh, Yancy,Albert, Peterson.Drafting of the manuscript: Hernandez, Fonarow,Peterson.Critical revision of the manuscript for important in-tellectual content: Hernandez, Fonarow, Liang,Al-Khatib, Curtis, LaBresh, Yancy, Albert, Peterson.Stat isti cal anal ysis: Hernandez, Fonarow, Liang,Peterson.Obtained funding: Hernandez, Fonarow, Peterson.

Administrative, technical, or material support:Fonarow, Hernandez, Peterson.Study supervision: Hernandez, Fonarow, Peterson.Expertise in electrophysiology: Al-Khatib.Financial Disclosures: Dr Hernandez reports receiv-in g re se a rch g ra n ts fro m S cio s, M e d tro n ic,GlaxoSmithKline, and Roche Diagnostics; and serv-ing on the speakers bureau or receiving honoraria inthe past 5 years from Novartis. Dr Fonarow reportsreceivingresearch grants fromAmgen,Biosite,Bristol-M y e r s S q u i b b , B o s t o n S c i e n t i f i c / G u i d a n t ,GlaxoSmithKline, Medtronic, Merck, Pfizer, Sanofi-Aventis, and Scios Inc; serving on the speakers bu-reau or receiving honoraria in the past 5 years fromAmgen, AstraZeneca, Biosite, Bristol-Myers Squibb,Boston Scientific/Guidant, GlaxoSmithKline, Kos,Medtronic, Merck, NitroMed, Novartis,Pfizer,Sanofi-Aventis, Schering Plough, Scios Inc, St Jude Medical,Takeda, and Wyeth; and serving as a consultant for

Biosite, Bristol-Myers Squibb, Boston Scientific/Guidant, GlaxoSmithKline, Medtronic, Merck, St JudeMedical, NitroMed, Orqis Medical,Pfizer, Sanofi, Sch-ering Plough,SciosInc, andWyeth.Dr Fonarowservesas chair of theAmerican Heart Associationss GetWiththe Guidelines Steering Committee, and has receivedresearch funding fromGlaxoSmithKlineand Medtronic.Dr Al-Khatib reports receiving research support fromMedtronic and honoraria for presentations fromMedtronic. Dr Curtis reports receiving research andsalary support from Allergan Pharmaceuticals,GlaxoSmithKline, Lilly,Medtronic, Novartis, OrthoBio-





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tech, OSI Eyetech, Pfizer, and Sanofi-Aventis. Dr Pe-terson reports receiving research grants from Bristol-Myers Squibb, Schering-Plough, and Sanofi-Aventis.Drs Curtis and Peterson have made available a de-tailedlisting of disclosure informationat http://www.dcri.duke.edu/research/coi.jsp. Dr Yancy reports re-ceiving research grants from Cardiodynamics,GlaxoSmithKline, Scios Inc, Medtronic, and Ni-troMed; serving as a consultant or on the speakers

b u r e a u f o r A s t r a Z e n e c a , C a r d i o d y n a m i c s ,GlaxoSmithKline, Medtronic,NitroMed, Novartis, andScios Inc; serving on advisory boards for CHF Solu-tions, a US Food and Drug Administration cardiovas-culardevice panel, andthe National Institutesof Health;receivinghonoraria fromAstraZeneca, Cardiodynam-ics, GlaxoSmithKline, Medtronic, Novartis, and SciosInc. Dr Albert reports serving as a consultant forGlaxoSmithKline and Medtronic and serving on thespeakersbureaufor GlaxoSmithKline,Medtronic, Ni-troMed, and Scios Inc. Drs Liang and LaBresh reportthat they have no conflicts of interest relevant to thesubject matter discussed in the article.Disclaimer: Dr EricPeterson,a JAMA contributing edi-tor, was not involved in the editorial review of or de-cision to publish this article.Funding/Support: The Get With the GuidelinesHeart Failure program is supported by an unre-stricted educational grant from GlaxoSmithKline. DrHernandez is supported by an American Heart Asso-ciation Pharmaceutical Roundtable grant0675060N.Role of theSponsors: GlaxoSmithKline hadno role inthedesign andconductof thestudy; collection, man-agement, analysis,and interpretation of the data; andpreparation, review, or approval of the manuscript.Additional Contributions: We thankDamonM. Seils,MA, of Duke University for editorial assistance andmanuscript preparation. Mr Seilsdid not receive com-pensation for his assistance apart from his employ-ment at the institution where the study was con-ducted.

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implantable defrib rill at or

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