Influence of Renal Function on the Use of Guideline-Recommended Therapies for Patients With Heart Failure

Influence of Renal Function on the Use of Guideline-Recommended Therapies for Patients With Heart Failure J. Thomas Heywood, MDa,*, Gregg C. Fonarow, MDb, Clyde W. Yancy, MDc, Nancy M. Albert, PhD, RNd, Anne B. Curtis, MDe, Wendy Gattis Stough, PharmDf,g, Mihai Gheorghiade, MDh, Mark L. McBride, PhDi, Mandeep R. Mehra, MDj, Christopher M. O’Connor, MDg, Dwight Reynolds, MDk, and Mary Norine Walsh, MDl Guidelines have been established for the treatment of patients with heart failure (HF) and left ventricular dysfunction, but renal dysfunction might limit adherence to these guidelines. Few data have characterized the use of guideline-recommended therapy for patients with HF, left ventricular dysfunction, and renal dysfunction who are treated in outpatient settings. The Registry to Improve the Use of Evidence-Based Heart Failure Therapies in the Outpatient Setting (IMPROVE HF) was a prospective study of patients receiving treatment as outpatients in cardiology practices in the United States. The rates of adherence to 7 guideline-recommended therapies were evaluated for patients with a left ventricular ejection fraction of <35%. The estimated glomerular filtration rate was estimated using the Modification of Diet in Renal Disease formula for 13,164 patients who were categorized as having stage 1 through stage 4/5 chronic kidney disease (CKD). More than 1/2 (52.2%) of the patients had stage 3 or 4/5 CKD. Older patients and women were at increased risk of higher stage CKD, and the rates of co-morbid health conditions were significantly greater among patients with more severe CKD. The patients with more severe CKD were significantly less likely to receive all interventions except cardiac resynchronization therapy. However, multivariate analysis controlling for patient characteristics revealed that the severity of CKD was an independent predictor of adherence to angiotensinconverting enzyme inhibitor/angiotensin receptor blocker therapy but not to any of the 6 other guideline-recommended measures. In conclusion, these results confirm that CKD is common in patients with HF and left ventricular dysfunction but is not independently associated with adherence to guideline-recommended therapy in outpatient cardiology practices, with the exception of angiotensin-converting enzyme inhibitor/angiotensin receptor blocker therapy. © 2010 Published by Elsevier Inc. (Am J Cardiol 2010;105:1140 –1146)

a

Scripps Clinic, La Jolla, California; bUniversity of California, Los Angeles, Medical Center, Los Angeles, California; cBaylor Heart and Vascular Institute, Baylor University Medical Center, Dallas, Texas; d Cleveland Clinic Foundation, Cleveland, Ohio; eUniversity of South Florida College of Medicine, Tampa, Florida; fCampbell University School of Pharmacy, Research Triangle Park, North Carolina; gDuke University Medical Center, Durham, North Carolina; hNorthwestern University, Feinberg School of Medicine, Chicago, Illinois; iOutcome Sciences, Inc., Cambridge, Massachusetts; jUniversity of Maryland, Baltimore, Maryland; k University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma; and lThe Care Group, LLC, Indianapolis, Indiana. Manuscript received October 19, 2009; revised manuscript received and accepted December 3, 2009. The IMPROVE HF registry and this study were sponsored by Medtronic, Inc., Minneapolis, MN. The authors served as consultants to Medtronic, Inc.; as of June 2008, this association ended for Dr. Yancy. Dr. McBride is a consultant to Outcome Sciences, Inc., Cambridge, Massachusetts. *Corresponding author: Tel: (858) 554-5588; fax: (858) 554-5197. E-mail address: [email protected] (J.T. Heywood). 0002-9149/10/$ – see front matter © 2010 Published by Elsevier Inc. doi:10.1016/j.amjcard.2009.12.016

A significant proportion of patients with heart failure (HF) also have renal dysfunction, which has been attributed to the common risk factors for HF and renal impairment, including hypertension, diabetes mellitus, and atherosclerosis.1– 4 Renal impairment in patients with HF is recognized as an independent risk factor for morbidity and mortality.5–10 Despite the greater risk of mortality in patients with HF and chronic kidney disease (CKD), evidence has suggested that guideline-recommended therapies for HF are less likely to be provided to patients with co-morbid HF and CKD.6,11–13 However, many of these studies involved hospitalized patients or were conducted before the release of contemporary therapeutic guidelines for HF. Thus, information about the rates and predictors of use of guideline-recommended therapies for outpatients with HF and reduced left ventricular ejection fraction who also have renal dysfunction is limited. Identification of the rates of adherence to guideline-recommended medical therapies and the factors associated with variations for patients with HF and CKD might provide important information about patterns of care and facilitate strategies to increase adherence. The present study was undertaken to determine the rates and severity of CKD in a population of patients with HF receiving care at outpatient www.AJConline.org

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Table 1 Comparison of baseline patient demographic and clinical characteristics by chronic kidney disease (CKD) stage eGFR (ml/min/1.73 m2)

Characteristic

Age (years) Mean ⫾ SD Median Men Race White Black Not documented/missing Insurance Medicare Medicaid Private Other Not documented/missing None Ischemic heart failure etiology Prior myocardial infarction Prior coronary bypass History of atrial fibrillation/flutter Prior peripheral vascular disease Diabetes mellitus Hypertension Chronic obstructive pulmonary disease Depression Prior percutaneous coronary intervention New York Heart Association class I II III IV Left ventricular ejection fraction (%) Mean ⫾ SD Median Body mass index (kg/m2) Mean ⫾ SD Median Systolic blood pressure (mm Hg) Mean ⫾ SD Median Diastolic blood pressure (mm Hg) Mean ⫾ SD Median Heart rate at rest (beats/min) Mean ⫾ SD Median

Pairwise Comparison p Value

ⱖ90 (n ⫽ 1,346)

60–89 (n ⫽ 4,941)

30–59 (n ⫽ 5,809)

ⱕ29 (n ⫽ 1,068)

57.0 ⫾ 14.3 57.0 74.6%

66.2 ⫾ 13.1 67.0 77.5%

72.9 ⫾ 11.0 74.0 67.4%

73.9 ⫾ 11.4 75.0 59.3%

36.3% 20.4% 40.8%

42.2% 9.8% 46.1%

44.6% 6.9% 46.9%

44.7% 8.6% 44.8%

34.4% 7.8% 44.4% 4.7% 6.4% 2.2% 51.7% 36.3% 21.6% 18.1% 7.3% 32.0% 56.7% 14.0% 11.0% 22.1%

54.7% 4.1% 30.3% 3.1% 6.2% 1.4% 62.6% 39.5% 27.9% 28.1% 9.0% 30.4% 60.0% 15.9% 8.9% 26.6%

69.6% 2.4% 18.0% 2.8% 6.1% 0.8% 70.7% 40.6% 35.9% 36.3% 13.2% 35.7% 64.3% 17.9% 9.1% 25.3%

73.9% 2.7% 14.5% 2.5% 5.6% 0.5% 74.2% 40.4% 40.0% 36.6% 19.7% 49.9% 71.5% 18.2% 8.4% 25.1%

20.4% 29.5% 18.3% 1.6%

22.9% 27.4% 15.8% 2.4%

18.6% 26.6% 19.7% 2.7%

13.7% 23.3% 24.3% 3.9%

25.5 ⫾ 7.1 25.0

25.6 ⫾ 7.0 25.0

25.2 ⫾ 7.0 25.0

25.3 ⫾ 7.0 25.0

30.3 ⫾ 7.4 29.2

29.1 ⫾ 6.7 28.2

27.9 ⫾ 6.2 27.1

27.3 ⫾ 6.7 26.3

120.1 ⫾ 18.3 120.0

121.1 ⫾ 18.6 120.0

119.3 ⫾ 19.1 120.0

120.7 ⫾ 20.3 120.0

72.9 ⫾ 11.3 70.0

71.6 ⫾ 11.2 70.0

68.6 ⫾ 11.0 70.0

67.7 ⫾ 12.2 68.0

73.9 ⫾ 12.2 72.0

72.0 ⫾ 11.5 71.0

71.8 ⫾ 11.2 70.0

72.3 ⫾ 11.1 72.0

cardiology practices in the United States and to assess the effect of CKD on adherence to guideline-recommended therapies. Methods IMPROVE HF was a prospective, longitudinal cohort study undertaken to characterize the current treatment of patients receiving care in outpatient cardiology practice settings for chronic HF or prior myocardial infarction and left ventricular dysfunction. The overall study objectives, design, and methods, including definitions of the 7 process measures, have been previously described.14,15 In brief,

p Value

Stage 2 vs 1

Stage 3 vs 1

Stage 4/5 vs 1

⬍0.001

⬍0.001

⬍0.001

⬍0.001

⬍0.001 ⬍0.001

0.082 ⬍0.001

⬍0.001 ⬍0.001

⬍0.001 ⬍0.001

⬍0.001

⬍0.001

⬍0.001

⬍0.001

⬍0.001 0.028 ⬍0.001 ⬍0.001 ⬍0.001 ⬍0.001 ⬍0.001 0.001 0.088 0.011 ⬍0.001

⬍0.001 0.087 ⬍0.001 ⬍0.001 0.137 0.777 0.081 0.261 — 0.003 0.032

⬍0.001 0.009 ⬍0.001 ⬍0.001 ⬍0.001 0.030 ⬍0.001 0.002 — 0.043 0.041

⬍0.001 0.118 ⬍0.001 ⬍0.001 ⬍0.001 ⬍0.001 ⬍0.001 0.018 — 0.267 ⬍0.001

0.031

1.000

0.611

1.000

⬍0.001

⬍0.001

⬍0.001

⬍0.001

⬍0.001

0.405

1.000

1.000

⬍0.001

0.001

⬍0.001

⬍0.001

⬍0.001

⬍0.001

⬍0.001

0.004

community-based practices, including single-specialty and multispecialty cardiology practices representing all geographic regions of the United States, were invited to participate.15 Patient eligibility criteria included a diagnosis of HF documented by physician assessment on ⱖ2 separate visits for HF treatment in the current practice setting during the 2-year period before the initiation of IMPROVE HF. Left ventricular dysfunction was confirmed by quantitative or qualitative determination of a left ventricular ejection fraction of ⱕ35%, as measured from the most recent echocardiogram, nuclear multiple-gated acquisition scan, contrast ventriculogram, or magnetic resonance imaging scan.15

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Table 2 Comparison of baseline patient laboratory and QRS duration measures by chronic kidney disease (CKD) stage eGFR (ml/min/1.73 m2)

Characteristic ⱖ90 (n ⫽ 1,346) Sodium (mEq/L) Mean ⫾ SD Median Potassium (mEq/L) Mean ⫾ SD Median Blood urea nitrogen (mg/dl) Mean ⫾ SD Median Creatinine (mg/dl) Mean ⫾ SD Median Albumin (mg/dl) Mean ⫾ SD Median Hemoglobin (g/dl) Mean ⫾ SD Median B-type natriuretic peptide (pg/dl) Mean ⫾ SD Median QRS duration (ms) Mean ⫾ SD Median

60–89 (n ⫽ 4,941)

30–59 (n ⫽ 5,809)

Pairwise Comparison p Value ⱕ29 (n ⫽ 1,068)

p Value

Stage 2 vs 1

Stage 3 vs 1

Stage 4 vs 1

138.8 ⫾ 3.4 139.0

139.3 ⫾ 3.3 140.0

139.3 ⫾ 4.2 140.0

138.8 ⫾ 3.9 139.0

⬍0.001

⬍0.001

⬍0.001

1.000

4.3 ⫾ 1.9 4.2

4.4 ⫾ 1.2 4.3

4.5 ⫾ 2.5 4.5

4.5 ⫾ 1.2 4.5

⬍0.001

1.000

0.003

0.093

15.2 ⫾ 6.4 14.0

18.8 ⫾ 6.4 18.0

29.3 ⫾ 12.6 27.0

52.4 ⫾ 22.1 49.0

⬍0.001

⬍0.001

⬍0.001

⬍0.001

0.8 ⫾ 0.1 0.8

1.1 ⫾ 0.2 1.1

1.5 ⫾ 0.3 1.5

3.2 ⫾ 1.8 2.6

⬍0.001

⬍0.001

⬍0.001

⬍0.001

4.1 ⫾ 1.9 4.1

4.0 ⫾ 1.1 4.0

3.9 ⫾ 0.9 4.0

3.7 ⫾ 0.6 3.8

⬍0.001

0.326

⬍0.001

⬍0.001

13.7 ⫾ 1.8 13.8

13.7 ⫾ 1.8 13.8

13.0 ⫾ 2.0 12.9

12.0 ⫾ 1.7 11.9

⬍0.001

1.000

⬍0.001

⬍0.001

446.2 ⫾ 674.8 202.0

549.6 ⫾ 795.8 289.0

775.1 ⫾ 932.3 443.0

1,169.5 ⫾ 1,157.3 791.0

⬍0.001

0.219

⬍0.001

⬍0.001

118.2 ⫾ 35.3 108.0

126.5 ⫾ 38.3 120.0

133.6 ⫾ 40.2 132.0

135.5 ⫾ 42.8 134.0

⬍0.001

⬍0.001

⬍0.001

⬍0.001

The baseline data entered into the IMPROVE HF registry between 2005 and 2007 were used for the present analysis. The baseline data for each patient were abstracted from the medical chart by trained, independent, chart review specialists. The patient data included demographic and clinical characteristics, medical history, previous cardiac treatments, New York Heart Association functional class, laboratory and diagnostic tests and results, and current pharmacologic and device-based HF treatments. Documented contraindications, intolerance, or other reasons (e.g., economic, social, religious, refusal, or patient nonadherence) for not prescribing evidence-based HF therapies were recorded by the chart review specialists when noted in the medical record. QRS duration was obtained from the most recent electrocardiogram (computerized reading or physician measurement). A representative sample of the patient medical records was screened to yield a median of 90 patients with HF for each practice (twenty-fifth and seventy-fifth percentiles, 58 and 107, respectively) for the study baseline period using the method described in the trial design report.15 Analyses examining the effect of renal function on the delivery of guideline-recommended therapies for HF were prespecified in the study protocol. All practices participating in the IMPROVE HF study were approved by a local or central institutional review board or received institutional review board waivers. Data quality was addressed by developing prespecified definitions for each variable, using consistent chart review specialists to collect data, and conducting regular, centralized retraining and testing of the chart review specialists to maintain accuracy in data abstraction. The average interrater reliability (␬) was 0.82. Automated quality checks (1.7

per data field) were performed to check the internal accuracy of the data, and monthly reports were generated to assess the completeness and accuracy of the data submitted. The registry coordinating center was Outcome Sciences (Cambridge, Massachusetts).15 Seven care measures were prospectively selected by the IMPROVE HF Steering Committee to quantify the quality of outpatient delivery of guideline-recommended HF therapy.14,15 All 7 measures were designated as class I therapies (useful and effective) by the American College of Cardiology/ American Heart Association guidelines.16 –19 Of the 7 measures, 4 were American College of Cardiology/American Heart Association outpatient performance measures, and 3 were not. The specific measures included (1) angiotensinconverting enzyme inhibitor/angiotensin receptor blocker (ACE-I/ARB) therapy; (2) ␤-blocker therapy; (3) aldosterone receptor antagonist therapy; (4) anticoagulation therapy for atrial fibrillation or flutter; (5) implantable cardioverter-defibrillator (ICD) therapy; (6) cardiac resynchronization therapy; and (7) patient education about HF. Patients eligible for inclusion in the calculations for each of the 7 care measures included only those who met the defined criteria for each specific care measure and for whom no contraindications, intolerance, refusal, or other documented rationale explaining the reason the guideline-recommended therapy should not be provided were present.15 Documentation of New York Heart Association functional status was a prerequisite for eligibility for the aldosterone antagonist, ICD, and cardiac resynchronization therapy measures. Thus, patients for whom no quantitative or qualitative documentation of New York Heart Association func-

Heart Failure/Renal Function and Heart Failure Therapy

100

p <0.001

1143

p <0.001

90 80

p = 0.002

% Pa
ents Treated

p = 0.026

70 60

p = 0.020

p = 0.008

50

CKD Stage 1 p = 0.896

CKD Stage 2

40

CKD Stage 3

30

CKD Stage 4/5

20 10 0

Figure 1. Rates of treatment with 7 care measures by stage of CKD. Included eligible patients without documented contraindications, intolerance, or medical or patient reasons for not prescribing therapy. CKD stages: stage 1, eGFR ⱖ90 ml/min/1.73 m2; stage 2, eGFR 60 to 89 ml/min/1.73 m2; stage 3, eGFR 30 to 59 ml/min/1.73 m2; and stage 4 –5, eGFR ⱕ29 ml/min/1.73 m2. Aldost. Antag. ⫽ aldosterone antagonist; Anticoag. ⫽ anticoagulation; CRT ⫽ cardiac resynchronization therapy; CRT-D ⫽ CRT with defibrillator; HF Educ ⫽ heart failure education.

tional status consistent with the prespecified definitions were excluded from the analyses of these 3 measures. The estimated glomerular filtration rate (eGFR) was calculated using the Modification of Diet in Renal Disease formula: eGFR ⫽ 186.3 ⫻ (serum creatinine)⫺1.154 ⫻ (age)⫺0.203 ⫻ (1.212 if black) ⫻ (0.742 if female). Patients with missing race data were considered nonblack for these calculations. Patients for whom the eGFR was not calculated because of missing data were not included in any between-group comparisons or multivariate analyses. All statistical analyses were performed by independent biostatisticians contracted by Outcome Sciences. Descriptive statistics for the patient and practice characteristics were calculated and reported for all practices in the IMPROVE HF registry that had completed a practice survey at baseline. These included the sample size, mean, median, and standard deviation for continuous variables and the sample size and percentage for categorical variables. The proportion and 95% confidence intervals (CIs) or median and twenty-fifth and seventy-fifth interquartile percentages were calculated for patient characteristics and the 7 measures stratified by stage of CKD. An overall test of differences in the mean values between the 4 CKD groups was performed using analysis of variance. Pairwise comparisons of patient groups were done for overall tests that were significant using the Bonferroni adjustment. Univariate general estimating equation hierarchical models were then calculated for the patient clinical and demographic characteristics that might be associated with stage of CKD, controlling for possible intrapractice data correlations. Multivariate logistic regression general estimating equation analysis was completed to determine whether the eGFR (analyzed as a continuous variable) was an independent predictor of adherence to each of the 7 guideline-recommended medical therapies after adjusting for patient characteristics and signs and symptoms of HF. The analyses were completed using Statistical Analysis Systems statistical software, version 9.1 (SAS Institute,

Cary, North Carolina). All statistical tests were 2-sided, and results were considered statistically significant at p ⬍0.05. The clinical trial registration unique identifier number was NCT00303979 (available at: www.clinicaltrials.gov). Results The baseline IMPROVE HF data set included medical records for 15,381 patients from 167 outpatient cardiology practices. The serum creatinine levels were missing for 2,217 patients, preventing calculation of the eGFR using the Modification of Diet in Renal Disease method and leaving 13,164 patients for the present analysis. The patients were categorized into 1 of 4 groups according to CKD stage, which determined from the eGFR: group 1, stage 1, eGFR of ⱖ90 ml/min/1.73 m2 (n ⫽ 1,346; 10.2%); group 2, stage 2, eGFR of ⱖ60 to 89 ml/min/1.73 m2 (n ⫽ 4,941; 37.5%); group 3, stage 3, eGFR 30 to 59 ml/min/1.73 m2 (n ⫽ 5,809; 44.1%); and group 4, stages 4 and 5, eGFR ⬍29 ml/min/1.73 m2 (n ⫽ 1,068; 8.1%). The demographic and clinical characteristics for each group are listed in Tables 1 and 2. Older patients, women, and those with an ischemic HF etiology were more likely to have advanced CKD, as were patients with co-morbid conditions such as atrial fibrillation or flutter, diabetes, chronic obstructive pulmonary disease, peripheral vascular disease, hypertension, and prior coronary artery bypass grafting. The New York Heart Association class was greater for patients with more severe CKD. The mean ejection fraction was relatively constant among the 4 groups (⬇25%). The blood urea nitrogen levels and B-type natriuretic peptide levels were significantly greater among patients with more severe renal dysfunction. As renal function decreased, serum hemoglobin levels decreased, from 13.7 mg/dl in group 1 to 12.0 mg/dl in group 4 (p ⬍0.001). QRS duration was sig-

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Table 3 Rates of treatment with 7 care measures by chronic kidney disease (CKD) stage eGFR (ml/min/1.73 m2)

HF Therapy*

ACE-I/ARB ␤ Blocker Aldosterone antagonist Anticoagulation for atrial fibrillation CRT ICD/CRT-D HF education

ⱖ90 (n ⫽ 1346)

60–89 (n ⫽ 4,941)

30–59 (n ⫽ 5,809)

ⱕ29 (n ⫽ 1,068)

1,134/1,298 (87.4) 1,112/1,230 (90.4) 118/243 (48.6) 159/231 (68.8) 35/93 (37.6) 321/670 (47.9) 835/1,346 (62.0)

3,945/4,715 (83.7) 3,920/4,472 (87.7) 303/817 (37.1) 889/1,287 (69.1) 150/386 (38.9) 1,246/2,327 (53.5) 3,141/4,941 (63.6)

4,161/5,317 (78.3) 4,533/5,306 (85.4) 396/1,063 (37.3) 1,335/1,906 (70.0) 259/641 (40.4) 1,492/2,855 (52.3) 3,527/5,809 (60.7)

472/815 (57.9) 834/967 (86.2) 24/64 (37.5) 204/342 (59.6) 54/143 (37.8) 256/531 (48.2) 665/1,069 (62.2)

p Value

⬍0.001 ⬍0.001 0.008 0.002 0.896 0.020 0.026

Data are presented as total treated/total eligible (%). * Eligible patients without documented contraindications, intolerance, or medical or patient reasons for not prescribing a specific therapy. CRT ⫽ cardiac resynchronization therapy; CRT-D ⫽ cardiac resynchronization therapy with defibrillator; ICD ⫽ implantable cardioverter-defibrillator. Table 4 Estimated unadjusted and adjusted odds ratios for estimated glomerular filtration rate (eGFR) as a predictor of adherence to 7 care measures* HF Therapy

ACE-I/ARB ␤ Blocker Aldosterone antagonist Anticoagulation for atrial fibrillation CRT ICD/CRT-D HF education

Univariate

Multivariate

Odds Ratio (95% CI)

Wald Chi-Square

p Value

Odds Ratio (95% CI)

Wald Chi-Square

p Value

0.85 (0.84–0.87) 0.95 (0.93–0.97) 0.99 (0.96–1.01) 0.97 (0.94–1.00) 0.98 (0.96–1.01) 1.00 (0.98–1.01) 1.00 (0.98–1.01)

217.42 20.83 0.88 3.44 1.56 0.44 0.22

⬍0.0001 ⬍0.0001 0.348 0.064 0.212 0.508 0.643

0.94 (0.88–0.99) 1.00 (0.96–1.04) 1.01 (0.93–1.09) 1.01 (0.93–1.10) 0.98 (0.96–1.01) 1.04 (0.99–1.08) 1.01 (0.98–1.04)

5.57 0.00 0.03 0.04 1.02 2.63 0.51

0.018 0.964 0.859 0.838 0.313 0.105 0.477

* Per 10-ml/min decrease in eGFR; multivariate model adjusted for patient characteristics, signs, and symptoms listed in Tables 1 and 2, excluding creatinine, B-type natriuretic peptide, blood urea nitrogen, hemoglobin, and race. Abbreviations as in Table 3.

nificantly longer for patients with stage 4 –5 CKD than for those with stage 1 (135.5 vs 118.2 ms, p ⬍0.001). Figure 1 and Table 3 present the adherence rates for each of the 7 guideline-recommended therapies by CKD stage. As renal function deteriorated, treatment with ACE-I/ARB decreased, from 87.4% in group 1 to 57.9% in group 4 (p ⬍0.001). The rates of ␤-blocker administration were somewhat greater and decreased modestly from groups 1 to 4 (p ⬍0.001). Almost 1/2 of the patients in group 1 were treated with aldosterone antagonists, and approximately 37% of patients in the other 3 groups received this therapy (p ⫽ 0.008). Nearly 70% of eligible patients without contraindications received anticoagulation for atrial fibrillation in groups 1 through 3, but this proportion had decreased to 59.6% in group 4 (p ⫽ 0.002). The use of cardiac resynchronization therapy did not vary significantly among the 4 groups, ranging from 37.6% to 40.4%. Approximately 1/2 of all patients received ICDs. Finally, patient education about HF was documented for approximately 60% of patients in all groups (p ⫽ 0.026). The univariate and adjusted multivariate odds ratios and 95% CIs for adherence to the 7 guideline-recommended HF therapies by eGFR are presented in Table 4. The multivariate general estimating equation model included all patient characteristics (Tables 1 and 2) except B-type natriuretic peptide, blood urea nitrogen, and a history of renal insufficiency, which were excluded for collinearity with the eGFR. Univariate analysis indicated that

ACE-I/ARB and ␤-blocker therapy were significantly less likely to be administered to patients with more severe CKD. None of the other measures were associated with the eGFR. The adjusted multivariate analysis controlling for other patient characteristics revealed that only the use of ACE-I/ ARB therapy was independently associated with the severity of renal dysfunction (odds ratio 0.94, 95% CI 0.88 to 0.99, per 10 ml/min/1.73 m2 decrease in eGFR). Discussion The Acute Decompensated Heart Failure National Registry (ADHERE) findings revealed that 30% of ⬎105,000 hospitalized patients with HF had CKD and 21% had serum creatinine levels ⬎2.0 mg/dl.8 A recent meta-analysis of hospitalized and nonhospitalized patients with HF revealed that 63% of patients had some degree of renal dysfunction and that 29% had moderate or severe impairment.9 The IMPROVE HF study has provided an important opportunity to characterize the prevalence of co-morbid HF and renal dysfunction and to examine the influence of renal status on the adherence to guideline-recommended HF therapies for outpatients with left ventricular systolic dysfunction. Results from the present study demonstrate that renal dysfunction is a frequent co-morbid condition of patients with HF receiving care in outpatient settings, with just ⬎1/2 of patients with stage 3 or 4/5 CKD. Contrary to expectations, the degree of renal function was not independently associ-

Heart Failure/Renal Function and Heart Failure Therapy

ated with adherence to guideline-recommended therapy in the outpatient cardiology practices with the exception of ACE-I/ARB therapy. Few studies have examined the use of guideline-recommended interventions for outpatients with HF and CKD. IMPROVE HF revealed that the overall use of cardiac resynchronization therapy was low for all patients regardless of CKD stage and that treatment with ICDs was most frequent for patients with stage 2 or 3 CKD. Patients with more severe renal dysfunction were less likely to be treated with ACE-I/ARB therapy, and use of the other 6 therapies did not vary significantly among CKD groups after multivariate adjustment. Although the exact reasons for lower use of ACE-I/ARB therapy in patients with severe renal impairment are unknown, the adjustments for patient characteristics excluded age or other co-morbid conditions as the sole reasons for this underuse. Other studies of outpatients with HF and CKD have also demonstrated lower use of ACE-I/ ARB therapy for patients with HF and renal dysfunction. The Minnesota Heart Survey showed that patients with severe renal function impairment (glomerular filtration rate ⬍15 ml/min) were significantly less likely to be treated with ACE-I/ARB therapy during hospitalization (52.0% vs 69.5%, p ⬍0.0001) and at discharge (50.5% vs 65.1%, p ⬍0.0001) than patients with HF and preserved renal function (glomerular filtration rate ⱖ90 ml/min).13 In an evaluation of a national sample of patients discharged from the hospital with a diagnosis of HF who were ⱖ65 years old, had left ventricular systolic dysfunction, and had no documented contraindications for use, ACE-I therapy was prescribed to only 68% of patients.20 Together these data confirm that ACE-I/ARB therapy is underused for patients with HF and CKD despite evidence of reduced 30-day and 1-year mortality, long-term improvement in renal function, and delayed progression of renal disease.13,20,21 It is important to note that the use of guideline-recommended therapies for the overall cohort of patients enrolled in IMPROVE HF was generally low, with only 36% of eligible patients treated with aldosterone antagonists, 51% receiving device therapy, and 61% receiving HF education. Notably, a median of only 27% of patients received all HF therapies for which they were eligible.14 The finding that the use of aldosterone antagonists was similar in patients with normal renal function and those with more advanced CKD warrants additional consideration because of the greater rate of complications with aldosterone antagonists in patients with severe renal dysfunction and current American College of Cardiology/American Heart Association HF guidelines, which discourage their use in patients with elevated serum creatinine (⬎2.5 and ⬎2.0 mg/dl in men and women, respectively).19 This observation suggests that more effective education on the appropriate use of aldosterone antagonists might be needed. Previous studies have suggested that guideline-recommended therapies are less likely to be used in patients with a lower eGFR. Of the hospitalized patients in the Get With The Guidelines—Heart Failure Program Study (GWTGHF), lower rates of the use of ␤ blockers, ICDs, cardiac resynchronization therapy, and anticoagulation for atrial fibrillation have been reported in patients with HF with worse kidney function.12 In contrast, multivariate analyses

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completed for the present study revealed that anticoagulation treatment of atrial fibrillation was independent of the eGFR. The similar rates of ICD and cardiac resynchronization therapy use for patients with CKD are of interest, because some studies have suggested that patients with more advanced CKD might derive less benefit from ICD therapy than those with preserved renal function.22,23 Although discharge instructions were previously reported to be less likely to be provided to patients with more advanced kidney disease,12 in the present study HF education was provided at similar rates, irrespective of the severity of CKD. Lower use of certain evidence-based therapies among high-risk patients with HF and CKD has a number of potential explanations. First, underuse might reflect physician training, education, or perceptions. Second, the evidence on which the guideline recommendations have been made came from randomized trials that largely excluded patients with significant renal dysfunction.24 Patients with CKD might be less likely to tolerate, and more likely to experience the adverse effects of, HF medications or device therapy, including hyperkalemia, bleeding, and infection. Thus, physicians might be less likely to follow the recommendations in the absence of strong evidence of efficacy in patients with renal dysfunction. However, the results of the present study suggest that the differences in treatment observed were attributable to patient characteristics other than renal function. This was also suggested in a previous analysis of baseline findings from IMPROVE HF, which revealed that both patient and practice characteristics were independent predictors of variations in use of guidelinerecommended interventions.14 Together these findings suggest that, at least among outpatient cardiology practices, the severity of renal dysfunction does not significantly influence decisions to use many guideline-recommended medical and device therapies for patients with systolic HF. The present study also identified potential opportunities to improve the use of evidence-based therapies in patients with HF irrespective of renal function. Whether performance improvement interventions will enhance the use of guideline-recommended therapies for patients with HF and CKD requires additional study. Several inherent limitations were present in the design of IMPROVE HF. First, the data were collected by medical chart review, which depends on the accuracy and completeness of documentation and abstraction. Second, a proportion of treatment-eligible patients who did not receive treatment might have had contraindications or intolerance that was not documented in the medical record. In particular, there might have been appropriate but unexplained reasons for nonadherence to recommended HF therapies for sicker patients, such as those with renal insufficiency. Third, although the Modification of Diet in Renal Disease formula has been recommended for estimating renal function, it has not been validated in patients with HF and might not be as accurate as direct measurement of glomerular filtration rate in these patients. Fourth, residual measured or unmeasured confounding variables might have accounted for some of the findings. Fifth, the New York Heart Association functional class was documented for only 58.5% of patients, which prevented the determination of eligibility for ICD therapy,

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The American Journal of Cardiology (www.AJConline.org)

cardiac resynchronization therapy, and aldosterone antagonist therapy for the entire cohort. Sixth, patients enrolled in the IMPROVE HF study might not have been fully representative of the general population of patients with HF treated in the outpatient setting. Thus, these results might not apply to practices with patient demographic and clinical characteristics different from those of the practices in the IMPROVE HF study. Finally, these findings have established only associations, not causality, among renal function, patient characteristics, and the use of guideline-recommended therapies. We were unable to explore the relation between the use of guideline-recommended therapies and clinical outcomes in patients with HF and CKD. Thus, the full implications of the use or lack of use of these 7 guideline-recommended therapies for patients with HF and CKD remain unclear. 1. Fonarow GC, Heywood JT. The confounding issue of comorbid renal insufficiency. Am J Med 2006;119:S17–S25. 2. Liang KV, Williams AW, Greene EL, Redfield MM. Acute decompensated heart failure and the cardiorenal syndrome. Crit Care Med 2008;36:S75–S88. 3. Saltzman HE, Sharma K, Mather PJ, Rubin S, Adams S, Whellan DJ. Renal dysfunction in heart failure patients: what is the evidence? Heart Fail Rev 2007;12:37– 47. 4. Schiffrin EL, Lipman ML, Mann JFE. Chronic kidney disease: effects on the cardiovascular system. Circulation 2007;116:85–97. 5. Bibbins-Domingo K, Lin F, Vittinghoff E, Barrett-Connor E, Grady D, Shlipak MG. Renal insufficiency as an independent predictor of mortality among women with heart failure. J Am Coll Cardiol 2004;44:1593–1600. 6. Ezekowitz J, McAlister FA, Humphries KH, Norris CM, Tonelli M, Ghali WA, Knudtson ML; APPROACH Investigators. The association among renal insufficiency, pharmacotherapy, and outcomes in 6,427 patients with heart failure and coronary artery disease. J Am Coll Cardiol 2004;44:1587–1592. 7. Hillege HL, Nitsch D, Pfeffer MA, Swedberg K, McMurray JJ, Yusuf S, Granger CB, Michelson EL, Ostergren J, Cornel JH, de Zeeuw D, Pocock S, van Veldhuisen DJ; Candesartan in Heart Failure: Assessment of Reduction in Mortality and Morbidity (CHARM) Investigators. Renal function as a predictor of outcome in a broad spectrum of patients with heart failure. Circulation 2006;113:671– 678. 8. Adams KF Jr, Fonarow GC, Emerman CL, LeJemtel TH, Costanzo MR, Abraham WT, Berkowitz RL, Galvao M, Horton DP; ADHERE Scientific Advisory Committee and Investigators. Characteristics and outcomes of patients hospitalized for heart failure in the United States: rationale, design, and preliminary observations from the first 100,000 cases in the Acute Decompensated Heart Failure National Registry (ADHERE). Am Heart J 2005;149:209 –216. 9. Smith GL, Lichtman JH, Bracken MB, Shlipak MG, Phillips CO, DiCapua P, Krumholz HM. Renal impairment and outcomes in heart failure: systematic review and meta-analysis. J Am Coll Cardiol 2006;47:1987–1996. 10. Owan TE, Hodge DO, Herges RM, Jacobsen SJ, Roger VL, Redfield MM. Secular trends in renal dysfunction and outcomes in hospitalized heart failure patients. J Card Fail 2006;12:257–262. 11. Lahoz C, Mostaza JM, Mantilla MT, Taboada M, Tranche S, LopezRodriquez I, Monteiro B, Soler B, Sanchez-Zamorano MA, MartinJadraque R. Achievement of therapeutic goals and utilization of evidence-based cardiovascular therapies in coronary heart disease patients with chronic kidney disease. Am J Cardiol 2008;101:1098 –1102. 12. Patel UD, Hernandez AF, Liang L, Peterson ED, LaBresh KA, Yancy CW, Albert NM, Ellrodt G, Fonarow GC. Quality of care and outcomes among patients with heart failure and chronic kidney disease: a Get With the Guidelines–Heart Failure Program study. Am Heart J 2008;156:674–681. 13. Berger AK, Duval S, Manske C, Vazquez G, Barber C, Miller L, Luepker RV. Angiotensin-converting enzyme inhibitors and angiotensin receptor blockers in patients with congestive heart failure and chronic kidney disease. Am Heart J 2007;153:1064 –1073. 14. Fonarow GC, Yancy CW, Albert NM, Curtis AB, Gattis Stough W, Gheorghiade M, Heywood JT, McBride ML, Mehra MR, O’Connor CM, Reyn-

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