Heart Failure
Transient and persistent worsening renal function during hospitalization for acute heart failure Arun Krishnamoorthy, MD, a,b Melissa A. Greiner, MS, a Puza P. Sharma, MBBS, MPH, PhD, c Adam D. DeVore, MD, a,b Katherine Waltman Johnson, PharmD, c Gregg C. Fonarow, MD, d Lesley H. Curtis, PhD, a,b and Adrian F. Hernandez, MD, MHS a,b Durham, NC; East Hanover, NJ; and Los Angeles, CA
Background Transient and persistent worsening renal function (WRF) may be associated with different risks during hospitalization for acute heart failure. We compared outcomes of patients hospitalized for acute heart failure with transient, persistent, or no WRF. Methods
We identified patients 65 years or older hospitalized with acute heart failure from a clinical registry linked to Medicare claims data. We defined WRF as an increase in serum creatinine of ≥0.3 mg/dL after admission. We further classified patients with WRF by the difference between admission and last recorded serum creatinine levels into transient WRF (b0.3 mg/dL) or persistent WRF (≥0.3 mg/dL). We examined unadjusted rates and adjusted associations between 90-day outcomes and WRF status.
Results Among 27,309 patients, 18,568 (68.0%) had no WRF, 3,205 (11.7%) had transient WRF, and 5,536 (20.3%) had persistent WRF. Patients with WRF had higher observed rates of 90-day postdischarge all-cause readmission and 90-day postadmission mortality (P b .001). After multivariable adjustment, transient WRF (hazard ratio [HR] 1.19, 99% CI 1.05-1.35) and persistent WRF (HR 1.73, 99% CI 1.57-1.91) were associated with higher risks of 90-day postadmission mortality (P b .001 for both). Compared with transient WRF, persistent WRF was associated with a higher risk of 90-day postadmission mortality (HR 1.46, 99% CI 1.28-1.66, P b .001). Conclusions Transient and persistent WRF during hospitalization for acute heart failure were associated with higher adjusted risks for 90-day all-cause postadmission mortality. Patients with persistent WRF had worse outcomes. (Am Heart J 2014;168:891-900.) Worsening renal function (WRF), commonly defined as an increase in serum creatinine level of ≥0.3 mg/dL, occurs in approximately 20% to 45% of patients hospitalized for acute heart failure. 1-15 Development of WRF is associated with an increased risk of adverse inpatient, 30-day, and long-term postdischarge outcomes, including mortality. 1,7,16 Thus, WRF represents a significant event during acute heart failure, and the prevention and treatment of WRF remain important targets. Recent clinical trial evidence suggests that the risks associated with WRF may differ depending on whether From the aDuke Clinical Research Institute, Duke University School of Medicine, Durham, NC, bDepartment of Medicine, Duke University School of Medicine, Durham, NC, c Novartis Pharmaceuticals Corporation, East Hanover, NJ, and dAhmanson-UCLA Cardiomyopathy Center, University of California, Los Angeles, CA. Hector O. Ventura, MD, served as guest editor for this article. Funding/support. This study was supported by a research agreement between Duke University and Novartis Pharmaceuticals Corporation. Submitted July 22, 2014; accepted August 17, 2014. Reprint requests: Adrian F. Hernandez, MD, MHS, Duke Clinical Research Institute, PO Box 17969, Durham, NC 27715. E-mail: [email protected] 0002-8703 © 2014 Elsevier Inc. All rights reserved http://dx.doi.org/10.1016/j.ahj.2014.08.016
WRF is transient or persistent. In the DOSE study, WRF occurred more often over 72 hours during hospitalization for acute heart failure in patients treated with higher doses of diuretics as compared with those randomized to a lowdose diuretic strategy. However, there was no significant difference in 60-day clinical outcomes between the 2 groups. 17 Moreover, in an analysis of patients enrolled in the VMAC trial over a 30-day period extending postdischarge, persistent WRF was associated with a higher risk of 6-month mortality as compared with transient WRF. 18 To further understand differences among patients with WRF during hospitalization for acute heart failure, we examined a cohort of patients from the Acute Decompensated Heart Failure National Registry (ADHERE) linked with Medicare claims. The objectives of our analysis were to describe the prevalence and characteristics of patients with inhospital transient and persistent WRF and to compare 90-day outcomes between patients with no WRF, transient WRF, or persistent WRF. We used an intermediate follow-up period of 90 days for observation of outcomes because new payment models being evaluated by the Centers for Medicare & Medicaid Services may extend up to 90 days after hospital
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Table I. Baseline characteristics of the study population Characteristic Age, mean (SD), y Male, n (%) Race, n (%) Black White Other/unknown Medical history, n (%) Anemia Atrial fibrillation Chronic renal insufficiency COPD Coronary artery disease Diabetes mellitus Dyslipidemia Heart failure hospitalization in the past 6 m Hypertension Myocardial infarction Peripheral vascular disease Smoking status Never smoked Former smoker Current smoker Missing Stroke or TIA Medical devices, n (%) CRT-P ICD or CRT-D Pacemaker alone Initial evaluation, n (%) Dyspnea Ejection fraction b40% ≥40% Missing Fatigue Pulmonary edema Rales Initial vital signs Pulse, mean (SD), beat/min Systolic blood pressure, mean (SD), mm Hg b140 mm Hg, n (%) ≥140 mm Hg, n (%) Initial laboratory test results Hemoglobin level, mean (SD), g/dL BNP, mean (SD), pg/mL⁎ Missing, n (%) Chronic kidney disease stage, n (%) Stage 1 Stage 2 Stage 3 Stage 4 Stage 5 eGFR, mean (SD), mL/min/1.73 m 2 Serum creatinine, mean (SD), mg/dL Serum sodium, mean (SD), mEq/L Discharge or last known laboratory test result eGFR, mean (SD), mL/min/1.73 m 2 Chronic kidney disease stage, n (%) Stage 1 Stage 2 Stage 3 Stage 4
No WRF (n = 18,568)
Transient WRF (n = 3205)
Persistent WRF (n = 5536)
P
79.9 (7.8) 8054 (43.4)
79.4 (7.5) 1449 (45.2)
80.1 (7.8) 2356 (42.6)
b.001 .05 b.001
1989 (10.7) 15,848 (85.4) 731 (3.9)
342 (10.7) 2688 (83.9) 175 (5.5)
671 (12.1) 4570 (82.6) 295 (5.3)
10,425 (56.1) 6923 (37.3) 4303 (23.2) 5512 (29.7) 11,013 (59.3) 7260 (39.1) 7235 (39.0) 2325 (12.5) 14,035 (75.6) 5300 (28.5) 3330 (17.9)
1847 1086 1064 1075 1971 1405 1270 360 2472 915 630
(57.6) (33.9) (33.2) (33.5) (61.5) (43.8) (39.6) (11.2) (77.1) (28.5) (19.7)
3380 1773 2004 1630 3346 2423 2216 634 4366 1631 1099
(61.1) (32.0) (36.2) (29.4) (60.4) (43.8) (40.0) (11.5) (78.9) (29.5) (19.9)
1426 1238 243 298 645
(44.5) (38.6) (7.6) (9.3) (20.1)
2669 2011 388 468 1041
(48.2) (36.3) (7.0) (8.5) (18.8)
.02
8997 6660 1400 1511 3370
(48.5) (35.9) (7.5) (8.1) (18.1)
b.001 b.001 b.001 b.001 .04 b.001 .33 .02 b.001 .40 .001 .002
332 (1.8) 1203 (6.5) 2554 (13.8)
48 (1.5) 193 (6.0) 418 (13.0)
85 (1.5) 305 (5.5) 720 (13.0)
.28 .03 .25
16,534 (89.0)
2902 (90.5)
4974 (89.8)
.02 b.001
6800 9163 2605 5705 15,971 12,339
(36.6) (49.3) (14.0) (30.7) (86.0) (66.5)
1176 1707 322 1008 2862 2182
(36.7) (53.3) (10.0) (31.5) (89.3) (68.1)
1947 2863 726 1612 4900 3805
(35.2) (51.7) (13.1) (29.1) (88.5) (68.7)
.03 b.001 .003
86.1 143.1 9047 9521
(21.6) (30.7) (48.7) (51.3)
87.4 145.8 1425 1780
(21.5) (31.5) (44.5) (55.5)
86.8 150.1 2164 3372
(20.8) (31.4) (39.1) (60.9)
b.001 b.001 b.001 b.001
12.0 (2.0) 1186.3 (1,122.4) 4715 (25.4)
12.0 (2.0) 1278.4 (1,183.2) 716 (22.3)
11.9 (1.9) 1287.2 (1,149.7) 1196 (21.6)
1022 (5.5) 5155 (27.8) 9245 (49.8) 2525 (13.6) 621 (3.3) 51.8 (24.0) 1.6 (1.1) 138.0 (4.7)
129 (4.0) 660 (20.6) 1698 (53.0) 500 (15.6) 218 (6.8) 46.7 (23.3) 1.8 (1.3) 137.9 (4.7)
275 (5.0) 1170 (21.1) 2785 (50.3) 978 (17.7) 328 (5.9) 47.8 (25.2) 1.7 (1.2) 138.5 (4.5)
54.5 (23.6)
45.6 (21.3)
31.2 (14.4)
1090 5680 9535 1855
84 587 1867 491
– 164 (3.0) 2719 (49.1) 1914 (34.6)
(5.9) (30.6) (51.4) (10.0)
(2.6) (18.3) (58.3) (15.3)
b.001 b.001 b.001 b.001
b.001 b.001 b.001 b.001 b.001
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Table I (continued) Characteristic Stage 5 Serum creatinine, mean (SD), mg/dL Admission medications, n (%) ACE inhibitor or ARB Aldosterone antagonist⁎ Aspirin β-Blocker Clopidogrel Lipid-lowering agent Loop diuretic Warfarin Discharge medications, n (%) ACE inhibitor or ARB Aldosterone antagonist⁎ Aspirin β-Blocker Clopidogrel Lipid-lowering agent Loop diuretic Warfarin Year of index hospitalization, n (%) 2003 2004 2005 2006
No WRF (n = 18,568)
Transient WRF (n = 3205)
Persistent WRF (n = 5536)
P
408 (2.2) 1.4 (0.8)
176 (5.5) 1.7 (1.1)
735 (13.3) 2.4 (1.6)
b.001
9335 1491 7893 10,405 2457 7051 11,633 5032
(50.3) (8.3) (42.5) (56.0) (13.2) (38.0) (62.7) (27.1)
1579 237 1390 1791 476 1231 1926 779
(49.3) (7.6) (43.4) (55.9) (14.9) (38.4) (60.1) (24.3)
2669 395 2374 3047 842 2102 3212 1227
(48.2) (7.3) (42.9) (55.0) (15.2) (38.0) (58.0) (22.2)
.02 .06 .63 .42 b.001 .89 b.001 b.001
11,433 2882 8972 11,880 2744 7093 14,911 5303
(61.6) (15.5) (48.3) (64.0) (14.8) (38.2) (80.3) (28.6)
1722 429 1583 2099 562 1261 2271 843
(53.7) (13.4) (49.4) (65.5) (17.5) (39.3) (70.9) (26.3)
2880 (52.0) 754 (13.6) 2545 (46.0) 3320 (60.0) 831 (15.0) 2048 (37.0) 3837 (69.3) 1240 (22.4)
b.001 b.001 .002 b.001 b.001 .08 b.001 b.001 .79
2372 10,863 4915 418
(12.8) (58.5) (26.5) (2.3)
404 1851 875 75
(12.6) (57.8) (27.3) (2.3)
744 3213 1451 128
(13.4) (58.0) (26.2) (2.3)
Abbreviations: COPD, Chronic obstructive pulmonary disease; TIA, transient ischemic attack; CRT-P, cardiac resynchronization therapy with pacemaker; ICD, implantable cardioverter-defibrillator; CRT-D, cardiac resynchronization therapy with defibrillator; ACE, angiotensin-converting enzyme; ARB, angiotensin II receptor blocker. ⁎ The BNP level and aldosterone antagonist variables were not included in the multivariable models because they had high rates of missingness.
discharge and because of the potential competing risk for mortality associated with shorter term readmission. 19,20
Methods Data sources ADHERE was established to improve understanding of the clinical characteristics, management, and outcomes of patients hospitalized with acute decompensated heart failure. 21 More than 300 community and academic medical centers in the United States participated and N185,000 patients were enrolled from January 2001 to March 2006. To analyze long-term follow-up data, we obtained Medicare standard analytic claim files from the Centers for Medicare & Medicaid Services. These files contain encrypted identifiers that allow for longitudinal follow-up of fee-forservice Medicare beneficiaries. We used indirect identifiers to link registry records to Medicare files using methods that have been described previously. 22 Almost 80% of the registry records have been linked with Medicare claims, and older patients enrolled in the registry constitute a nationally representative sample of fee-for-service Medicare beneficiaries. 22,23 Study population We included patients 65 years or older living in the United States who had a registry hospitalization linked to
Medicare claims between January 1, 2003, and March 31, 2006, the period during which serum creatinine level was recorded. If multiple registry hospitalizations were identified for a single patient, we used the earliest as the index hospitalization. We restricted the population to patients enrolled in fee-for-service Medicare at the time of the index hospitalization and for at least 6 months before the hospitalization. To identify WRF, we required that admission serum creatinine level and at least 2 subsequent creatinine values were recorded in the registry. We excluded patients who were admitted electively for the index hospitalization. For the analysis of outcomes at discharge or in the 90 days after discharge, we excluded patients who died in the hospital, left against medical advice, or were discharged or transferred to another short-term hospital or hospice. In addition, patients who enrolled in Medicare managed care during the follow-up period were excluded from the measurement of days alive and out of the hospital and Medicare payments.
Worsening renal function We defined WRF as any increase in serum creatinine level of ≥0.3 mg/dL during the index hospitalization over the admission value recorded in the registry. We further classified patients with WRF by the difference between the last recorded serum creatinine level and the admission
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Table II. Observed outcomes by study group Outcome All patients No. of patients Length of stay, mean (SD), d ICU or CCU stay, n (%) Length of stay among patients with ICU/CCU stay, mean (SD), d Length of stay among all patients, mean (SD), d Inhospital mortality, n (%) Inhospital Medicare facility payments, $⁎ Mean (SD) Median (interquartile range) Mortality at 90 d after admission, n (%) † Patients discharged alive No. of patients Clinical status at discharge, n (%) Asymptomatic Symptomatic but improved Other/unknown All-cause readmission at 90 d after discharge, n (%) † Heart failure readmission at 90 d after discharge, n (%) † Patients discharged alive and not censored at 90 d No. of patients Days alive and out of the hospital at 90 d after discharge, mean (SD) Medicare payments at 90 d after discharge, $⁎ Mean (SD) Median (interquartile range)
No WRF
Transient WRF
Persistent WRF
P
18,568 5.3 (4.6) 2455 (13.2) 3.4 (4.2) 0.4 (1.9) 453 (2.4)
3205 7.8 (5.0) 662 (20.7) 4.5 (4.2) 0.9 (2.6) 102 (3.2)
5536 6.4 (5.2) 874 (15.8) 4.1 (4.7) 0.7 (2.4) 512 (9.2)
b.001 b.001 b.001 b.001 b.001
9165 (11,275) 6657 (5583-8571) 3002 (16.2)
10,700 (12,177) 7042 (5835-9859) 598 (18.7)
9401 (10,892) 6696 (5591-8820) 1297 (23.5)
b.001 b.001 b.001
17,256
2920
4720
(46.9) (40.8) (12.3) (40.3) (16.8)
1284 (44.0) 1262 (43.2) 374 (12.8) 1272 (43.6) 512 (17.6)
2151 (45.6) 1979 (41.9) 590 (12.5) 1984 (42.1) 756 (16.1)
.04 .008 .04 .69 b.001 .17
17,163 79.3 (21.3)
2904 77.3 (23.1)
4690 78.4 (22.3)
b.001
10,608 (19,447) 2539 (610-12,748)
12,534 (21,409) 4739 (761-15,835)
11,594 (20,370) 3521 (658-15,051)
b.001 b.001
8091 7048 2117 6938 2896
⁎ Expressed in 2010 US dollars. † Expressed as number of patients (cumulative incidence per 100 patients at risk).
creatinine value into either transient (b0.3 mg/dL) or persistent (≥0.3 mg/dL) inhospital WRF. The last recorded serum creatinine value did not necessarily correspond to the discharge date. We classified patients into 3 groups: no WRF, transient WRF, or persistent WRF.
Outcomes The main outcomes of interest were mortality, all-cause readmission, heart failure readmission, and days alive and out of the hospital. We measured mortality within 90 days after admission, and we measured all-cause readmission, heart failure readmission, and days alive and out of the hospital within 90 days after discharge. We also analyzed index hospitalization length of stay, intensive care unit (ICU) or cardiac care unit (CCU) length of stay, index hospitalization mortality, clinical status at discharge, and Medicare payments at 90 days after discharge. We determined mortality during the index hospitalization based on discharge status on the Medicare inpatient claims, and we measured 90-day postadmission mortality based on death dates in the Medicare denominator files. We calculated index hospitalization length of stay using the Medicare index hospitalization claim. Intensive care unit and CCU length of stay and clinical status at discharge (categorized as asymptomatic, symptomatic but improved, or other/unknown) were based on the
registry data. We calculated total days alive and out of the hospital in the 90 days after discharge based on death dates in the Medicare denominator files and hospitalization dates in the Medicare inpatient files. We identified allcause readmission using subsequent inpatient claims except those for transfers to or from another hospital and admissions for rehabilitation (diagnosis-related group 462 or International Classification of Diseases, Ninth Revision, Clinical Modification, diagnosis code V57.xx). We identified readmission for heart failure based on a primary diagnosis of heart failure (International Classification of Diseases, Ninth Revision, Clinical Modification, diagnosis codes 428.x, 402.x1, 404.x1, or 404.x3) on the inpatient claim. We calculated total Medicare payments in the 90 days after discharge by summing payments for inpatient, outpatient, and carrier claims. We report payments in 2010 US dollars with inflation adjustment using the medical care component of the Consumer Price Index.
Covariates Variables from the registry included demographic characteristics, medical history, initial evaluation results, initial vital signs, laboratory test results, and admission and discharge medications. For variables with low rates of missingness (ie, b5% of records), we imputed missing
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continuous variables to the overall median value, dichotomous variables to “no,” and multichotomous variables to the most frequent categorical value. 24,25 For variables with N5% missingness (including smoking status, B-type natriuretic peptide [BNP] level, and ejection fraction), we treated missing values as a separate category.
Figure 1
Cumulative Incidence, %
A
30%
No worsening renal function Transient worsening renal function Persistent worsening renal function
20%
10%
0% 0
10
20
30
40
50
60
70
80
90
Days from Index Hospitalization Admission
Cumulative Incidence, %
B
50%
No worsening renal function Transient worsening renal function Persistent worsening renal function
40%
30%
20%
10%
0% 0
10
20
30
40
50
60
70
80
90
Days from Index Hospitalization Discharge
Cumulative Incidence, %
C
30%
No worsening renal function Transient worsening renal function Persistent worsening renal function
20%
10%
0% 0
10
20
30
40
50
60
70
80
90
Days from Index Hospitalization Discharge Cumulative incidence of mortality in the 90 days after admission (A), all-cause readmission in the 90 days after discharge (B), and heart failure readmission in the 90 days after discharge (C).
Statistical analysis We present baseline characteristics of the study population stratified by WRF status (no WRF, transient WRF, and persistent WRF). We present categorical variables as frequencies with percentages and continuous variables as means with SDs. We tested for differences in baseline variables between groups using χ 2 tests for categorical variables and Kruskal-Wallis tests for continuous variables. We described observed outcomes by study group. For inhospital mortality and clinical status at discharge, we calculated frequencies with percentages and tested for differences between groups using χ 2 tests. For hospital length of stay, ICU length of stay, days alive and out of the hospital, and Medicare payments, we calculated means with SDs and compared the mean difference between groups using Kruskal-Wallis tests. For 90-day mortality, we calculated the cumulative incidence of mortality using Kaplan-Meier estimates and tested for differences between the groups using log-rank tests. For 90-day all-cause and heart failure readmission, we calculated incidence using estimates from the cumulative incidence function to account for the competing risk of mortality and tested for group differences using Gray tests. 26 We examined the unadjusted and adjusted associations between WRF classification and 90-day outcomes. For 90-day mortality and readmission, we used Cox proportional hazards models with robust standard errors to account for clustering of patients within hospitals. We used a linear mixed model for days alive and out of the hospital and a generalized linear mixed model with a log link and Poisson distribution for Medicare payments. In all the mixed models, we accounted for clustering of patients within hospitals by estimating hospital-level random intercepts. In the unadjusted models, WRF category was the only predictor. In the adjusted models, we included other baseline characteristics (ie, demographic characteristics, medical history, laboratory/test results, and medications). For mortality and readmission survival analyses, we censored data for patients if they enrolled in Medicare-managed care. For readmission outcomes, we censored data for patients at the time of death. Because of multiple comparisons, we used a 2-tailed P = .01 to establish statistical significance, and we report 99% CIs. We used SAS version 9.3 (SAS Institute, Inc, Cary, NC) for all analyses. The Institutional Review Board of the Duke University Health System approved the study.
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Table III. Unadjusted and adjusted associations between study groups and outcomes Association Outcome Mortality at 90 d after admission⁎ Transient vs no WRF Persistent vs no WRF Persistent vs transient WRF All-cause readmission at 90 d after discharge † Transient vs no WRF Persistent vs no WRF Persistent vs transient WRF HF readmission at 90 days after discharge † Transient vs no WRF Persistent vs no WRF Persistent vs transient WRF
Days alive and out of the hospital at 90 d after discharge ‡ Transient vs no WRF Persistent vs no WRF Persistent vs transient WRF
Medicare payments at 90 d after discharge ‡ Transient vs no WRF Persistent vs no WRF Persistent vs transient WRF
Unadjusted HR (99% CI)
P
Adjusted HR (99% CI)
P
1.17 (1.03-1.33) 1.56 (1.42-1.72) 1.33 (1.17-1.52)
.002 b.001 b.001
1.19 (1.05-1.35) 1.73 (1.57-1.91) 1.46 (1.28-1.66)
b.001 b.001 b.001
1.13 (1.03-1.23) 1.07 (0.99-1.14) 0.95 (0.86-1.04)
b.001 .02 .14
1.06 (0.97-1.17) 1.05 (0.98-1.12) 0.98 (0.89-1.08)
.08 .08 .63
1.06 (0.94-1.20) 0.95 (0.86-1.06) 0.90 (0.79-1.02)
.18 .25 .03
1.02 (0.91-1.15) 0.94 (0.85-1.04) 0.92 (0.81-1.05)
.60 .14 .10
Estimate (99% CI)
P
Estimate (99% CI)
P
−1.99 (−3.12 to −0.87) −0.91 (−1.84 to 0.01) 1.08 (−0.24 to 2.40)
b.001 .01 .03
−1.45 (−2.54 to −0.36) −1.17 (−2.08 to −0.26) 0.28 (−1.00 to 1.56)
b.001 b.001 .57
Cost ratio (99% CI)
P
Cost ratio (99% CI)
P
1.18 (1.09-1.28) 1.11 (1.03-1.19) 0.94 (0.85-1.04)
b.001 b.001 .11
1.09 (1.01-1.18) 1.07 (0.99-1.14) 0.98 (0.89-1.07)
.005 .02 .51
Abbreviation: WRF, Worsening renal function. In addition to the WRF variable, covariates in the multivariable regression models included age, sex, race, anemia, atrial fibrillation, coronary artery disease, chronic renal insufficiency, chronic obstructive pulmonary disease, diabetes mellitus, heart failure hospitalization in the past 6 months, dyslipidemia, hypertension, myocardial infarction, peripheral vascular disease, stroke or transient ischemic attack, smoking status, medical device type, fatigue, rales, pulmonary edema, dyspnea, ejection fraction, pulse, systolic blood pressure, serum sodium, hemoglobin level, serum creatinine, angiotensin-converting enzyme inhibitor or angiotensin II receptor blocker, aspirin, β-blocker, loop diuretic, clopidogrel, lipid-lowering medication, warfarin, and year of index hospitalization. The mortality model included medication information at admission; other models included medication information at discharge. ⁎ Among all patients. † Among patients discharged alive. ‡ Among patients discharged alive and not censored at 90 days after discharge.
Results Among 27,309 patients, 18,568 (68.0%) had no WRF, 3,205 (11.7%) had transient WRF, and 5,536 (20.3%) had persistent WRF (Table I). The average age in each group was approximately 80 years, and most patients were white women. The direction of observed trends was similar for transient and persistent WRF. Patients with WRF were more likely to have a left ventricular ejection fraction of ≥40%, with higher rates in patients with transient WRF. The highest rates of hypertension were in patients with persistent WRF, and there was an equally high rate of diabetes mellitus between the WRF groups. Rates of loop diuretic use both on admission and at discharge were lower in patients with WRF, with slightly lower rates for each in those with persistent WRF. More patients with transient WRF were likely to have pulmonary edema and dyspnea on initial presentation. A history of chronic renal insufficiency at baseline was most common in persistent WRF; the estimated glomerular
filtration rate (eGFR) on admission was also more likely to be lower (and, consequently, the baseline serum creatinine level higher) in those with persistent WRF. Most patients in each group had stage 3 chronic kidney disease at baseline (ie, eGFR of 30-59 mL/min per 1.73 m 2). Table II shows the observed outcomes in each group. Compared with no WRF, patients with either transient or persistent WRF had higher observed rates of 90-day postadmission mortality, with the highest rate among patients with persistent WRF (16.2% vs 18.7% vs 23.5%, P b .001) (Figure 1, A). In addition, both the transient and persistent WRF groups had higher rates of 90-day postdischarge all-cause readmission (Figure 1, B) and fewer days alive and out of the hospital at 90 days. There was no significant difference in observed rates of 90-day postdischarge heart failure readmission between groups (Figure 1, C). Patients with either transient or persistent WRF, compared with no WRF, also had a longer hospital length of stay, higher inhospital mortality, higher
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Figure 2
A
B
C
Hazards of mortality in the 90 days after admission among patients with transient vs no worsening renal function (A), persistent vs no worsening renal function (B), and persistent vs transient worsening renal function (C). Note: The solid lines represent HRs, and the dashed lines, 99% CIs.
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Medicare payments at 90 days after discharge, higher rate of ICU and CCU stays, and longer ICU and CCU length of stay. The mean lengths of stay among patients with no WRF, transient WRF, and persistent WRF were 5.3, 7.8, and 6.4 days, respectively (P b .001). Patients with transient or persistent WRF were more likely to have remained symptomatic but improved at discharge, whereas patients with no WRF were more likely to have been asymptomatic at discharge (ie, clinical status at discharge was noted in the registry as asymptomatic, symptomatic but improved, or other/unknown). Table III shows the unadjusted and adjusted associations between the WRF groups and outcomes. In adjusted analyses, both transient and persistent WRF were associated with a higher risk of 90-day postadmission mortality (hazard ratio [HR] 1.19, 99% CI 1.05-1.35, P b .001 for transient WRF, and HR 1.73, 99% CI 1.57-1.91, P b .001 for persistent WRF) and fewer days alive and out of the hospital at 90 days after discharge (−1.45 days, 99% CI −2.54 to −0.36, P b .001, and −1.17 days, 99% CI −2.08 to −0.26, P b .001) compared with no WRF. After multivariable adjustment, only transient WRF was associated with higher Medicare payments at 90 days after discharge compared with no WRF (P b .005). There were no significant differences between either WRF group compared with no WRF in the risk of 90-day all-cause or heart failure readmission. In the adjusted mortality model, the proportional hazards assumption was not met for the WRF study variable (P b .001). In the comparison between transient WRF and no WRF, the HR attenuated over time and was no longer statistically significant at approximately 30 days after admission (Figure 2, A). The risk associated with persistent WRF, compared with no WRF, also attenuated but remained significantly higher 90 days after admission (Figure 2, B). After multivariable adjustment, persistent WRF was associated with a 46% higher risk of 90-day postadmission mortality (HR 1.46, 99% CI 1.28-1.66, P b .001) compared with transient WRF. However, the HR attenuated over time and was no longer statistically significant at approximately 70 days after admission (Figure 2, C). There was no significant difference at 90 days after discharge in either all-cause or heart failure readmission, days alive and out of the hospital, or Medicare payments in the comparison between persistent and transient WRF.
Discussion In a large cohort of patients hospitalized for acute heart failure, N30% of patients experienced WRF, with transient WRF occurring frequently in more than one-third of the patients with WRF. Patients with transient WRF were similar to patients with persistent WRF, particularly with regard to high rates of relatively preserved ejection fraction, chronic kidney disease (predominantly stage 3 or greater), and signs or symptoms of congestive heart failure at baseline. Furthermore, we observed that any
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WRF, whether transient or persistent, was associated with a higher adjusted risk of postadmission mortality and fewer days alive and out of the hospital at 90 days. However, the hazards of mortality in the comparison of transient WRF and no WRF attenuated over time and were no longer statistically significant at approximately 30 days after admission. In addition, persistent WRF was associated with a significantly higher 90-day mortality risk, compared with transient WRF. Finally, patients with transient but not persistent WRF had higher Medicare payments compared with no WRF. There were no significant differences between transient and persistent WRF for all-cause or heart failure readmission, days alive and out of the hospital, and Medicare payments in the 90 days after discharge. Worsening renal function during acute heart failure has been observed to be associated with worse mortality in many studies, including prior registries. 1,27 Most of these studies defined WRF as a singular event and did not examine trends of renal function over the course of an episode of acute heart failure. However, several recent clinical trial analyses have suggested that patients with recovery of renal function after WRF during acute heart failure may represent a unique cohort distinct from patients with persistent WRF, with differing associated clinical risks. 17,18,28,29 In the DOSE study, WRF (defined with respect to the degree of serum creatinine increase, as in our study) occurred over a 72-hour period during hospitalization in 23% of patients treated with higher dose diuretics and in 14% with lower doses (P = .04), but there was no significant difference in a 60-day composite outcome of death, readmission, or emergency department visits between the 2 groups. In our analysis of 90day postadmission mortality comparing transient WRF and no WRF (Figure 2, A), the hazards attenuated over time and were no longer statistically significant at about 30 days after admission, an earlier time point of decreased risk than that seen in the DOSE trial. These previous studies examined patients enrolled in clinical trials, whereas our study is the first to report similar outcomes associated with transient WRF in the real-world setting of a clinical registry. In our cohort of older patients with relatively higher rates of hypertension and preserved ejection fractions, patients with transient WRF had less mortality risk than those with persistent WRF. The mechanism of transient WRF may be related to improvement in congestion (the cardinal symptom during acute heart failure, manifested as dyspnea and edema). 30-32 It has been proposed that transient WRF may be an acceptable therapeutic compromise if accompanied by decongestion, which, in turn, has been associated with improved clinical outcomes. 33,34 Indeed, in our analysis, the adjusted mortality risk associated with transient WRF compared with no WRF attenuated quickly and again was no longer statistically significantly different by approximately 30 days after admission. There was a
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greater adjusted mortality risk with transient WRF during the index hospitalization and early after discharge, but much less as compared with persistent WRF. The small, early mortality risk associated with transient WRF and the potential relationship between transient WRF and decongestion deserve further consideration. Our findings suggest that the use and development of therapeutic strategies that lead to decongestion during acute heart failure without incurring WRF, particularly persistent WRF, should remain a preferred focus for atrisk populations. However, such modalities remain elusive, as evidenced by recent findings with dopamine and nesiritide as potential therapies for both decongestion and preventing WRF during acute heart failure. 35 Other novel vasodilators, such as serelaxin, may provide benefit in preventing WRF, particularly among patients with systolic blood pressure of ≥140 mm Hg on presentation. 36,37 Further study of the efficacy of novel therapies to prevent WRF in real-world populations is warranted. Our analysis has limitations. First, the study population was limited to patients 65 years or older who were enrolled in the registry from 2003 to 2006 and linked to Medicare claims data. The findings may not be generalizable to other patient populations, including younger patients and those in other periods. Second, the study was retrospective, subject to residual measured and unmeasured confounding, and definitive cause-and-effect relationships cannot be determined. Third, we were unable to investigate the relationship between changes in congestion and WRF because these data are not available in the registry. Fourth, WRF was ascertained between admission and discharge, whereas mortality was modeled starting from admission. Information bias may exist if hospitals were more likely to record WRF for patients who died inhospital or because of other differences in recording practices. However, there were an average of 5 creatinine measurements per patient, the mean by hospital was normally distributed, and we found no interaction between the number of creatinine measurements and adjusted estimates. Finally, if the last recorded serum creatinine value did not correspond to the discharge date, the patient may have been misclassified into the incorrect WRF group. Additional trends in renal function (either improvement or worsening) that were not documented may have occurred during the interval period between the last recorded serum creatinine level and discharge, potentially leading to erroneous classification of WRF status. In conclusion, in a large registry of patients with acute heart failure, WRF occurred often, particularly persistent WRF. Both transient and persistent WRF were associated with a higher adjusted risk for all-cause mortality compared with no WRF, with this outcome substantially
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worse in those with persistent WRF. There remains a need to identify therapies that prevent the development of WRF during acute heart failure.
Disclosures Drs Sharma and Johnson are employees of Novartis Pharmaceuticals Corporation. Dr Fonarow reported serving as a consultant to Bayer, Gambro, Medtronic, and Novartis. Dr Fonarow also holds the Eliot Corday Chair of Cardiovascular Medicine at UCLA and is supported by the Ahmanson Foundation, Los Angeles, CA. Dr Hernandez reported receiving research funding from Amgen and Novartis. No other disclosures were reported.
Acknowledgements Damon M. Seils, MA, Duke University, provided editorial assistance and prepared the manuscript. Mr Seils did not receive compensation for his assistance apart from his employment at the institution where the study was conducted.
References 1. Damman K, Valente MA, Voors AA, et al. Renal impairment, worsening renal function, and outcome in patients with heart failure: an updated meta-analysis. Eur Heart J 2014;35:455-69. 2. Krumholz HM, Chen YT, Vaccarino V, et al. Correlates and impact on outcomes of worsening renal function in patients N or =65 years of age with heart failure. Am J Cardiol 2000;85:1110-3. 3. Smith GL, Vaccarino V, Kosiborod M, et al. Worsening renal function: what is a clinically meaningful change in creatinine during hospitalization with heart failure? J Card Fail 2003;9:13-25. 4. Forman DE, Butler J, Wang Y, et al. Incidence, predictors at admission, and impact of worsening renal function among patients hospitalized with heart failure. J Am Coll Cardiol 2004;43:61-7. 5. Owan TE, Hodge DO, Herges RM, et al. Secular trends in renal dysfunction and outcomes in hospitalized heart failure patients. J Card Fail 2006;12:257-62. 6. Cowie MR, Komajda M, Murray-Thomas T, et al. Prevalence and impact of worsening renal function in patients hospitalized with decompensated heart failure: results of the Prospective Outcomes Study in Heart Failure (POSH). Eur Heart J 2006;27:1216-22. 7. Kociol RD, Greiner MA, Hammill BG, et al. Long-term outcomes of Medicare beneficiaries with worsening renal function during hospitalization for heart failure. Am J Cardiol 2010;105:1786-93. 8. Metra M, Nodari S, Parrinello G, et al. Worsening renal function in patients hospitalised for acute heart failure: clinical implications and prognostic significance. Eur J Heart Fail 2008;10:188-95. 9. Belziti CA, Bagnati R, Ledesma P, et al. Worsening renal function in patients admitted with acute decompensated heart failure: incidence, risk factors and prognostic implications. Rev Esp Cardiol 2010;63: 294-302. 10. Herout PM, Harshaw Q, Phatak H, et al. Impact of worsening renal function during hospital admission on resource utilization in patients with heart failure. Am J Cardiol 2010;106:1139-45. 11. Testani JM, McCauley BD, Chen J, et al. Worsening renal function defined as an absolute increase in serum creatinine is a biased metric for the study of cardio-renal interactions. Cardiology 2010;116:206-12.
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12. Verdiani V, Lastrucci V, Nozzoli C. Worsening renal function in patients hospitalized with acute heart failure: risk factors and prognostic significances. Int J Nephrol 2010;2011:785974. 13. Breidthardt T, Socrates T, Noveanu M, et al. Effect and clinical prediction of worsening renal function in acute decompensated heart failure. Am J Cardiol 2011;107:730-5. 14. Voors AA, Davison BA, Felker GM, et al. Early drop in systolic blood pressure and worsening renal function in acute heart failure: renal results of Pre-RELAX-AHF. Eur J Heart Fail 2011;13:961-7. 15. Lanfear DE, Peterson EL, Campbell J, et al. Relation of worsened renal function during hospitalization for heart failure to long-term outcomes and rehospitalization. Am J Cardiol 2011;107:74-8. 16. Patel UD, Greiner MA, Fonarow GC, et al. Associations between worsening renal function and 30-day outcomes among Medicare beneficiaries hospitalized with heart failure. Am Heart J 2010;160: 132-8. [e1]. 17. Felker GM, Lee KL, Bull DA, et al. Diuretic strategies in patients with acute decompensated heart failure. N Engl J Med 2011;364:797-805. 18. Aronson D, Burger AJ. The relationship between transient and persistent worsening renal function and mortality in patients with acute decompensated heart failure. J Card Fail 2010;16:541-7. 19. Centers for Medicare & Medicaid Services. BPCI Model 2: Retrospective Acute & Post Acute Care Episode. http://innovation.cms.gov/ initiatives/BPCI-Model-2/index.html. [Accessed March 25, 2014]. 20. Gheorghiade M, Vaduganathan M, Fonarow GC, et al. Rehospitalization for heart failure: problems and perspectives. J Am Coll Cardiol 2013;61:391-403. 21. Adams Jr KF, Fonarow GC, Emerman CL, et al. 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;149:209-16. 22. Hammill BG, Hernandez AF, Peterson ED, et al. Linking inpatient clinical registry data to Medicare claims data using indirect identifiers. Am Heart J 2009;157:995-1000. 23. Kociol RD, Hammill BG, Fonarow GC, et al. Generalizability and longitudinal outcomes of a national heart failure clinical registry: comparison of Acute Decompensated Heart Failure National Registry (ADHERE) and non-ADHERE Medicare beneficiaries. Am Heart J 2010;160:885-92. 24. Krumholz HM, Wang Y, Mattera JA, et al. An administrative claims model suitable for profiling hospital performance based on 30-day mortality rates among patients with heart failure. Circulation 2006;113:1693-701. 25. Harrell FE. Multivariable modeling strategies. Regression modeling strategies: with applications to linear models, logistic regression, and survival analysis. New York: Springer-Verlag. 200153-85. 26. Gray RJ. A class of K-sample tests for comparing the cumulative incidence of a competing risk. Ann Stat 1988;16:1141-54. 27. Fonarow GC, Abraham WT, Albert NM, et al. Factors identified as precipitating hospital admissions for heart failure and clinical outcomes: findings from OPTIMIZE-HF. Arch Intern Med 2008;168:847-54. 28. Blair JE, Pang PS, Schrier RW, et al. Changes in renal function during hospitalization and soon after discharge in patients admitted for worsening heart failure in the placebo group of the EVEREST trial. Eur Heart J 2011;32:2563-72. 29. Testani JM, Chen J, McCauley BD, et al. Potential effects of aggressive decongestion during the treatment of decompensated heart failure on renal function and survival. Circulation 2010;122:265-72. 30. Damman K, Navis G, Smilde TD, et al. Decreased cardiac output, venous congestion and the association with renal impairment in patients with cardiac dysfunction. Eur J Heart Fail 2007;9:872-8.
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31. Damman K, van Deursen VM, Navis G, et al. Increased central venous pressure is associated with impaired renal function and mortality in a broad spectrum of patients with cardiovascular disease. J Am Coll Cardiol 2009;53:582-8. 32. Mullens W, Abrahams Z, Francis GS, et al. Importance of venous congestion for worsening of renal function in advanced decompensated heart failure. J Am Coll Cardiol 2009;53:589-96. 33. Kociol RD, McNulty SE, Hernandez AF, et al. Markers of decongestion, dyspnea relief, and clinical outcomes among patients hospitalized with acute heart failure. Circ Heart Fail 2013;6:240-5. 34. Felker GM, Mentz RJ. Diuretics and ultrafiltration in acute decompensated heart failure. J Am Coll Cardiol 2012;59:2145-53.
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35. Chen HH, Anstrom KJ, Givertz MM, et al. Low-dose dopamine or low-dose nesiritide in acute heart failure with renal dysfunction: the ROSE acute heart failure randomized trial. JAMA 2013;310: 2533-43. 36. Chen HH, AbouEzzeddine OF, Anstrom KJ, et al. Targeting the kidney in acute heart failure: can old drugs provide new benefit? Renal Optimization Strategies Evaluation in Acute Heart Failure (ROSE AHF) trial. Circ Heart Fail 2013;6:1087-94. 37. Metra M, Cotter G, Davison BA, et al. Effect of serelaxin on cardiac, renal, and hepatic biomarkers in the Relaxin in Acute Heart Failure (RELAX-AHF) development program: correlation with outcomes. J Am Coll Cardiol 2013;61:196-206.
Transient and persistent worsening renal function during hospitalization for acute heart failure Arun Krishnamoorthy, MD, a,b Melissa A. Greiner, MS, a Puza P. Sharma, MBBS, MPH, PhD, c Adam D. DeVore, MD, a,b Katherine Waltman Johnson, PharmD, c Gregg C. Fonarow, MD, d Lesley H. Curtis, PhD, a,b and Adrian F. Hernandez, MD, MHS a,b Durham, NC; East Hanover, NJ; and Los Angeles, CA
Background Transient and persistent worsening renal function (WRF) may be associated with different risks during hospitalization for acute heart failure. We compared outcomes of patients hospitalized for acute heart failure with transient, persistent, or no WRF. Methods
We identified patients 65 years or older hospitalized with acute heart failure from a clinical registry linked to Medicare claims data. We defined WRF as an increase in serum creatinine of ≥0.3 mg/dL after admission. We further classified patients with WRF by the difference between admission and last recorded serum creatinine levels into transient WRF (b0.3 mg/dL) or persistent WRF (≥0.3 mg/dL). We examined unadjusted rates and adjusted associations between 90-day outcomes and WRF status.
Results Among 27,309 patients, 18,568 (68.0%) had no WRF, 3,205 (11.7%) had transient WRF, and 5,536 (20.3%) had persistent WRF. Patients with WRF had higher observed rates of 90-day postdischarge all-cause readmission and 90-day postadmission mortality (P b .001). After multivariable adjustment, transient WRF (hazard ratio [HR] 1.19, 99% CI 1.05-1.35) and persistent WRF (HR 1.73, 99% CI 1.57-1.91) were associated with higher risks of 90-day postadmission mortality (P b .001 for both). Compared with transient WRF, persistent WRF was associated with a higher risk of 90-day postadmission mortality (HR 1.46, 99% CI 1.28-1.66, P b .001). Conclusions Transient and persistent WRF during hospitalization for acute heart failure were associated with higher adjusted risks for 90-day all-cause postadmission mortality. Patients with persistent WRF had worse outcomes. (Am Heart J 2014;168:891-900.) Worsening renal function (WRF), commonly defined as an increase in serum creatinine level of ≥0.3 mg/dL, occurs in approximately 20% to 45% of patients hospitalized for acute heart failure. 1-15 Development of WRF is associated with an increased risk of adverse inpatient, 30-day, and long-term postdischarge outcomes, including mortality. 1,7,16 Thus, WRF represents a significant event during acute heart failure, and the prevention and treatment of WRF remain important targets. Recent clinical trial evidence suggests that the risks associated with WRF may differ depending on whether From the aDuke Clinical Research Institute, Duke University School of Medicine, Durham, NC, bDepartment of Medicine, Duke University School of Medicine, Durham, NC, c Novartis Pharmaceuticals Corporation, East Hanover, NJ, and dAhmanson-UCLA Cardiomyopathy Center, University of California, Los Angeles, CA. Hector O. Ventura, MD, served as guest editor for this article. Funding/support. This study was supported by a research agreement between Duke University and Novartis Pharmaceuticals Corporation. Submitted July 22, 2014; accepted August 17, 2014. Reprint requests: Adrian F. Hernandez, MD, MHS, Duke Clinical Research Institute, PO Box 17969, Durham, NC 27715. E-mail: [email protected] 0002-8703 © 2014 Elsevier Inc. All rights reserved http://dx.doi.org/10.1016/j.ahj.2014.08.016
WRF is transient or persistent. In the DOSE study, WRF occurred more often over 72 hours during hospitalization for acute heart failure in patients treated with higher doses of diuretics as compared with those randomized to a lowdose diuretic strategy. However, there was no significant difference in 60-day clinical outcomes between the 2 groups. 17 Moreover, in an analysis of patients enrolled in the VMAC trial over a 30-day period extending postdischarge, persistent WRF was associated with a higher risk of 6-month mortality as compared with transient WRF. 18 To further understand differences among patients with WRF during hospitalization for acute heart failure, we examined a cohort of patients from the Acute Decompensated Heart Failure National Registry (ADHERE) linked with Medicare claims. The objectives of our analysis were to describe the prevalence and characteristics of patients with inhospital transient and persistent WRF and to compare 90-day outcomes between patients with no WRF, transient WRF, or persistent WRF. We used an intermediate follow-up period of 90 days for observation of outcomes because new payment models being evaluated by the Centers for Medicare & Medicaid Services may extend up to 90 days after hospital
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Table I. Baseline characteristics of the study population Characteristic Age, mean (SD), y Male, n (%) Race, n (%) Black White Other/unknown Medical history, n (%) Anemia Atrial fibrillation Chronic renal insufficiency COPD Coronary artery disease Diabetes mellitus Dyslipidemia Heart failure hospitalization in the past 6 m Hypertension Myocardial infarction Peripheral vascular disease Smoking status Never smoked Former smoker Current smoker Missing Stroke or TIA Medical devices, n (%) CRT-P ICD or CRT-D Pacemaker alone Initial evaluation, n (%) Dyspnea Ejection fraction b40% ≥40% Missing Fatigue Pulmonary edema Rales Initial vital signs Pulse, mean (SD), beat/min Systolic blood pressure, mean (SD), mm Hg b140 mm Hg, n (%) ≥140 mm Hg, n (%) Initial laboratory test results Hemoglobin level, mean (SD), g/dL BNP, mean (SD), pg/mL⁎ Missing, n (%) Chronic kidney disease stage, n (%) Stage 1 Stage 2 Stage 3 Stage 4 Stage 5 eGFR, mean (SD), mL/min/1.73 m 2 Serum creatinine, mean (SD), mg/dL Serum sodium, mean (SD), mEq/L Discharge or last known laboratory test result eGFR, mean (SD), mL/min/1.73 m 2 Chronic kidney disease stage, n (%) Stage 1 Stage 2 Stage 3 Stage 4
No WRF (n = 18,568)
Transient WRF (n = 3205)
Persistent WRF (n = 5536)
P
79.9 (7.8) 8054 (43.4)
79.4 (7.5) 1449 (45.2)
80.1 (7.8) 2356 (42.6)
b.001 .05 b.001
1989 (10.7) 15,848 (85.4) 731 (3.9)
342 (10.7) 2688 (83.9) 175 (5.5)
671 (12.1) 4570 (82.6) 295 (5.3)
10,425 (56.1) 6923 (37.3) 4303 (23.2) 5512 (29.7) 11,013 (59.3) 7260 (39.1) 7235 (39.0) 2325 (12.5) 14,035 (75.6) 5300 (28.5) 3330 (17.9)
1847 1086 1064 1075 1971 1405 1270 360 2472 915 630
(57.6) (33.9) (33.2) (33.5) (61.5) (43.8) (39.6) (11.2) (77.1) (28.5) (19.7)
3380 1773 2004 1630 3346 2423 2216 634 4366 1631 1099
(61.1) (32.0) (36.2) (29.4) (60.4) (43.8) (40.0) (11.5) (78.9) (29.5) (19.9)
1426 1238 243 298 645
(44.5) (38.6) (7.6) (9.3) (20.1)
2669 2011 388 468 1041
(48.2) (36.3) (7.0) (8.5) (18.8)
.02
8997 6660 1400 1511 3370
(48.5) (35.9) (7.5) (8.1) (18.1)
b.001 b.001 b.001 b.001 .04 b.001 .33 .02 b.001 .40 .001 .002
332 (1.8) 1203 (6.5) 2554 (13.8)
48 (1.5) 193 (6.0) 418 (13.0)
85 (1.5) 305 (5.5) 720 (13.0)
.28 .03 .25
16,534 (89.0)
2902 (90.5)
4974 (89.8)
.02 b.001
6800 9163 2605 5705 15,971 12,339
(36.6) (49.3) (14.0) (30.7) (86.0) (66.5)
1176 1707 322 1008 2862 2182
(36.7) (53.3) (10.0) (31.5) (89.3) (68.1)
1947 2863 726 1612 4900 3805
(35.2) (51.7) (13.1) (29.1) (88.5) (68.7)
.03 b.001 .003
86.1 143.1 9047 9521
(21.6) (30.7) (48.7) (51.3)
87.4 145.8 1425 1780
(21.5) (31.5) (44.5) (55.5)
86.8 150.1 2164 3372
(20.8) (31.4) (39.1) (60.9)
b.001 b.001 b.001 b.001
12.0 (2.0) 1186.3 (1,122.4) 4715 (25.4)
12.0 (2.0) 1278.4 (1,183.2) 716 (22.3)
11.9 (1.9) 1287.2 (1,149.7) 1196 (21.6)
1022 (5.5) 5155 (27.8) 9245 (49.8) 2525 (13.6) 621 (3.3) 51.8 (24.0) 1.6 (1.1) 138.0 (4.7)
129 (4.0) 660 (20.6) 1698 (53.0) 500 (15.6) 218 (6.8) 46.7 (23.3) 1.8 (1.3) 137.9 (4.7)
275 (5.0) 1170 (21.1) 2785 (50.3) 978 (17.7) 328 (5.9) 47.8 (25.2) 1.7 (1.2) 138.5 (4.5)
54.5 (23.6)
45.6 (21.3)
31.2 (14.4)
1090 5680 9535 1855
84 587 1867 491
– 164 (3.0) 2719 (49.1) 1914 (34.6)
(5.9) (30.6) (51.4) (10.0)
(2.6) (18.3) (58.3) (15.3)
b.001 b.001 b.001 b.001
b.001 b.001 b.001 b.001 b.001
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Table I (continued) Characteristic Stage 5 Serum creatinine, mean (SD), mg/dL Admission medications, n (%) ACE inhibitor or ARB Aldosterone antagonist⁎ Aspirin β-Blocker Clopidogrel Lipid-lowering agent Loop diuretic Warfarin Discharge medications, n (%) ACE inhibitor or ARB Aldosterone antagonist⁎ Aspirin β-Blocker Clopidogrel Lipid-lowering agent Loop diuretic Warfarin Year of index hospitalization, n (%) 2003 2004 2005 2006
No WRF (n = 18,568)
Transient WRF (n = 3205)
Persistent WRF (n = 5536)
P
408 (2.2) 1.4 (0.8)
176 (5.5) 1.7 (1.1)
735 (13.3) 2.4 (1.6)
b.001
9335 1491 7893 10,405 2457 7051 11,633 5032
(50.3) (8.3) (42.5) (56.0) (13.2) (38.0) (62.7) (27.1)
1579 237 1390 1791 476 1231 1926 779
(49.3) (7.6) (43.4) (55.9) (14.9) (38.4) (60.1) (24.3)
2669 395 2374 3047 842 2102 3212 1227
(48.2) (7.3) (42.9) (55.0) (15.2) (38.0) (58.0) (22.2)
.02 .06 .63 .42 b.001 .89 b.001 b.001
11,433 2882 8972 11,880 2744 7093 14,911 5303
(61.6) (15.5) (48.3) (64.0) (14.8) (38.2) (80.3) (28.6)
1722 429 1583 2099 562 1261 2271 843
(53.7) (13.4) (49.4) (65.5) (17.5) (39.3) (70.9) (26.3)
2880 (52.0) 754 (13.6) 2545 (46.0) 3320 (60.0) 831 (15.0) 2048 (37.0) 3837 (69.3) 1240 (22.4)
b.001 b.001 .002 b.001 b.001 .08 b.001 b.001 .79
2372 10,863 4915 418
(12.8) (58.5) (26.5) (2.3)
404 1851 875 75
(12.6) (57.8) (27.3) (2.3)
744 3213 1451 128
(13.4) (58.0) (26.2) (2.3)
Abbreviations: COPD, Chronic obstructive pulmonary disease; TIA, transient ischemic attack; CRT-P, cardiac resynchronization therapy with pacemaker; ICD, implantable cardioverter-defibrillator; CRT-D, cardiac resynchronization therapy with defibrillator; ACE, angiotensin-converting enzyme; ARB, angiotensin II receptor blocker. ⁎ The BNP level and aldosterone antagonist variables were not included in the multivariable models because they had high rates of missingness.
discharge and because of the potential competing risk for mortality associated with shorter term readmission. 19,20
Methods Data sources ADHERE was established to improve understanding of the clinical characteristics, management, and outcomes of patients hospitalized with acute decompensated heart failure. 21 More than 300 community and academic medical centers in the United States participated and N185,000 patients were enrolled from January 2001 to March 2006. To analyze long-term follow-up data, we obtained Medicare standard analytic claim files from the Centers for Medicare & Medicaid Services. These files contain encrypted identifiers that allow for longitudinal follow-up of fee-forservice Medicare beneficiaries. We used indirect identifiers to link registry records to Medicare files using methods that have been described previously. 22 Almost 80% of the registry records have been linked with Medicare claims, and older patients enrolled in the registry constitute a nationally representative sample of fee-for-service Medicare beneficiaries. 22,23 Study population We included patients 65 years or older living in the United States who had a registry hospitalization linked to
Medicare claims between January 1, 2003, and March 31, 2006, the period during which serum creatinine level was recorded. If multiple registry hospitalizations were identified for a single patient, we used the earliest as the index hospitalization. We restricted the population to patients enrolled in fee-for-service Medicare at the time of the index hospitalization and for at least 6 months before the hospitalization. To identify WRF, we required that admission serum creatinine level and at least 2 subsequent creatinine values were recorded in the registry. We excluded patients who were admitted electively for the index hospitalization. For the analysis of outcomes at discharge or in the 90 days after discharge, we excluded patients who died in the hospital, left against medical advice, or were discharged or transferred to another short-term hospital or hospice. In addition, patients who enrolled in Medicare managed care during the follow-up period were excluded from the measurement of days alive and out of the hospital and Medicare payments.
Worsening renal function We defined WRF as any increase in serum creatinine level of ≥0.3 mg/dL during the index hospitalization over the admission value recorded in the registry. We further classified patients with WRF by the difference between the last recorded serum creatinine level and the admission
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Table II. Observed outcomes by study group Outcome All patients No. of patients Length of stay, mean (SD), d ICU or CCU stay, n (%) Length of stay among patients with ICU/CCU stay, mean (SD), d Length of stay among all patients, mean (SD), d Inhospital mortality, n (%) Inhospital Medicare facility payments, $⁎ Mean (SD) Median (interquartile range) Mortality at 90 d after admission, n (%) † Patients discharged alive No. of patients Clinical status at discharge, n (%) Asymptomatic Symptomatic but improved Other/unknown All-cause readmission at 90 d after discharge, n (%) † Heart failure readmission at 90 d after discharge, n (%) † Patients discharged alive and not censored at 90 d No. of patients Days alive and out of the hospital at 90 d after discharge, mean (SD) Medicare payments at 90 d after discharge, $⁎ Mean (SD) Median (interquartile range)
No WRF
Transient WRF
Persistent WRF
P
18,568 5.3 (4.6) 2455 (13.2) 3.4 (4.2) 0.4 (1.9) 453 (2.4)
3205 7.8 (5.0) 662 (20.7) 4.5 (4.2) 0.9 (2.6) 102 (3.2)
5536 6.4 (5.2) 874 (15.8) 4.1 (4.7) 0.7 (2.4) 512 (9.2)
b.001 b.001 b.001 b.001 b.001
9165 (11,275) 6657 (5583-8571) 3002 (16.2)
10,700 (12,177) 7042 (5835-9859) 598 (18.7)
9401 (10,892) 6696 (5591-8820) 1297 (23.5)
b.001 b.001 b.001
17,256
2920
4720
(46.9) (40.8) (12.3) (40.3) (16.8)
1284 (44.0) 1262 (43.2) 374 (12.8) 1272 (43.6) 512 (17.6)
2151 (45.6) 1979 (41.9) 590 (12.5) 1984 (42.1) 756 (16.1)
.04 .008 .04 .69 b.001 .17
17,163 79.3 (21.3)
2904 77.3 (23.1)
4690 78.4 (22.3)
b.001
10,608 (19,447) 2539 (610-12,748)
12,534 (21,409) 4739 (761-15,835)
11,594 (20,370) 3521 (658-15,051)
b.001 b.001
8091 7048 2117 6938 2896
⁎ Expressed in 2010 US dollars. † Expressed as number of patients (cumulative incidence per 100 patients at risk).
creatinine value into either transient (b0.3 mg/dL) or persistent (≥0.3 mg/dL) inhospital WRF. The last recorded serum creatinine value did not necessarily correspond to the discharge date. We classified patients into 3 groups: no WRF, transient WRF, or persistent WRF.
Outcomes The main outcomes of interest were mortality, all-cause readmission, heart failure readmission, and days alive and out of the hospital. We measured mortality within 90 days after admission, and we measured all-cause readmission, heart failure readmission, and days alive and out of the hospital within 90 days after discharge. We also analyzed index hospitalization length of stay, intensive care unit (ICU) or cardiac care unit (CCU) length of stay, index hospitalization mortality, clinical status at discharge, and Medicare payments at 90 days after discharge. We determined mortality during the index hospitalization based on discharge status on the Medicare inpatient claims, and we measured 90-day postadmission mortality based on death dates in the Medicare denominator files. We calculated index hospitalization length of stay using the Medicare index hospitalization claim. Intensive care unit and CCU length of stay and clinical status at discharge (categorized as asymptomatic, symptomatic but improved, or other/unknown) were based on the
registry data. We calculated total days alive and out of the hospital in the 90 days after discharge based on death dates in the Medicare denominator files and hospitalization dates in the Medicare inpatient files. We identified allcause readmission using subsequent inpatient claims except those for transfers to or from another hospital and admissions for rehabilitation (diagnosis-related group 462 or International Classification of Diseases, Ninth Revision, Clinical Modification, diagnosis code V57.xx). We identified readmission for heart failure based on a primary diagnosis of heart failure (International Classification of Diseases, Ninth Revision, Clinical Modification, diagnosis codes 428.x, 402.x1, 404.x1, or 404.x3) on the inpatient claim. We calculated total Medicare payments in the 90 days after discharge by summing payments for inpatient, outpatient, and carrier claims. We report payments in 2010 US dollars with inflation adjustment using the medical care component of the Consumer Price Index.
Covariates Variables from the registry included demographic characteristics, medical history, initial evaluation results, initial vital signs, laboratory test results, and admission and discharge medications. For variables with low rates of missingness (ie, b5% of records), we imputed missing
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continuous variables to the overall median value, dichotomous variables to “no,” and multichotomous variables to the most frequent categorical value. 24,25 For variables with N5% missingness (including smoking status, B-type natriuretic peptide [BNP] level, and ejection fraction), we treated missing values as a separate category.
Figure 1
Cumulative Incidence, %
A
30%
No worsening renal function Transient worsening renal function Persistent worsening renal function
20%
10%
0% 0
10
20
30
40
50
60
70
80
90
Days from Index Hospitalization Admission
Cumulative Incidence, %
B
50%
No worsening renal function Transient worsening renal function Persistent worsening renal function
40%
30%
20%
10%
0% 0
10
20
30
40
50
60
70
80
90
Days from Index Hospitalization Discharge
Cumulative Incidence, %
C
30%
No worsening renal function Transient worsening renal function Persistent worsening renal function
20%
10%
0% 0
10
20
30
40
50
60
70
80
90
Days from Index Hospitalization Discharge Cumulative incidence of mortality in the 90 days after admission (A), all-cause readmission in the 90 days after discharge (B), and heart failure readmission in the 90 days after discharge (C).
Statistical analysis We present baseline characteristics of the study population stratified by WRF status (no WRF, transient WRF, and persistent WRF). We present categorical variables as frequencies with percentages and continuous variables as means with SDs. We tested for differences in baseline variables between groups using χ 2 tests for categorical variables and Kruskal-Wallis tests for continuous variables. We described observed outcomes by study group. For inhospital mortality and clinical status at discharge, we calculated frequencies with percentages and tested for differences between groups using χ 2 tests. For hospital length of stay, ICU length of stay, days alive and out of the hospital, and Medicare payments, we calculated means with SDs and compared the mean difference between groups using Kruskal-Wallis tests. For 90-day mortality, we calculated the cumulative incidence of mortality using Kaplan-Meier estimates and tested for differences between the groups using log-rank tests. For 90-day all-cause and heart failure readmission, we calculated incidence using estimates from the cumulative incidence function to account for the competing risk of mortality and tested for group differences using Gray tests. 26 We examined the unadjusted and adjusted associations between WRF classification and 90-day outcomes. For 90-day mortality and readmission, we used Cox proportional hazards models with robust standard errors to account for clustering of patients within hospitals. We used a linear mixed model for days alive and out of the hospital and a generalized linear mixed model with a log link and Poisson distribution for Medicare payments. In all the mixed models, we accounted for clustering of patients within hospitals by estimating hospital-level random intercepts. In the unadjusted models, WRF category was the only predictor. In the adjusted models, we included other baseline characteristics (ie, demographic characteristics, medical history, laboratory/test results, and medications). For mortality and readmission survival analyses, we censored data for patients if they enrolled in Medicare-managed care. For readmission outcomes, we censored data for patients at the time of death. Because of multiple comparisons, we used a 2-tailed P = .01 to establish statistical significance, and we report 99% CIs. We used SAS version 9.3 (SAS Institute, Inc, Cary, NC) for all analyses. The Institutional Review Board of the Duke University Health System approved the study.
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Table III. Unadjusted and adjusted associations between study groups and outcomes Association Outcome Mortality at 90 d after admission⁎ Transient vs no WRF Persistent vs no WRF Persistent vs transient WRF All-cause readmission at 90 d after discharge † Transient vs no WRF Persistent vs no WRF Persistent vs transient WRF HF readmission at 90 days after discharge † Transient vs no WRF Persistent vs no WRF Persistent vs transient WRF
Days alive and out of the hospital at 90 d after discharge ‡ Transient vs no WRF Persistent vs no WRF Persistent vs transient WRF
Medicare payments at 90 d after discharge ‡ Transient vs no WRF Persistent vs no WRF Persistent vs transient WRF
Unadjusted HR (99% CI)
P
Adjusted HR (99% CI)
P
1.17 (1.03-1.33) 1.56 (1.42-1.72) 1.33 (1.17-1.52)
.002 b.001 b.001
1.19 (1.05-1.35) 1.73 (1.57-1.91) 1.46 (1.28-1.66)
b.001 b.001 b.001
1.13 (1.03-1.23) 1.07 (0.99-1.14) 0.95 (0.86-1.04)
b.001 .02 .14
1.06 (0.97-1.17) 1.05 (0.98-1.12) 0.98 (0.89-1.08)
.08 .08 .63
1.06 (0.94-1.20) 0.95 (0.86-1.06) 0.90 (0.79-1.02)
.18 .25 .03
1.02 (0.91-1.15) 0.94 (0.85-1.04) 0.92 (0.81-1.05)
.60 .14 .10
Estimate (99% CI)
P
Estimate (99% CI)
P
−1.99 (−3.12 to −0.87) −0.91 (−1.84 to 0.01) 1.08 (−0.24 to 2.40)
b.001 .01 .03
−1.45 (−2.54 to −0.36) −1.17 (−2.08 to −0.26) 0.28 (−1.00 to 1.56)
b.001 b.001 .57
Cost ratio (99% CI)
P
Cost ratio (99% CI)
P
1.18 (1.09-1.28) 1.11 (1.03-1.19) 0.94 (0.85-1.04)
b.001 b.001 .11
1.09 (1.01-1.18) 1.07 (0.99-1.14) 0.98 (0.89-1.07)
.005 .02 .51
Abbreviation: WRF, Worsening renal function. In addition to the WRF variable, covariates in the multivariable regression models included age, sex, race, anemia, atrial fibrillation, coronary artery disease, chronic renal insufficiency, chronic obstructive pulmonary disease, diabetes mellitus, heart failure hospitalization in the past 6 months, dyslipidemia, hypertension, myocardial infarction, peripheral vascular disease, stroke or transient ischemic attack, smoking status, medical device type, fatigue, rales, pulmonary edema, dyspnea, ejection fraction, pulse, systolic blood pressure, serum sodium, hemoglobin level, serum creatinine, angiotensin-converting enzyme inhibitor or angiotensin II receptor blocker, aspirin, β-blocker, loop diuretic, clopidogrel, lipid-lowering medication, warfarin, and year of index hospitalization. The mortality model included medication information at admission; other models included medication information at discharge. ⁎ Among all patients. † Among patients discharged alive. ‡ Among patients discharged alive and not censored at 90 days after discharge.
Results Among 27,309 patients, 18,568 (68.0%) had no WRF, 3,205 (11.7%) had transient WRF, and 5,536 (20.3%) had persistent WRF (Table I). The average age in each group was approximately 80 years, and most patients were white women. The direction of observed trends was similar for transient and persistent WRF. Patients with WRF were more likely to have a left ventricular ejection fraction of ≥40%, with higher rates in patients with transient WRF. The highest rates of hypertension were in patients with persistent WRF, and there was an equally high rate of diabetes mellitus between the WRF groups. Rates of loop diuretic use both on admission and at discharge were lower in patients with WRF, with slightly lower rates for each in those with persistent WRF. More patients with transient WRF were likely to have pulmonary edema and dyspnea on initial presentation. A history of chronic renal insufficiency at baseline was most common in persistent WRF; the estimated glomerular
filtration rate (eGFR) on admission was also more likely to be lower (and, consequently, the baseline serum creatinine level higher) in those with persistent WRF. Most patients in each group had stage 3 chronic kidney disease at baseline (ie, eGFR of 30-59 mL/min per 1.73 m 2). Table II shows the observed outcomes in each group. Compared with no WRF, patients with either transient or persistent WRF had higher observed rates of 90-day postadmission mortality, with the highest rate among patients with persistent WRF (16.2% vs 18.7% vs 23.5%, P b .001) (Figure 1, A). In addition, both the transient and persistent WRF groups had higher rates of 90-day postdischarge all-cause readmission (Figure 1, B) and fewer days alive and out of the hospital at 90 days. There was no significant difference in observed rates of 90-day postdischarge heart failure readmission between groups (Figure 1, C). Patients with either transient or persistent WRF, compared with no WRF, also had a longer hospital length of stay, higher inhospital mortality, higher
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Figure 2
A
B
C
Hazards of mortality in the 90 days after admission among patients with transient vs no worsening renal function (A), persistent vs no worsening renal function (B), and persistent vs transient worsening renal function (C). Note: The solid lines represent HRs, and the dashed lines, 99% CIs.
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Medicare payments at 90 days after discharge, higher rate of ICU and CCU stays, and longer ICU and CCU length of stay. The mean lengths of stay among patients with no WRF, transient WRF, and persistent WRF were 5.3, 7.8, and 6.4 days, respectively (P b .001). Patients with transient or persistent WRF were more likely to have remained symptomatic but improved at discharge, whereas patients with no WRF were more likely to have been asymptomatic at discharge (ie, clinical status at discharge was noted in the registry as asymptomatic, symptomatic but improved, or other/unknown). Table III shows the unadjusted and adjusted associations between the WRF groups and outcomes. In adjusted analyses, both transient and persistent WRF were associated with a higher risk of 90-day postadmission mortality (hazard ratio [HR] 1.19, 99% CI 1.05-1.35, P b .001 for transient WRF, and HR 1.73, 99% CI 1.57-1.91, P b .001 for persistent WRF) and fewer days alive and out of the hospital at 90 days after discharge (−1.45 days, 99% CI −2.54 to −0.36, P b .001, and −1.17 days, 99% CI −2.08 to −0.26, P b .001) compared with no WRF. After multivariable adjustment, only transient WRF was associated with higher Medicare payments at 90 days after discharge compared with no WRF (P b .005). There were no significant differences between either WRF group compared with no WRF in the risk of 90-day all-cause or heart failure readmission. In the adjusted mortality model, the proportional hazards assumption was not met for the WRF study variable (P b .001). In the comparison between transient WRF and no WRF, the HR attenuated over time and was no longer statistically significant at approximately 30 days after admission (Figure 2, A). The risk associated with persistent WRF, compared with no WRF, also attenuated but remained significantly higher 90 days after admission (Figure 2, B). After multivariable adjustment, persistent WRF was associated with a 46% higher risk of 90-day postadmission mortality (HR 1.46, 99% CI 1.28-1.66, P b .001) compared with transient WRF. However, the HR attenuated over time and was no longer statistically significant at approximately 70 days after admission (Figure 2, C). There was no significant difference at 90 days after discharge in either all-cause or heart failure readmission, days alive and out of the hospital, or Medicare payments in the comparison between persistent and transient WRF.
Discussion In a large cohort of patients hospitalized for acute heart failure, N30% of patients experienced WRF, with transient WRF occurring frequently in more than one-third of the patients with WRF. Patients with transient WRF were similar to patients with persistent WRF, particularly with regard to high rates of relatively preserved ejection fraction, chronic kidney disease (predominantly stage 3 or greater), and signs or symptoms of congestive heart failure at baseline. Furthermore, we observed that any
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WRF, whether transient or persistent, was associated with a higher adjusted risk of postadmission mortality and fewer days alive and out of the hospital at 90 days. However, the hazards of mortality in the comparison of transient WRF and no WRF attenuated over time and were no longer statistically significant at approximately 30 days after admission. In addition, persistent WRF was associated with a significantly higher 90-day mortality risk, compared with transient WRF. Finally, patients with transient but not persistent WRF had higher Medicare payments compared with no WRF. There were no significant differences between transient and persistent WRF for all-cause or heart failure readmission, days alive and out of the hospital, and Medicare payments in the 90 days after discharge. Worsening renal function during acute heart failure has been observed to be associated with worse mortality in many studies, including prior registries. 1,27 Most of these studies defined WRF as a singular event and did not examine trends of renal function over the course of an episode of acute heart failure. However, several recent clinical trial analyses have suggested that patients with recovery of renal function after WRF during acute heart failure may represent a unique cohort distinct from patients with persistent WRF, with differing associated clinical risks. 17,18,28,29 In the DOSE study, WRF (defined with respect to the degree of serum creatinine increase, as in our study) occurred over a 72-hour period during hospitalization in 23% of patients treated with higher dose diuretics and in 14% with lower doses (P = .04), but there was no significant difference in a 60-day composite outcome of death, readmission, or emergency department visits between the 2 groups. In our analysis of 90day postadmission mortality comparing transient WRF and no WRF (Figure 2, A), the hazards attenuated over time and were no longer statistically significant at about 30 days after admission, an earlier time point of decreased risk than that seen in the DOSE trial. These previous studies examined patients enrolled in clinical trials, whereas our study is the first to report similar outcomes associated with transient WRF in the real-world setting of a clinical registry. In our cohort of older patients with relatively higher rates of hypertension and preserved ejection fractions, patients with transient WRF had less mortality risk than those with persistent WRF. The mechanism of transient WRF may be related to improvement in congestion (the cardinal symptom during acute heart failure, manifested as dyspnea and edema). 30-32 It has been proposed that transient WRF may be an acceptable therapeutic compromise if accompanied by decongestion, which, in turn, has been associated with improved clinical outcomes. 33,34 Indeed, in our analysis, the adjusted mortality risk associated with transient WRF compared with no WRF attenuated quickly and again was no longer statistically significantly different by approximately 30 days after admission. There was a
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greater adjusted mortality risk with transient WRF during the index hospitalization and early after discharge, but much less as compared with persistent WRF. The small, early mortality risk associated with transient WRF and the potential relationship between transient WRF and decongestion deserve further consideration. Our findings suggest that the use and development of therapeutic strategies that lead to decongestion during acute heart failure without incurring WRF, particularly persistent WRF, should remain a preferred focus for atrisk populations. However, such modalities remain elusive, as evidenced by recent findings with dopamine and nesiritide as potential therapies for both decongestion and preventing WRF during acute heart failure. 35 Other novel vasodilators, such as serelaxin, may provide benefit in preventing WRF, particularly among patients with systolic blood pressure of ≥140 mm Hg on presentation. 36,37 Further study of the efficacy of novel therapies to prevent WRF in real-world populations is warranted. Our analysis has limitations. First, the study population was limited to patients 65 years or older who were enrolled in the registry from 2003 to 2006 and linked to Medicare claims data. The findings may not be generalizable to other patient populations, including younger patients and those in other periods. Second, the study was retrospective, subject to residual measured and unmeasured confounding, and definitive cause-and-effect relationships cannot be determined. Third, we were unable to investigate the relationship between changes in congestion and WRF because these data are not available in the registry. Fourth, WRF was ascertained between admission and discharge, whereas mortality was modeled starting from admission. Information bias may exist if hospitals were more likely to record WRF for patients who died inhospital or because of other differences in recording practices. However, there were an average of 5 creatinine measurements per patient, the mean by hospital was normally distributed, and we found no interaction between the number of creatinine measurements and adjusted estimates. Finally, if the last recorded serum creatinine value did not correspond to the discharge date, the patient may have been misclassified into the incorrect WRF group. Additional trends in renal function (either improvement or worsening) that were not documented may have occurred during the interval period between the last recorded serum creatinine level and discharge, potentially leading to erroneous classification of WRF status. In conclusion, in a large registry of patients with acute heart failure, WRF occurred often, particularly persistent WRF. Both transient and persistent WRF were associated with a higher adjusted risk for all-cause mortality compared with no WRF, with this outcome substantially
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worse in those with persistent WRF. There remains a need to identify therapies that prevent the development of WRF during acute heart failure.
Disclosures Drs Sharma and Johnson are employees of Novartis Pharmaceuticals Corporation. Dr Fonarow reported serving as a consultant to Bayer, Gambro, Medtronic, and Novartis. Dr Fonarow also holds the Eliot Corday Chair of Cardiovascular Medicine at UCLA and is supported by the Ahmanson Foundation, Los Angeles, CA. Dr Hernandez reported receiving research funding from Amgen and Novartis. No other disclosures were reported.
Acknowledgements Damon M. Seils, MA, Duke University, provided editorial assistance and prepared the manuscript. Mr Seils did not receive compensation for his assistance apart from his employment at the institution where the study was conducted.
References 1. Damman K, Valente MA, Voors AA, et al. Renal impairment, worsening renal function, and outcome in patients with heart failure: an updated meta-analysis. Eur Heart J 2014;35:455-69. 2. Krumholz HM, Chen YT, Vaccarino V, et al. Correlates and impact on outcomes of worsening renal function in patients N or =65 years of age with heart failure. Am J Cardiol 2000;85:1110-3. 3. Smith GL, Vaccarino V, Kosiborod M, et al. Worsening renal function: what is a clinically meaningful change in creatinine during hospitalization with heart failure? J Card Fail 2003;9:13-25. 4. Forman DE, Butler J, Wang Y, et al. Incidence, predictors at admission, and impact of worsening renal function among patients hospitalized with heart failure. J Am Coll Cardiol 2004;43:61-7. 5. Owan TE, Hodge DO, Herges RM, et al. Secular trends in renal dysfunction and outcomes in hospitalized heart failure patients. J Card Fail 2006;12:257-62. 6. Cowie MR, Komajda M, Murray-Thomas T, et al. Prevalence and impact of worsening renal function in patients hospitalized with decompensated heart failure: results of the Prospective Outcomes Study in Heart Failure (POSH). Eur Heart J 2006;27:1216-22. 7. Kociol RD, Greiner MA, Hammill BG, et al. Long-term outcomes of Medicare beneficiaries with worsening renal function during hospitalization for heart failure. Am J Cardiol 2010;105:1786-93. 8. Metra M, Nodari S, Parrinello G, et al. Worsening renal function in patients hospitalised for acute heart failure: clinical implications and prognostic significance. Eur J Heart Fail 2008;10:188-95. 9. Belziti CA, Bagnati R, Ledesma P, et al. Worsening renal function in patients admitted with acute decompensated heart failure: incidence, risk factors and prognostic implications. Rev Esp Cardiol 2010;63: 294-302. 10. Herout PM, Harshaw Q, Phatak H, et al. Impact of worsening renal function during hospital admission on resource utilization in patients with heart failure. Am J Cardiol 2010;106:1139-45. 11. Testani JM, McCauley BD, Chen J, et al. Worsening renal function defined as an absolute increase in serum creatinine is a biased metric for the study of cardio-renal interactions. Cardiology 2010;116:206-12.
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12. Verdiani V, Lastrucci V, Nozzoli C. Worsening renal function in patients hospitalized with acute heart failure: risk factors and prognostic significances. Int J Nephrol 2010;2011:785974. 13. Breidthardt T, Socrates T, Noveanu M, et al. Effect and clinical prediction of worsening renal function in acute decompensated heart failure. Am J Cardiol 2011;107:730-5. 14. Voors AA, Davison BA, Felker GM, et al. Early drop in systolic blood pressure and worsening renal function in acute heart failure: renal results of Pre-RELAX-AHF. Eur J Heart Fail 2011;13:961-7. 15. Lanfear DE, Peterson EL, Campbell J, et al. Relation of worsened renal function during hospitalization for heart failure to long-term outcomes and rehospitalization. Am J Cardiol 2011;107:74-8. 16. Patel UD, Greiner MA, Fonarow GC, et al. Associations between worsening renal function and 30-day outcomes among Medicare beneficiaries hospitalized with heart failure. Am Heart J 2010;160: 132-8. [e1]. 17. Felker GM, Lee KL, Bull DA, et al. Diuretic strategies in patients with acute decompensated heart failure. N Engl J Med 2011;364:797-805. 18. Aronson D, Burger AJ. The relationship between transient and persistent worsening renal function and mortality in patients with acute decompensated heart failure. J Card Fail 2010;16:541-7. 19. Centers for Medicare & Medicaid Services. BPCI Model 2: Retrospective Acute & Post Acute Care Episode. http://innovation.cms.gov/ initiatives/BPCI-Model-2/index.html. [Accessed March 25, 2014]. 20. Gheorghiade M, Vaduganathan M, Fonarow GC, et al. Rehospitalization for heart failure: problems and perspectives. J Am Coll Cardiol 2013;61:391-403. 21. Adams Jr KF, Fonarow GC, Emerman CL, et al. 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;149:209-16. 22. Hammill BG, Hernandez AF, Peterson ED, et al. Linking inpatient clinical registry data to Medicare claims data using indirect identifiers. Am Heart J 2009;157:995-1000. 23. Kociol RD, Hammill BG, Fonarow GC, et al. Generalizability and longitudinal outcomes of a national heart failure clinical registry: comparison of Acute Decompensated Heart Failure National Registry (ADHERE) and non-ADHERE Medicare beneficiaries. Am Heart J 2010;160:885-92. 24. Krumholz HM, Wang Y, Mattera JA, et al. An administrative claims model suitable for profiling hospital performance based on 30-day mortality rates among patients with heart failure. Circulation 2006;113:1693-701. 25. Harrell FE. Multivariable modeling strategies. Regression modeling strategies: with applications to linear models, logistic regression, and survival analysis. New York: Springer-Verlag. 200153-85. 26. Gray RJ. A class of K-sample tests for comparing the cumulative incidence of a competing risk. Ann Stat 1988;16:1141-54. 27. Fonarow GC, Abraham WT, Albert NM, et al. Factors identified as precipitating hospital admissions for heart failure and clinical outcomes: findings from OPTIMIZE-HF. Arch Intern Med 2008;168:847-54. 28. Blair JE, Pang PS, Schrier RW, et al. Changes in renal function during hospitalization and soon after discharge in patients admitted for worsening heart failure in the placebo group of the EVEREST trial. Eur Heart J 2011;32:2563-72. 29. Testani JM, Chen J, McCauley BD, et al. Potential effects of aggressive decongestion during the treatment of decompensated heart failure on renal function and survival. Circulation 2010;122:265-72. 30. Damman K, Navis G, Smilde TD, et al. Decreased cardiac output, venous congestion and the association with renal impairment in patients with cardiac dysfunction. Eur J Heart Fail 2007;9:872-8.
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31. Damman K, van Deursen VM, Navis G, et al. Increased central venous pressure is associated with impaired renal function and mortality in a broad spectrum of patients with cardiovascular disease. J Am Coll Cardiol 2009;53:582-8. 32. Mullens W, Abrahams Z, Francis GS, et al. Importance of venous congestion for worsening of renal function in advanced decompensated heart failure. J Am Coll Cardiol 2009;53:589-96. 33. Kociol RD, McNulty SE, Hernandez AF, et al. Markers of decongestion, dyspnea relief, and clinical outcomes among patients hospitalized with acute heart failure. Circ Heart Fail 2013;6:240-5. 34. Felker GM, Mentz RJ. Diuretics and ultrafiltration in acute decompensated heart failure. J Am Coll Cardiol 2012;59:2145-53.
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35. Chen HH, Anstrom KJ, Givertz MM, et al. Low-dose dopamine or low-dose nesiritide in acute heart failure with renal dysfunction: the ROSE acute heart failure randomized trial. JAMA 2013;310: 2533-43. 36. Chen HH, AbouEzzeddine OF, Anstrom KJ, et al. Targeting the kidney in acute heart failure: can old drugs provide new benefit? Renal Optimization Strategies Evaluation in Acute Heart Failure (ROSE AHF) trial. Circ Heart Fail 2013;6:1087-94. 37. Metra M, Cotter G, Davison BA, et al. Effect of serelaxin on cardiac, renal, and hepatic biomarkers in the Relaxin in Acute Heart Failure (RELAX-AHF) development program: correlation with outcomes. J Am Coll Cardiol 2013;61:196-206.
