Methods

We accessed clinical data for the study from the OPTIMIZE-HF registry. We also obtained research-identifiable Medicare claims data from the Centers for Medicare and Medicaid Services. The OPTIMIZE-HF registry contains data for patients admitted with HF from January 1, 2003, through December 31, 2004, at 259 participating hospitals. Eligible patients were those who presented with symptoms of HF during a hospitalization for which HF was the primary discharge diagnosis or for whom worsening HF was the primary reason for hospital admission. The registry included hospitals in a range of sizes throughout the United States, and Medicare beneficiaries enrolled in OPTIMIZE-HF are similar to the broader Medicare population with HF. Variables available for this study included gender, race, date of birth, hospital admission and discharge dates, American Hospital Association hospital identifier, medical history variables, and laboratory measurements and pharmacy indicators from admission and discharge. For race, we used the category “black” and combined all others as “nonblack.”

Medicare claims data in this study included inpatient claims and corresponding denominator files for all Medicare beneficiaries discharged from a hospitalization from 2002 through 2005. These files included institutional claims for facility costs covered by Medicare Part A; beneficiary, physician, and hospital identifiers; admission and discharge dates; and International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis and procedure codes. Corresponding denominator files included beneficiary identifier, date of birth, gender, race, date of death, and information about program eligibility and enrollment. Data from Medicare claims files also allowed us to calculate length of stay and Medicare payments during the year before the index hospitalization. We converted Medicare payment amounts to 2005 US dollars.

We included patients in the analysis if we could link a patient’s OPTIMIZE-HF registry record to an inpatient Medicare claim. Because OPTIMIZE-HF and Medicare claims data do not include direct patient identifiers, we linked the files by gender, admission date, discharge date, and hospital identifier. In combination, the fields could be used to identify unique hospitalizations. The earliest hospitalization for each patient served as the index HF hospitalization. Several patients were excluded from the analysis because they had missing data for serum creatinine level at admission (n = 166, 0.6%) or discharge (n = 3,650, 14%) or they had a history of dialysis (n = 485, 1.9%). Eligible patients lived in the United States, were ≥65 years of age, were enrolled in fee-for-service Medicare for ≥12 months before the index hospitalization, and were alive at the time of discharge from the index hospitalization.

We obtained patient demographic characteristics, medical history variables, laboratory and examination variables, discharge medications, and procedural information from the OPTIMIZE-HF registry. We imputed mean values of the overall cohort for patients who were missing values for systolic blood pressure (n = 18, 0.1%), serum sodium level (n = 54, 0.3%), or hemoglobin level (n = 322, 1.6%). We imputed the “no” value for missing values on several dichotomous variables, including left ventricular systolic dysfunction (n = 3,015, 15.0%), smoker within the previous year (n = 634, 3.2%), rales (n = 307, 1.5%), lower extremity edema (n = 375, 1.9%), and β-blocker prescription at discharge (n = 178, 0.9%).

We defined 3 categories of RF by serum creatinine level at admission. Normal RF at admission was defined as a serum creatinine level <1.5 mg/dl. Two categories of impaired RF at admission included serum creatinine levels of 1.5 to 1.9 mg/dl and ≥2 mg/dl. We defined worsening RF as a ≥0.3-mg/dl difference between discharge and admission serum creatinine levels.

Patients were followed for up to 1 year after discharge from the index hospitalization. We calculated all-cause mortality and hospital readmission within 1 year. Mortality information was obtained from Centers for Medicare and Medicaid Services denominator files. We also calculated time to first hospital readmission within 1 year after the index discharge date as the number of days between the index discharge date and subsequent readmission date. We did not count transfers to or from another hospital and admissions for rehabilitation (Diagnosis Related Group 462 or an admitting diagnosis code of V57.xx) as readmissions. In addition, we calculated total inpatient costs to Medicare by summing payment amounts and per diem adjustments from all inpatient claims (including transfer and rehabilitation claims) within 1 year of the index discharge date.

We present categorical variables as frequencies and continuous variables as means ± SDs or medians with interquartile ranges. In assessing differences in baseline characteristics between patients with worsening RF and those without, we used chi-square tests for categorical variables and Kruskal-Wallis tests for continuous variables.

We present 1-year outcomes stratified by whether patients had worsening RF. We also calculated 1-year inpatient costs by renal impairment group and compared groups using Kruskal-Wallis tests. We calculated unadjusted 1-year mortality rates using Kaplan-Meier methods and tested for differences between patients with worsening RF and those without using log-rank tests. We calculated unadjusted 1-year hospital readmission rates using the cumulative incidence function to account for the competing risk of death. We assessed differences in readmission between patients with worsening RF and those without using Gray tests.

Cox proportional hazards models with robust SEs accounted for site clustering when we examined unadjusted and adjusted relations between worsening RF and mortality. In multivariable analysis, we modeled 1-year mortality as a function of worsening RF, age, gender, race, medical history, admission laboratory and examination variables, medications at discharge, procedures during the index hospitalization, inpatient costs in the year before the index hospitalization, intensive care unit length of stay, and a variable indicating whether the length of stay for the index hospitalization was >7 days. We also used Cox proportional hazards models to examine relations between worsening RF and 1-year readmission.

We used generalized linear models with a log-link and Poisson distribution to examine the unadjusted relation between worsening RF and 1-year inpatient costs. Cost ratios, when using exponentiation, estimate the proportional increase in costs attributable to the variable. Generalized estimating equations accounted for correlations resulting from clustering of similar patients within hospitals. We also used this approach to examine adjusted relations and included the same baseline variables from the mortality and readmission models.

We used SAS 9.2 (SAS Institute, Cary, North Carolina) for all analyses. The institutional review board of the Duke University Health System (Durham, North Carolina) approved the study.

Results

After we linked OPTIMIZE-HF hospitalizations to Medicare inpatient claims and applied the exclusion criteria, the study population included 20,063 patients hospitalized with HF, of whom 3,581 (17.8%) had worsening RF at discharge. Median age was 80 years, and 56.2% were women. Cause of HF was ischemic in 9,671 patients (48.2%), and 7,246 patients (36.1%) had systolic dysfunction.

Table 1 lists baseline demographic characteristics of patients with worsening RF and those without. Patients with worsening RF were more likely to be black. These patients also had higher rates of hypertension, hyperlipidemia, peripheral vascular disease, anemia, history of cerebrovascular accident or transient ischemic attack, and chronic renal dysfunction. Mean length of stay was longer for patients with worsening RF. Patients with worsening RF were less likely to have systolic dysfunction and to be discharged with angiotensin-converting enzyme (ACE) inhibitors or angiotensin II receptor blockers (ARBs), digoxin, and diuretics. In contrast, patients with worsening RF were more likely to be discharged with antiplatelet medications and lipid-lowering agents.

Unadjusted all-cause mortality at 1 year in patients discharged with worsening RF was 35.4% versus 34.2% in patients without (p = 0.07; Figure 1 , Table 2 ). Multivariable predictors of mortality are presented in Table 3 . After adjustment for baseline characteristics, including serum creatinine level at admission, worsening RF was a significant independent predictor of 1-year all-cause mortality (hazard ratio 1.12, 95% confidence interval 1.04 to 1.20). Other variables were also significant predictors. After adjustment for other variables in the model, a serum creatinine level ≥2 mg/dl at admission was associated with a 46% higher hazard of mortality compared with the reference value (serum creatinine <1.5 mg/dl). Older age, systolic dysfunction, chronic obstructive pulmonary disease, peripheral vascular disease, previous cerebrovascular accident or transient ischemic attack, and index hospitalization length of stay >7 days increased the hazard of 1-year mortality. Beta blockers and ACE inhibitors/ARBs at discharge lowered the hazard of mortality. Diuretic prescription at discharge also lowered the hazard of mortality, whereas digoxin at discharge was associated with a slightly higher hazard of mortality.

Kaplan-Meier survival curves for presence (≥3 mg/dl) (dashed line) or absence (<3 mg/dl) (solid line) of worsening RF.

Table 3

Predictors of mortality, readmission, and inpatient Medicare costs at one year

Variable	Mortality		Readmission		Inpatient Medicare Costs
	HR (95% CI)	p Value	HR (95% CI)	p Value	Cost Ratio (95% CI)	p Value
Age (years)
65–69	1.00 (reference)		1.00 (reference)		1.00 (reference)
70–74	1.20 (1.07–1.34)	0.001	1.04 (0.97–1.11)	0.31	0.92 (0.83–1.03)	0.14
75–79	1.37 (1.24–1.51)	<0.001	1.04 (0.97–1.11)	0.25	0.85 (0.78–0.93)	<0.001
≥80	1.91 (1.73–2.10)	<0.001	1.05 (0.99–1.12)	0.13	0.69 (0.63–0.76)	<0.001
Male gender	1.07 (1.01–1.13)	0.02	0.98 (0.94–1.02)	0.37	1.04 (0.98–1.09)	0.20
Black	0.93 (0.84–1.04)	0.21	1.24 (1.17–1.33)	<0.001	1.27 (1.16–1.38)	<0.001
Nonblack	1.00 (reference)		1.00 (reference)		1.00 (reference)
Anemia	1.09 (1.02–1.17)	0.02	1.04 (0.99–1.10)	0.14	0.98 (0.93–1.03)	0.42
Atrial arrhythmia	1.06 (1.01–1.12)	0.03	1.05 (1.01–1.09)	0.01	1.00 (0.96–1.05)	0.88
Chronic obstructive pulmonary disease	1.20 (1.14–1.26)	<0.001	1.17 (1.12–1.22)	<0.001	1.09 (1.04–1.14)	<0.001
Chronic renal insufficiency	1.10 (1.02–1.19)	0.02	1.06 (0.99–1.12)	0.08	1.03 (0.96–1.10)	0.46
Depression	1.11 (1.03–1.19)	0.009	1.03 (0.98–1.09)	0.25	0.99 (0.93–1.04)	0.62
Diabetes mellitus	1.02 (0.96–1.08)	0.48	1.11 (1.07–1.15)	<0.001	1.09 (1.04–1.14)	<0.001
Heart failure cause, ischemic	1.00 (0.94–1.05)	0.92	1.06 (1.02–1.11)	0.006	0.98 (0.94–1.03)	0.45
Hyperlipidemia	0.84 (0.79–0.90)	<0.001	0.92 (0.88–0.96)	<0.001	1.02 (0.96–1.07)	0.57
Left ventricular systolic dysfunction	1.21 (1.14–1.29)	<0.001	1.02 (0.98–1.07)	0.25	1.02 (0.97–1.07)	0.43
Peripheral vascular disease	1.15 (1.08–1.22)	<0.001	1.11 (1.06–1.17)	<0.001	1.09 (1.02–1.16)	0.01
Previous cerebrovascular accident or transient ischemic attack	1.16 (1.08–1.25)	<0.001	1.10 (1.05–1.15)	<0.001	1.05 (0.99–1.10)	0.08
Smoker in previous year	1.09 (0.99–1.19)	0.07	1.07 (1.01–1.13)	0.03	0.99 (0.93–1.06)	0.86
Pulmonary reactive airway disease	1.04 (0.93–1.17)	0.45	1.05 (0.96–1.14)	0.27	1.04 (0.90–1.20)	0.57
Thyroid abnormality	1.04 (0.97–1.10)	0.26	1.05 (1.01–1.10)	0.02	1.02 (0.97–1.07)	0.42
Admission characteristics
Hemoglobin level	0.96 (0.94–0.97)	<0.001	0.97 (0.96–0.98)	<0.001	0.98 (0.97–0.99)	0.001
Lower extremity edema	0.95 (0.90–1.00)	0.04	0.98 (0.95–1.02)	0.40	1.00 (0.96–1.05)	0.83
Rales	1.15 (1.09–1.21)	<0.001	1.01 (0.97–1.06)	0.65	1.04 (1.00–1.08)	0.06
Serum creatinine level
<1.5 mg/dl	1.00 (reference)		1.00 (reference)		1.00 (reference)
1.5–<2.0 mg/dl	1.22 (1.14–1.31)	<0.001	1.19 (1.13–1.25)	<0.001	1.08 (1.03–1.14)	0.004
≥2.0 mg/dl	1.46 (1.36–1.57)	<0.001	1.25 (1.17–1.34)	<0.001	1.12 (1.02–1.22)	0.02
Serum sodium level	0.98 (0.98–0.99)	<0.001	1.00 (0.99–1.00)	0.10	1.00 (1.00–1.00)	0.96
Systolic blood pressure, per 10 mm Hg	0.92 (0.91–0.93)	<0.001	0.99 (0.98–0.99)	<0.001	1.00 (0.99–1.01)	0.52
Change in serum creatinine ≥0.3 mg/dl	1.12 (1.04–1.20)	0.003	1.02 (0.98–1.07)	0.30	0.98 (0.94–1.03)	0.50
Medications at discharge
Angiotensin-converting enzyme inhibitor or angiotensin receptor blocker	0.81 (0.77–0.86)	<0.001	0.97 (0.94–1.01)	0.21	1.04 (0.99–1.10)	0.13
Aldosterone antagonist	0.96 (0.88–1.04)	0.31	0.98 (0.92–1.03)	0.40	1.03 (0.96–1.11)	0.45
Antiplatelet agent	0.99 (0.94–1.04)	0.63	1.01 (0.98–1.05)	0.57	1.00 (0.95–1.04)	0.85
β blocker	0.80 (0.76–0.84)	<0.001	0.93 (0.89–0.97)	<0.001	0.97 (0.93–1.02)	0.20
Digoxin	1.07 (1.01–1.13)	0.02	1.03 (0.99–1.07)	0.20	1.01 (0.96–1.07)	0.67
Diuretic	0.92 (0.86–0.99)	0.02	1.04 (0.99–1.10)	0.12	1.01 (0.94–1.08)	0.81
Lipid-lowering agent	0.73 (0.69–0.77)	<0.001	0.98 (0.94–1.02)	0.37	1.08 (1.02–1.14)	0.006
Characteristics of index hospitalization
Coronary angiography	0.62 (0.55–0.70)	<0.001	0.97 (0.90–1.06)	0.53	1.17 (1.08–1.27)	<0.001
Implantable cardioverter–defibrillator	0.70 (0.54–0.90)	0.006	0.81 (0.69–0.96)	0.02	0.81 (0.67–0.98)	0.03
Inpatient costs to Medicare in previous year
$0	1.00 (reference)		1.00 (reference)		1.00 (reference)
≤$8,000	1.23 (1.15–1.31)	<0.001	1.27 (1.21–1.35)	<0.001	1.19 (1.12–1.27)	<0.001
$8,001–$21,000	1.30 (1.22–1.38)	<0.001	1.40 (1.33–1.47)	<0.001	1.34 (1.27–1.41)	<0.001
>$21,000	1.26 (1.18–1.33)	<0.001	1.58 (1.49–1.67)	<0.001	1.78 (1.67–1.90)	<0.001
Intensive care unit length of stay	1.00 (0.99–1.01)	0.81	1.00 (1.00–1.01)	0.31	1.01 (1.00–1.02)	0.002
Length of stay >7 days	1.37 (1.29–1.46)	<0.001	1.10 (1.05–1.15)	<0.001	0.99 (0.94–1.05)	0.83
Mechanical ventilation	1.16 (0.96–1.40)	0.13	1.07 (0.93–1.23)	0.37	1.19 (1.03–1.38)	0.02

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