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Impact of Worsening Renal Function During Hospital Admission on Resource Utilization in Patients With Heart Failure Peter M. Herout, PharmDa,*, Qing Harshaw, MD, PhDa, Hemant Phatak, PhDb, Gorkem Saka, PhDc, Annie McNeill, PhDd, David Wu, PhDb, Vasilisa Sazonov, PhDb, Robert DeSagun, MPHa, and Jamshid Shirani, MDe Renal impairment frequently accompanies heart failure (HF) and is a recognized independent risk factor for morbidity and mortality. Few data are available assessing the impact of worsening renal function (WRF) during hospitalization on health care resource use in patients with HF. Health Insurance Portability and Accountability Act– compliant, deidentified, clinical, laboratory, and economic data for patients admitted to a tertiary care medical center with a primary diagnosis of HF were extracted by MedMining and reviewed retrospectively by the authors. Patients were excluded if they had no previous HF or were admitted for acute coronary syndrome or coronary artery bypass grafting within 30 days of index hospitalization. WRF was defined as >0.3 mg/dl increase in serum creatinine from baseline at any time during hospitalization. Of 5,803 hospitalized patients with primary HF diagnosis, 827 patients (14%) fulfilled all prespecified inclusion and exclusion criteria (74 ⴞ 14 years of age, 43% men, 98% white, admission serum creatinine 1.4 ⴞ 0.9 mg/dl, estimated glomerular filtration rate <90 ml/min/1.73 m2 at admission in 83%). During index hospitalization, WRF was identified in nearly 33%. Compared to patients without WRF, those with WRF had greater prevalence of diabetes (54% vs 43%), lower estimated glomerular filtration rate (44 ⴞ 30 vs 62 ⴞ 35 ml/min/1.73 m2), higher serum potassium (4.3 ⴞ 0.7 vs 4.2 ⴞ 0.7 mEq/L), and higher B-type natriuretic peptide (845 ⴞ 821 vs 795 ⴞ 947 pg/ml) at baseline (all p values <0.05). Patients developing WRF incurred higher total inpatient costs ($10,977, range 671 to 212,819, vs $7,820, range 697 to 269,797, p <0.001) and longer hospital stay (8.2 ⴞ 6.8 vs 5.7 ⴞ 5.5 days, p <0.001). In conclusion, occurrence of WRF during HF-related hospitalization is associated with higher hospitalization costs and longer hospital stay. © 2010 Elsevier Inc. All rights reserved. (Am J Cardiol 2010;106:1139–1145) Worsening renal function (WRF) during hospitalization, defined as an increase in serum creatinine (SCr) value ⱖ0.3 mg/dl, has been reported in nearly 30% of acute heart failure (HF) admissions.1–3 This has been associated with inpatient length of stay exceeding 10 days (adjusted risk ratio 3.2, confidence interval 2.2 to 4.9) and increased in-hospital mortality (adjusted risk ratio 7.5, confidence interval 2.9 to 19.3).2 This study evaluated the costs and resource usage associated with WRF in a group of patients admitted with HF and a wide range of renal function in a single integrated health care system. Methods Data were prepared by MedMining (Danville, Pennsylvania), a Geisinger business unit that licenses Health Insurance a EPI-Q, Inc., Oak Brook, Illinois; bGlobal Health Outcomes, Merck and Co., Inc., Whitehouse Station, New Jersey; cHealth Economics Statistics and dEpidemiology, Merck Research Laboratories, Upper Gwynedd, Pennsylvania; and eDepartment of Cardiology, Geisinger Medical Center, Danville, Pennsylvania. Manuscript received March 10, 2010; revised manuscript received and accepted June 2, 2010. Support of this study was provided by Merck and Co., Inc., Whitehouse Station, New Jersey. *Corresponding author: Tel: 630-570-5505; fax: 630-570-5506. E-mail address: [email protected] (P.M. Herout). 0002-9149/10/$ – see front matter © 2010 Elsevier Inc. All rights reserved. doi:10.1016/j.amjcard.2010.06.026 Portability and Accountability Act– compliant, de-identified patient clinical, laboratory, and economic data to promote research based on data from a real-world setting. After an approved process for de-identifying the data, MedMining’s honest broker linked the following data together: (1) clinical and laboratory data from the electronic medical record system (Epic Systems Corporation, Madison, Wisconsin) used by Geisinger Health System (GHS) and (2) actual encounter-level cost data, including direct and indirect costs, from Geisinger’s financial data warehouse. The GHS consists of 3 hospitals located primarily in rural Pennsylvania with 791 beds and nearly 2 million yearly outpatient visits among its 41 community practice sites. These rural communities mostly consist of Caucasian/European-descent inhabitants. All electronic health record patient-level data were captured for a period of ⱖ12 months before the index hospitalization, throughout the index hospitalization, and for up to 60 days after hospital discharge to examine preindex hospitalization health care usage, costs and resource use related to inpatient care, and short-term follow-up health care resource use and mortality. The database contained data of all patients admitted to a GHS facility with a primary or secondary inpatient HF diagnosis from January 2004 through August 2008. Patients were considered for inclusion in the study if they were ⱖ19 years of age and had ⱖ12 months of GHS encounter data before an index hospitalization with HF based on Internawww.ajconline.org 1140 The American Journal of Cardiology (www.ajconline.org) Figure 1. Study population. ACS ⫽ acute coronary syndrome; CABG ⫽ coronary artery bypass grafting; IV ⫽ intravenous; LVAD ⫽ left ventricular assist device. Table 1 Demographic and baseline clinical characteristics in total cohort and those without or with worsening renal function Variable Total (n ⫽ 827) No WRF (n ⫽ 515) WRF (n ⫽ 252) Age (years) Men White Body mass index (kg/m2) Current smoker Admission through emergency department Insurance coverage Medicare Medicaid Commercial Self/other Preadmission health care use Hospitalizations Hospital stay (days) Annual health care costs ($) Health care encounters  blocker Angiotensin-converting enzyme inhibitor/angiotensin receptor blocker Loop diuretics Furosemide equivalent diuretic dose Co-morbidities Cerebrovascular disease Hypertension Atrial fibrillation Diabetes mellitus Myocardial infarction Valvular disease Renal insufficiency Serum creatinine increase ⱖ0.3 mg/dl in previous 3 months Chronic pulmonary disease 73 ⫾ 14 355 (43%) 814 (98%) 30 ⫾ 8 81 (10%) 389 (72%) 74 ⫾ 14 228 (44%) 507 (99%) 30 ⫾ 7 53 (10%) 258 (73%) 74 ⫾ 14 103 (41%) 248 (98%) 30 ⫾ 8 23 (9%) 122 (76%) 434 (53%) 29 (4%) 328 (40%) 35 (4%) 289 (56%) 15 (3%) 195 (38%) 16 (3%) 123 (49%) 9 (4%) 102 (41%) 18 (7%) 1.4 ⫾ 0.8 9.6 ⫾ 9.2 13,518 ⫾ 21,912 49 ⫾ 45 461 (56%) 375 (45%) 518 (63%) 58 ⫾ 56 1.5 ⫾ 0.9 10.3 ⫾ 9.7 13,518 ⫾ 21,912 50 ⫾ 46 288 (56%) 224 (44%) 329 (64%) 55 ⫾ 44 1.3 ⫾ 0.7 8.5 ⫾ 8.5 14,280 ⫾ 22,455 46 ⫾ 41 136 (54%) 117 (46%) 148 (59%) 63 ⫾ 78 Data are presented as mean ⫾ SD or number of patients (percentage). * p ⬍0.05 for no WRF versus WRF. 142 (17%) 691 (84%) 420 (51%) 382 (46%) 151 (18%) 418 (51%) 213 (26%) 91 (11.0%) 399 (48%) 90 (18%) 426 (89%) 252 (49%) 222 (43%) 87 (17%) 250 (49%) 121 (24%) 66 (12.8%) 249 (48%) 45 (18%) 220 (87%) 141 (56%) 136 (54%)* 55 (22%) 141 (56%) 88 (35%)* 24 (9.5%) 125 (50%) Heart Failure/Economic Impact of WRF in HF Admissions 1141 Table 2 Laboratory values obtained at index admission in total cohort and in those without or with worsening renal function Laboratory Variable Serum creatinine (mg/dl) Estimated glomerular filtration rate (ml/min/1.73 m2) Serum urea nitrogen (mg/dl) Serum sodium (mEq/L) Serum potassium (mEq/L) B-type natriuretic peptide (pg/ml) ⱕ250 251–400 ⬎400 Total (n ⫽ 827) No WRF (n ⫽ 515) WRF (n ⫽ 252) 1.39 ⫾ 0.93 57 ⫾ 35 32 ⫾ 22 139 ⫾ 4 4.2 ⫾ 0.7 814 ⫾ 901 (n ⫽ 422) 111 (26%) 79 (19%) 232 (55%) 1.36 ⫾ 0.86 62 ⫾ 36 32 ⫾ 23 139 ⫾ 4 4.2 ⫾ 0.7 795 ⫾ 947 (n ⫽ 254) 76 (30%) 49 (19%) 129 (51%) 1.48 ⫾ 1.01* 44 ⫾ 30* 33 ⫾ 21 139 ⫾ 4 4.3 ⫾ 0.7* 845 ⫾ 821* (n ⫽ 157) 31 (20%) 28 (18%) 98 (62%) Data are presented as mean ⫾ SD or number of patients (percentage). * p ⬍0.05 for no WRF versus WRF. tional Classification of Diseases, Ninth Revision, Clinical Modification codes. Patients were excluded if they had no documentation of HF before the index hospitalization (i.e., de novo HF), died within 24 hours of the index admission, or had no documented baseline (within 1 day of hospital admission) SCr. To limit the confounding effect of procedures or drug exposures known to be associated with acute renal dysfunction, additional criteria for exclusion included admission with a primary diagnosis of cardiogenic shock or acute coronary syndrome; exposure to radiographic contrast agents during the index hospitalization; current or previous use of a left ventricular assist device; chemotherapy or coronary artery bypass grafting surgery during or within 30 days of the index hospitalization; solid organ transplantation before or during the index hospitalization; or diagnosed end-stage renal disease on long-term dialysis. Of the original 12,277 patients admitted with a primary or secondary diagnosis of HF during the prespecified period, 5,803 met all inclusion criteria (Figure 1). Of the latter, 4,976 (85.7%) were also excluded due to the presence of ⱖ1 exclusion criterion. The remaining 827 patients (14.3%) who fulfilled all inclusion and exclusion criteria are the subjects of this evaluation. The primary outcome measurement was total cost of the index hospitalization for patients stratified to the no-WRF and WRF groups. Costs are reported as the actual cost of care derived from the GHS Eclipsys cost accounting system database. All costs were adjusted to 2007 price levels using the medical care component of the consumer price index. Among inpatient costs, the following were evaluated: medication costs, costs for physician services, costs for procedures and laboratory tests, and costs for general hospital services. Inpatient usage variables included length of stay (total, intensive care unit, telemetric monitoring), number of procedures or laboratory tests performed, number of medication orders written, and total amount of intravenous loop diuretic (in furosemide equivalents) administered. The following doses of diuretics were considered equivalent: furosemide 40 mg, bumetanide 1 mg, and torsemide 10 mg. Hospital mortality and 30- and 60-day health care outcomes and usage were also evaluated. The descriptive analysis includes population demographics, co-morbidities, information related to treatment such as the site where treatment was provided (e.g., Figure 2. Distribution of admission eGFR for total study population (n ⫽ 827) (left column), population not developing WRF (n ⫽ 515) (center column), and population developing WRF (n ⫽ 252) (right column). eGFR (milliliters per minute per 1.73 m2) was calculated using the Modification of Diet in Renal Disease Study equation and admission study variables and reported as percentage of study group within the ranges ⬎90 (A), 60 to 89 (B), 30 to 59 (C), 15 to 29 (D), and ⬍15 (E). inpatient, outpatient), medications, and select baseline laboratory values. Health care resource units (e.g., readmissions, emergency department visits, office visits, procedures, length of stay) and costs are stratified and compared by the presence of WRF defined as an increase in SCr ⱖ0.3 mg/dl from hospital admission to any time during the index hospitalization. Univariate analysis was conducted between the no-WRF and WRF groups for primary outcomes and secondary outcomes using chisquare test for categorical variables and t test or MannWhitney U test for continuous variables based on variable characteristics and data distribution. Comparison of continuous variables among ⱖ3 groups was performed by Kruskal-Wallis analysis of variance. Multivariable analysis was performed for the primary outcome. A generalized linear regression model with log-link function and ␥ distribution was performed to estimate total costs associated with the WRF and no-WRF groups. Variables that were found to have a difference at the significance level ⱕ0.10 during univariate analysis and those identified as clinically important from the relevant literature were included in the model to adjust for baseline differences. Correlations between variables were evaluated before modeling. If the correlation coefficient for 2 variables was ⬎0.65 and statistically significant, then only 1 1142 The American Journal of Cardiology (www.ajconline.org) Table 3 Index hospitalization costs for total cohort and for patients without or with worsening renal function Cost Variable ($) Total Mean ⫾ SD Hospital services Mean ⫾ SD Physician services Mean ⫾ SD Medications administered Mean ⫾ SD Procedures Mean ⫾ SD Total (n ⫽ 827) No WRF (n ⫽ 515) WRF (n ⫽ 252) 8,825 (671–269,797) 16,195 ⫾ 22,675 7,570 (1,154–246,067) 13,961 ⫾ 19,735 1,193 (12–29,850) 2,355 ⫾ 3,532 393 (3–52,980) 1,396 ⫾ 3,862 552 (2–11,014) 900 ⫾ 1,102 7,820 (697–269,797) 13,445 ⫾ 20,392 6,878 (1,251–246,067) 11,532 ⫾ 17,812 1,071.53 (12–29,850) 2,030 ⫾ 3,254 352.43 (3–52,980) 1,145 ⫾ 3,532 501 (2–9,333) 773 ⫾ 858 10,977 (671–212,819)* 20,829 ⫾ 26,686 9,478 (1,866–183,872)* 17,752 ⫾ 22,791 1,627.46 (46–28,947)* 3,218 ⫾ 4,327 680 (15–41,163)* 2,184 ⫾ 4,729 911 (28–11,014)* 1,309 ⫾ 1,465 Data are presented as median (range) or mean ⫾ SD where noted. * p ⬍0.05 for no WRF versus WRF. Table 4 Index hospitalization resource usage for total cohort and for patients without or with worsening renal function Usage Variable Total length of stay (days) Intensive care Telemetry unit Length of stay ⬎4 days Total procedures performed Medication orders Laboratory results Intravenous loop diuretic doses given Total intravenous loop diuretic (mg) Total (n ⫽ 827) No WRF (n ⫽ 515) WRF (n ⫽ 252) 6.2 ⫾ 6.0 5.1 ⫾ 3.9 (n ⫽ 81) 4.5 ⫾ 3.5 (n ⫽ 351) 416 (50%) 33 ⫾ 39 37 ⫾ 37 76 ⫾ 79 0.97 ⫾ 0.91 270.57 ⫾ 1,085.21 5.7 ⫾ 5.5 5.9 ⫾ 4.3 (n ⫽ 36) 4.0 ⫾ 2.8 (n ⫽ 214) 246 (48%) 28 ⫾ 29 34 ⫾ 36 66 ⫾ 67 0.84 ⫾ 0.86 190.62 ⫾ 640.25 8.2 ⫾ 6.8* 4.5 ⫾ 3.4 (n ⫽ 44) 6.0 ⫾ 4.2* (n ⫽ 117) 164 (65%)* 48 ⫾ 53* 47 ⫾ 39* 104 ⫾ 94* 1.42 ⫾ 0.89* 487.26 ⫾ 1,719.53* Data are presented as mean ⫾ SD or number of patients (percentage). * p ⬍0.05 for no WRF versus WRF. variable was included in the model to avoid multicollinearity. In addition, we used the general linear regression model for sensitivity analysis by looking at the association between level of SCr change and cost. The level of significance for all comparisons was set at a p value ⱕ0.05. All analyses were performed using SAS 9.1 (SAS Institute, Cary, North Carolina) and STATA 9 (STATA Corp. LP, College Station, Texas). Results Baseline clinical and demographic characteristics of the 827 patients and those of the 2 subgroups, without and with WRF, are presented in Table 1. Approximately 55% of patients (n ⫽ 453) were ⱖ75 years of age at the index admission. Laboratory data obtained at admission are presented in Table 2. All subjects had all laboratory values available on admission except where noted. Sixty subjects had no follow-up SCr value during the index admission and therefore are not represented within the no-WRF or WRF subgroup. Prehospitalization SCr (within 3 months) was available in 337 patients and was acutely increased in 27% (n ⫽ 92). The percentage of the patients without or with WRF who had increased prehospitalization SCr was not significantly different (12.8% vs 9.5%, p ⫽ 0.183). A coded diagnosis of renal insufficiency before the index hospitalization was present in 26% of the total cohort. Overall, 36% presented with an increased SCr on admission to the hospital (defined as SCr ⬎1.3 mg/dl) and 82% had an estimated glomerular filtration rate (eGFR) ⬍90 ml/min as calculated by the Modification of Diet in Renal Disease method. Decreased eGFR at admission was significantly more prevalent in those who would eventually show WRF during the index hospitalization (203, 81%, vs 285, 55%). Of 767 patients with a follow-up SCr level during the index hospitalization, 252 (32.6%) had increased SCr ⱖ0.3 mg/dl anytime during hospitalization. Severity of WRF was proportional to the interval from admission to SCr measurement such that SCr increases of 0.30 to 0.39 mg/dl occurred in 3.0 ⫾ 1.9 days and increases ⱖ0.5 g/dl occurred in 5.3 ⫾ 5.9 days. Patients with an admission eGFR range of 30 to 59 ml/min represented the largest proportion of patients who developed WRF (Figure 2). The median of total cost of the index hospitalization was $8,826 (671 to 269,797) for the entire cohort (Table 3) and was significantly lower in those without WRF compared to those with WRF ($7,820, 697 to 269,797, vs $10,977, 671 to 212,819, p ⬍0.0001). Patients without WRF also had a shorter total length of stay; a smaller proportion remaining hospitalized ⬎4 days; fewer procedures, medication orders, and laboratory tests; and lower usage of intravenous loop diuretics (Table 4). Heart Failure/Economic Impact of WRF in HF Admissions 1143 Table 5 Generalized linear regression model of total cost of index hospitalization Parameter Estimate SE 95% Confidence Interval Wald Chi-Square p Value Intercept Age 65–74 years Age ⱖ75 years Male gender New emergency admission Worsening renal function Previous hypertension* Admission B-type natriuretic peptide (pg/ml) Previous diabetes* Previous renal insufficiency* Total intravenous loop dose† Admission serum sodium Emergency department admission, age 65–74 years Emergency department admission, age ⱖ75 years Scale 10.6206 ⫺0.0498 ⫺0.8150 ⫺0.0228 ⫺0.2204 0.4767 ⫺0.0504 0.0001 ⫺0.0787 0.0727 0.0001 ⫺0.0065 ⫺0.2177 0.4106 1.6954 1.0659 0.1465 0.1281 0.0682 0.1472 0.0715 0.1016 0.0000 0.0696 0.0778 0.0000 0.0076 0.2049 0.1725 0.0947 8.5314 to 12.7098 ⫺0.3369 to 0.2374 ⫺1.0661 to ⫺0.5638 ⫺0.1564 to 0.1108 ⫺0.5088 to 0.0681 0.3366 to 0.6168 ⫺0.2495 to 0.1486 ⫺0.0000 to 0.0001 ⫺0.2151 to 0.0577 ⫺0.0797 to 0.2252 0.0001 to 0.0002 ⫺0.0215 to 0.0084 ⫺0.6193 to 0.1840 0.0725 to 0.7488 1.5197 to 1.8915 99.28 0.12 40.46 0.11 2.24 44.47 0.25 2.49 1.28 0.87 15.91 0.73 1.13 5.67 ⬍0.0001 0.7340 ⬍0.0001 0.7382 0.1343 ⬍0.0001 0.6195 0.1148 0.2580 0.3497 ⬍0.0001 0.3938 0.2881 0.0173 * From the International Classification of Diseases, Ninth Revision, Clinical Modification codes before index hospitalization. Total amount of intravenous loop diuretic during index hospitalization. † Table 6 Impact of worsening renal function on total cost of index hospitalization Change in SCr Estimated Parameter ⬍0.3 mg/dl ⱖ0.3 mg/dl ⬍0.1 mg/dl ⱖ0.1–⬍0.2 mg/dl ⱖ0.2–⬍0.3 mg/dl ⱖ0.3–⬍0.4 mg/dl ⱖ0.4–⬍0.5 mg/dl ⱖ0.5 mg/dl reference group 0.4764 reference group ⫺0.0322 0.1152 ⫺0.0175 0.3144 0.7382 95% CI Mean Incremental Cost ($) 0.3366 to 0.6168 5,846 ⫺0.2248 to 0.1604 ⫺0.0927 to 0.3231 ⫺0.2509 to 0.2158 0.0264 to 0.6024 0.5520 to 0.9245 ⫺813 442 ⫺1,603 2,806 8,456 95% CI of Cost ($) p Value 5,827 to 5,864 ⬍0.0001 ⫺843 to ⫺784 411 to 473 ⫺1,640 to ⫺1,565 2,765 to 2,847 8,434 to 8,479 0.7428 0.2774 0.8828 0.0324 ⬍0.0001 CI ⫽ confidence interval. Of the 809 patients with hospital discharge information, 42 (5.2%) died, 391 (48.3%) were discharged home, 363 (44.9%) were discharged to another medical facility or rehabilitation center, and 13 (1.6%) were discharged to endof-life care. Patients without WRF had significantly lower hospital mortality compared to those with WRF (16, 3.1%, vs 25, 9.9%, p ⬍0.0001). Thirty- and 60-day outcomes including mortality, all-cause and HF-related hospital readmissions, ambulatory encounters, and total health care costs were not significantly different between those without and those with WRF. By multivariate analysis, WRF, total intravenous loop diuretic dose, and admission through the emergency department of those ⱖ75 years of age were independent predictors of hospitalization costs, although the overall cost of hospitalization was lower in those ⱖ75 years old at admission (Table 5). The impact of WRF on total index hospitalization cost is presented in Table 6. After adjusting for confounding variables, adjusted mean cost of hospitalization was $5,846 higher for those with WRF compared to patients without. The corresponding difference between the adjusted mean hospital costs of those with an increase in SCr ⱖ0.5 mg/dl compared to those with an increase ⬍0.1 mg/dl was $8,456. Analysis indicated that a threshold of an increase of SCr of 0.3 mg/dl is associated with a statistically significant increase in hospital cost per patient. Discussion The present study provides further data in support of the observed high prevalence and negative impact of baseline renal impairment and WRF on the hospital course and outcome of patients with established HF who are hospitalized with acute decompensated HF. Thus, moderate to severe decrease in eGFR was noted in ⬎60% of the patients at admission and nearly 1/3 showed an increase in SCr of ⱖ0.3 mg/dl during the course of their hospital stay. Such deterioration in renal function was found to be associated with longer hospital stay, and greater resource use, cost of hospitalization, and in-hospital mortality. Prominent among the predisposing factors for WRF were pre-existing renal dysfunction and diabetes mellitus. The patients included in this study had the general characteristics of patients treated at other tertiary care medical centers but differed from those by being taken care of in a primarily rural setting and having had established HF. Prevalences of concomitant diseases and pre-existing chronic kidney disease in our patients were similar to those in previous studies.4 –10 Impaired renal function is frequently seen in hospitalized patients with HF and is a powerful independent determinant of outcomes.1– 4 In recent years, there has been a trend toward higher SCr and lower eGFR in patients with HF admitted to the hospital.5 Based on recent reports, some 1144 The American Journal of Cardiology (www.ajconline.org) degree of renal impairment is present in ⬎50% of patients hospitalized for HF and moderate to severe renal dysfunction is observed in 1/3 of such patients.1,6,7,11 Chronic kidney disease was reported as present in 30% of the 105,388 hospitalization episodes in the Acute Decompensated Heart Failure National Registry (ADHERE) and documentation of a SCr exceeding 2.0 mg/dl occurred in 1/5 of cases.8 Of patients enrolled in the Candesartan in Heart Failure Assessment of Reduction in Mortality and Morbidity (CHARM) study, severity of renal dysfunction was a strong independent predictor of hospitalization and mortality.9 It is important to note that the presence of renal dysfunction is also a strong predictor of future development of HF in those with acute myocardial infarction.12 We used a largely accepted definition of WRF, that is, an absolute increase in SCr of ⱖ0.3 mg/dl (26.5 mol/L) at any time during hospitalization compared to the value obtained at admission. Others have used different criteria including requirements for relative increases in SCr compared to baseline, achievement of a minimum level of SCr, or use of eGFR rather than SCr.4,13–15 For 2 reasons, the criterion used in our study appears appropriate. First, it has been used in many previous studies, is shown to be a clinically relevant and appropriate choice, and provides a basis for direct comparison of the findings.1–3,16 –20 Second, a stricter criterion may yield lower incidences of WRF and exclude many patients with heightened risk for adverse outcome from consideration.13 Importantly, the threshold of 0.3 mg/dl used in this study had the best discriminating power for identifying the highest increase in hospital cost per patient (Table 6). Others have also shown that a threshold of a ⱖ0.3 mg/dl increase in SCr has the best overall diagnostic accuracy for identification of patients at high risk for in-hospital mortality and prolonged hospital stay.6 This is unlike the finding of another study indicating that a relative increase ⱖ25% from the admission SCr value (rather than an absolute increase) lacked sensitivity and showed a relatively small effect size for predicting mortality.7 In general, WRF occurs relatively early in the course of hospitalization.21 However, as shown in our study, the magnitude of SCr increase increases with length of hospitalization. As defined in this study, WRF occurs in 1/6 of patients with HF in the ambulatory setting and 1/3 of those admitted with acute decompensated HF.1–3,20 The major predisposing factors to WRF can be generally categorized into demographic (age, male gender), systemic (hypertension, diabetes, vascular disease), renal (pre-existing kidney dysfunction), medication related (diuretics, calcium channel blockers), and cardiac (atrial fibrillation, increased ventricular filling pressures).1–3,13,17,19,20,22 Importantly, several studies have indicated a lack of relation between cardiac output and WRF.1,2,13,17,19 The latter has been specifically addressed in the Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness (ESCAPE) trial that demonstrated a lack of relation between baseline renal function and cardiac index, thus indicating that impaired renal function in patients with HF may not necessarily be a direct consequence of low cardiac output.18 Occurrence of WRF during hospitalization in patients with acute decompensated HF has been associated with increased risk of in-hospital mortality, rehospitalization, and postdischarge mortality.1,6,7,15 Although we did observe a statistically significantly greater unadjusted in-hospital mortality in patients meeting the criteria for WRF versus those who did not, our study was not designed or powered to detect differences in short- or long-term clinical outcomes. Total intravenous loop diuretic dose was significantly greater in the WRF group and independently associated with higher hospitalization costs; however, no causal relation between loop diuretic use and WRF can be assumed. We used strict criteria for patient selection to assure uniformity and to decrease clinical heterogeneity in our patients. The selection process limited the size of the final cohort and may have thus decreased the power of the study to identify other factors that may have influenced renal function, length of hospital stay, hospital cost, and the outcome of our patients. Nevertheless, the present sample size was sufficient to detect important differences between those with and without WRF and to support our conclusions. Due to the retrospective nature of the study, measurements of SCr and other relevant laboratory parameters were not uniform and variations in the timing of these measurements may have introduced unknown biases in the study. In-hospital management choices in individual patients may have differed significantly in this study depending on the year and place of admission and the specialty of the treating physician. This study reports the results of HF referral and management in a primarily rural setting and a relatively homogenous patient population and thus may not be generalizable to other clinical settings. HF is a costly condition and has an increasing economic impact on the national health care system. More than 1/2 of the total cost of the management of HF is related to hospitalization. Factors that precipitate hospitalization, increased hospital stay, and need for resource usage can add to the economic impact of HF. Limited information is available regarding the impact of WRF on cost of hospitalization and its economic attributes in patients with acute decompensated HF. In the present study, WRF is shown to be an independent predictor of hospitalization costs. After adjusting for confounding variables, the calculated cost of hospitalization was $5,846 higher for those with WRF compared to patients without. Considering the large number of annual hospital admissions for HF (⬎1 million) and the current prevalence of WRF (roughly 30% of patients), this estimate of additional hospital cost would translate into a projected total cost of nearly $2 billion. 1. Krumholz HM, Chen YT, Vaccarino V, Wang Y, Radford MJ, Bradford WD, Horwitz RI. Correlates and impact on outcomes of worsening renal function in patients ⱖ65 years of age with heart failure. Am J Cardiol 2000;85:1110 –1113. 2. Forman DE, Butler J, Wang Y, Abraham WT, O’Connor CM, Gottlieb SS, Loh E, Massie BM, Rich MW, Stevenson LW, Young JB, Krumholz HM. Incidence, predictors at admission, and impact of worsening renal function among patients hospitalized with heart failure. J Am Coll Cardiol 2004;43:61– 67. 3. Cowie MR, Komajda M, Murray-Thomas T, Underwood J, Ticho B. 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