Clinical Investigations

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Clinical Investigations Predictors of 30-Day Readmission in Patients Hospitalized With Decompensated Heart Failure Address for correspondence: Gian M.

1 Clinical Investigations Predictors of 30-Day Readmission in Patients Hospitalized With Decompensated Heart Failure Address for correspondence: Gian M. Novaro, MD, Department of Cardiology, Cleveland Clinic Florida, 2950 Cleveland Clinic Blvd. Weston, FL 33331, Marlow B. Hernandez, DO, MPH; Randall S. Schwartz, MD; Craig R. Asher, MD; Elsy V. Navas, MD; Victor Totfalusi, DO; Ivan Buitrago, MD; Ankush Lahoti, MD; Gian M. Novaro, MD Department of Internal Medicine (Hernandez, Schwartz, Totfalusi, Buitrago, Lahoti) and Department of Cardiology (Asher, Navas, Novaro), Cleveland Clinic Florida, Weston, Florida Background: Heart failure (HF) is the leading cause of hospitalizations and readmissions in the United States. Approximately one-third of patients admitted for HF are readmitted within 3 months; however, there are few markers that can identify those at highest risk for readmission. The purpose of this study was to identify clinical and laboratory markers associated with hospital readmission in decompensated HF. Hypothesis: Clinical and laboratory markers are associated with readmission rates in decompensated HF. Methods: Clinical and laboratory data from 412 patients admitted with HF were analyzed using a multivariable logistic regression analysis to find predictors of HF readmission by 30 days. Results: HF readmission rates at 30 days were lowest in those with at least 2 of the following discharge criteria: net fluid reduction >1.3 L (odds ratio [OR]: 0.27, P = 0.019), serum sodium level >135 (OR: 0.46, P = 0.034), and N-terminal brain natriuretic peptide level reduction >23% (OR: 0.11, P = 0.048). In multivariate analysis, those patients meeting 2 criteria had a very low risk of 30-day readmission (OR: 0.10, 95% confidence interval: , P = 0.019) compared to patients who failed to meet 2 criteria. Conclusions: A negative fluid balance, normal serum sodium, and net reduction in N-terminal brain natriuretic peptide level during hospitalization may be important indices to target to help reduce the likelihood of HF readmission within 30 days. Introduction In the United States, the estimated prevalence of heart failure (HF) approaches 6 million individuals. 1 Despite advances in the medical management of HF, it remains the leading cause of hospitalizations and readmissions. 2 Within 3 months of a HF hospitalization, there is a national 30% readmission rate and an associated 10% mortality rate. 3 Discharge planning, including comprehensive patient and family education with postdischarge support, has shown to significantly reduce readmission rates. 4 Various laboratory markers such as creatinine level have been examined as potential predictors for future HF readmission. 5 Studies have shown that low serum sodium levels are associated with increased mortality in hospitalized HF patients, 6,7 and persistent hyponatremia may serve as a marker for a higher rate of HF readmissions. 8 Brain natriuretic peptide (BNP) level-guided therapy has been shown to decrease healthcare costs associated with hospitalization for acute dyspnea in the outpatient setting. 9 Bettencourt et al showed that change in N-terminal BNP was the The authors have no funding, financial relationships, or conflicts of interest to disclose. 542 strongest predictor of readmission or 6-month mortality among other measured parameters. 10 There have been similar findings by Michtalik et al, 11 although others have failed to show a reliable association with BNP-guided therapy. 12 The objective of this study was to identify clinical and laboratory markers associated with a reduction in readmission rates in patients hospitalized with decompensated HF. Methods Study Population This was a retrospective study of hospitalized patients with an International Classification of Diseases, 9th Revision (ICD-9) diagnosis of HF conducted at Cleveland Clinic Florida in Weston, Florida from January 1, 2010 to December 31, Included patients had an ICD-9 diagnosis of HF listed as an active hospital problem. Study patients required at least 1 of the following: N-terminal BNP drawn at admission and within 3 days of discharge, daily fluid balance measurements throughout admission, and serum sodium measured within 1 day of discharge. The primary study end point was readmission within 30 days Received: June 28, 2013 Accepted: June 28, 2013

2 Table 1. Baseline Patient Characteristics Variable Study Group (n = 412) Age, y 74 ± 13 Male gender 62% Caucasian race 78% African American race 9% Body mass index, kg/m ± 7.9 Hypertension 80% Hyperlipidemia 65% Diabetes mellitus 44% Coronary artery disease 54% Peripheral artery disease 19% Smoking history 58% Chronic kidney disease 34% Atrial fibrillation 41% Obstructive lung disease 29% Cardiac resynchronization therapy 11% Ischemic cardiomyopathy 54% Systolic heart failure 43% Ejection fraction at admission, % 46 ± 18 N-terminal BNP at admission, pg/ml 8289 ± Abbreviations: BNP, brain natriuretic peptide. Data are expressed as mean value ± standard deviation or percentages of subjects. for decompensated HF. Secondary end points were readmission and mortality up to 6 months following the initial admission. Statistical Analysis Unadjusted trends in readmission rates as a function of clinical variables were evaluated. A 30-day multivariable logistic regression model for HF readmission was created, controlling for age and gender. This model was used to identify the clinical variables most predictive of HF readmission. When these variables were selected, a χ 2 test was used for categorical variables to find the odds ratio (OR) for readmission. For continuous variables, receiver operating characteristic curves were used to test for the optimum level for a given variable to predict HF readmission. A Kaplan-Meier curve was used to graphically show differences among the groups who met model criteria and those who did not. Differences within these groups were tested using a log-rank test. Significance was set at P value <0.05. Data were reported using means and medians (as appropriate), and their respective standard deviation and confidence intervals (CI) for means or medians. Statistical calculations were made using Table 2. Baseline and Discharge Patient Characteristics Variable Study Group (n = 412) ACE-I or ARB use 41% Aldosterone antagonist use 29% β-blocker use 80% Digoxin use 15% Loop diuretic use 69% Hemoglobin level at discharge, mg/dl 11.5 ± 1.9 Fluid balance at discharge, L 1.04 ± 1.8 Serum sodium level at discharge, mg/dl 138 ± 4.1 N-terminal BNP change in hospital, % 15± 40 Systolic BP at discharge, mm Hg 122 ± 22 Serum creatinine at discharge, mg/dl 1.54 ± 1.2 Discharge to skilled nursing facility 10% Physician follow-up within 72 hours 11% Days between readmission 73 ± 125 Heart failure readmission rate 14% Death from cardiovascular cause 4.3% Abbreviations: ACE-I, angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blocker; BNP, brain natriuretic peptide; BP, blood pressure. Data are expressed as mean value ± standard deviation or percentages of subjects. Serum sodium level at discharge was available in 383 (93%) patients. Fluid balance measurements were available in 245 (59%) patients. N-terminal BNP was available in 52 (13%) patients. Medcalc 2011 software (MedCalc Software, Mariakerke, Belgium). Results Baseline Patient Characteristics A total of 412 inpatients were identified with decompensated HF during hospitalization. Sixty-six percent of patients had a primary diagnosis of acute HF (n = 270), whereas the rest were admitted for another diagnosis, but HF was an ongoing hospital problem. The study group had a mean age of 74 years, were mostly male (62%), and self-identified as Caucasian (78%). The baseline patient characteristics are shown in Table 1. Treatment and Outcomes The median length of hospital admission was 3 days (95% CI: 2-4 days). The majority of HF readmissions occurred within the first 30 days of discharge (median 22 days, 95% CI: days). Coronary artery disease and chronic kidney disease trended to predict readmission at 30 days. Higher sodium levels, negative fluid balance, and a reduction in N-terminal BNP were associated with reductions in 30- day readmissions (Table 2). Using a receiver operating characteristic curve analysis for prognosis at 30 days, 543

3 Figure 1. Receiver operating characteristic curves for independent predictors of lower 30-day readmission rates. Abbreviations: AUC, area under the curve; BNP, brain natriuretic peptide. Table 3. Multivariate Predictors of Heart Failure Readmission at 30 Days Variable Odds Ratio 95% CI P Value Atrial fibrillation CRT-D in place Coronary artery disease Active cancer Chronic kidney disease Obstructive lung disease CRT during admission Diabetes mellitus New CABG New PCI Physician follow-up within 72 hours Weight change Fluid balance > 1.3 L Serum sodium >135mg/dL N-terminal BNP >23% reduction a 2 criteria met b Abbreviations: BNP, brain natriuretic peptide; CABG, coronary artery bypass grafting; CI, confidence interval; CRT, cardiac resynchronization therapy; CRT-D, cardiac resynchronization therapy-defibrillator; PCI, percutaneous coronary intervention. a Unadjusted odds ratio calculated using Haldane s estimator. b Odds ratio was adjusted for adjusted for age, gender, and comorbidities. discharge clinical markers were plotted with subsequent outcomes to obtain optimal variables predicting a lower rate of 30-day HF readmission: fluid reduction of >1.3 L, N-terminal BNP reduction of >23% compared to admission level, and discharge serum sodium level >135 (Figure 1). In multivariate analysis, meeting 2 or more of the above criteria was independently associated with a 90% lower risk of 30-day readmission, after adjusting for age, gender, and significant covariates (Table 3). Tables 4 compares patients who had at least 2 criteria met to those who did not. Patients experienced incremental risk reductions for HF readmission, at both 30 and 60 days, with meeting each goal. Patients who did not meet any criteria goal had a 13.6% readmission rate at 30 days compared to 1.3% for those who met 2 or more criteria (Figures 2 and 3). There was a trend toward patients with a primary diagnosis of HF being more likely to be readmitted for HF within 30 days compared to those with HF as a secondary problem (15% vs 8%; OR: 1.81, 95% CI: , P = 0.10, adjusted for age and gender). There was no difference with regard to primary study variables (N-terminal BNP, serum sodium at discharge, or fluid balance). All-cause readmission at 30 days was not statistically different for those with a primary diagnosis of HF than those with secondary diagnosis (24% vs 18%; OR: 1.68, 95% CI: , P = 0.29, adjusted for age and gender). Discussion Our study demonstrates that 3 variables (negative fluid balance >1.3 L, discharge serum sodium level >135, and N-terminal BNP reduction >23%) were each predictive of reduced hospital readmissions for HF, and the combination of these variables provided incremental predictive power. Furthermore, these predictors can be utilized in an easyto-use clinical model that can serve as a measure of 544

4 Figure 2. Readmission rates at 30 days and 60 days stratified by number of favorable criteria met. Abbreviations: HF, heart failure. Figure 3. Kaplan-Meier curve analysis demonstrating freedom from readmission among the groups who met 0-, 1-, 2-, and 3-model criteria. Abbreviations: HF, heart failure. effectiveness of HF management and the probability of recurrent HF admissions or cardiac events. In the 2009 focused update for the diagnosis and management of HF by the American College of Cardiology Foundation/American Heart Association, there were no specific recommendations regarding readiness for discharge or relief of congestion in patients admitted for HF. 13 Rather, the focus of most cardiac societies to curb the problem of HF readmission has been primarily geared toward quality improvement measures to assure patient education (regarding compliance, diet, daily weights, recognition of signs and symptoms of HF, and follow-up), physician adherence to evidence based HF medications (such as β-blockers and angiotensin-converting enzyme 545

5 Table 4. Characteristics and Heart Failure Outcomes for Patients With vs Without Favorable Predictors of Readmission Variable 0 1 Marker Met (n = 324) 2 Markers Met (n = 88) Fluid balance at discharge, L a 0.32 ± ± 1.19 Serum sodium at discharge, mg/dl a 137 ± ± 2.8 N-terminal BNP change, % a 6 ± ± 38 Systolic BP at discharge, mm Hg 123 ± ± 22 Serum creatinine at discharge, mg/dl Discharge to skilled nursing facility 8.3% 14.3% Physician follow-up within 72 hours a 12.4% 3.2% Time between readmission for HF, d a 66 ± ± 88 Death from cardiovascular cause b 5.3% 0% Abbreviations: BNP, brain natriuretic peptide; BP, blood pressure; HF, heart failure. a P < b P = Data are expressed as mean value ± standard deviation or percentages of subjects. inhibitors), and follow-up appointments within 7 days of discharge. Although numerous studies have identified clinical, laboratory, and hemodynamic predictors of adverse outcomes in patients admitted for HF, few studies have attempted to define variables that could be prospectively utilized by clinicians to predict HF readmissions. Among the laboratory markers known to be associated with adverse outcomes in patients with HF and higher rates of readmission are creatinine, albumin, hemoglobin, serum sodium, troponin, and BNP levels. 5 8,10 12,14 Of these variables, only BNP levels have been examined as a potential target to determine response to HF and likelihood of readmission. The utility of BNP levels to predict outcomes in ambulatory and hospitalized patients with HF has been previously studied. In a study of 182 patients admitted for acute decompensated HF, Bettencourt et al showed that a reduction in N-terminal BNP of 30% was a strong predictor of freedom from readmission for HF. 10 A similar cohort study by Michtalik et al of 241 patients hospitalized for acute HF found that failure to achieve a >50% reduction in N-terminal BNP levels was highly predictive of both readmission and death. 11 Among ambulatory HF patients, the Pro-BNP Outpatient Tailored Chronic Heart Failure Therapy study demonstrated that prospectively targeting N- terminal BNP target level of <1,000 pg/ml was associated with better outcomes than standard of care. 15 Because each of these studies assessed different populations of patients with variable degrees of congestion, it is not surprising that those different cutoff values were found to have significance. In our study, the inclusion of patients with preserved ejection fraction likely accounted for a more favorable outcome despite a lower reduction in N-terminal BNP. With half of our study group presenting with heart failure with preserved ejection fraction, our findings appear applicable to a realworld heart failure population reflective of the current trend, suggesting an increase in the prevalence of heart failure with preserved ejection fraction. 16 The intended contribution of this study was to propose a practical and reliable model to guide the clinical management of decompensated HF. Although the use of BNP to guide HF management is promising and easy to assess, the value of a single measure of response to therapy may not be effective in all patients. For example, a patient with reduction in BNP levels >23% of baseline and effective diuresis of >1.3 L with a serum sodium of 125 may still have significant excess free water and not be appropriate for discharge. Therefore, we believe the compound effect of 3 objective markers of relief of congestion and return to a euvolemic state may be advantageous in addition to subjective clinical data in assessing response to HF therapy. The major limitation of our study is selection bias related to the retrospective nature of the study. Factors such as fluid balance cannot be independently verified as being entirely accurate, and N-terminal BNP levels were only available in a subset of patients. Moreover, it is reasonable to assume those patients with more favorable laboratory values on admission will tend to have a better prognosis at discharge. We believe a prospective study would further validate these data, although the results may not be as clinically significant given the diverse nature of the pathophysiology and severity of HF presentation and associated comorbidities. A further limitation related to this retrospective study is the inability to account for HF readmissions to hospitals outside of our institution. Conclusion Either alone or in combination, a net negative fluid balance, normal serum sodium, and net reduction in N-terminal BNP at discharge are predictive of a lower rate of 30- day readmission for HF. Meeting these goals should be sought after prior to discharging a patient hospitalized for HF. Utilizing these noninvasive tools in the treatment of HF may supplement clinical judgment and help to reduce readmissions for HF. References 1. Lloyd-Jones D, Adams R, Carnethon M, et al; American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics 2009 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation. 2009;119:e21 e Haldeman GA, Croft JB, Giles WH, et al. Hospitalization of patients with heart failure: National Hospital Discharge Survey, 1985 to Am Heart J. 1999;137: Fonarow GC, Abraham WT, Albert NM, et al; OPTIMIZE-HF Investigators and Hospitals. Association between performance measures and clinical outcomes for patients hospitalized with heart failure. JAMA. 2007;297: McAlister FA, Stewart S, Ferrua S, et al. Multidisciplinary strategies for the management of heart failure patients at high risk for admission. A systematic review of randomized trials. JAmColl Cardiol. 2004;44: Krumholz HM, Chen YT, Wang Y, et al. Predictors of readmission among elderly survivors of admission with heart failure. Am Heart J. 2000;139: Klein L, O Connor CM, Leimberger JD, et al; OPTIME-CHF Investigators. Lower serum sodium is associated with increased 546

6 short-term mortality in hospitalized patients with worsening heart failure. Circulation. 2005;111: Madan VD, Novak E, Rich MW. Impact of change in serum sodium concentration on mortality in patients hospitalized with heart failure and hyponatremia. Circ Heart Fail. 2011;4: Gheorghiade M, Rossi JS, Cotts W, et al. Characterization and prognostic value of persistent hyponatremia in patients with severe heart failure in the ESCAPE Trial. Arch Intern Med. 2007;167: Mueller C, Laule-Kilian K, Schindler C, et al. Cost-effectiveness of B-type natriuretic peptide testing in patients with acute dyspnea. Arch Intern Med. 2006;166: Bettencourt P, Azevedo A, Pimenta J, et al. N-terminal pro-brain natriuretic peptide predicts outcome after hospital discharge in heart failure patients. Circulation. 2004;110: Michtalik HJ, Yeh HC, Campbell CY, et al. Acute changes in N- terminal pro-b-type natriuretic peptide during hospitalization and risk of readmission and mortality in patients with heart failure. Am J Cardiol. 2011;107: Noveanu M, Breidthardt T, Potocki M, et al. Direct comparison of serial B-type natriuretic peptide and NT-proBNP levels for prediction of short- and long-term outcome in acute decompensated heart failure. Crit Care. 2011;15:R Jessup M, Abraham WT, Casey DE, et al focused update: ACCF/AHA guidelines for the diagnosis and management of heart failure in adults: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines: developed in collaboration with the International Society for Heart and Lung Transplantation. Circulation. 2009;119: Alonso-Martineza JL, Llorente-Diez B, Echegaray-Agara M, et al. C-reactive protein as a predictor of improvement and readmission in heart failure. Eur J Heart Fail. 2002;4: Gaggin HK, Mohammed AA, Bhardwaj A, et al. Heart failure outcomes and benefits of NT-proBNP-guided management in the elderly: results from the prospective, randomized ProBNP outpatient tailored chronic heart failure therapy (PROTECT) study. J Card Fail. 2012;18: Owan TE, Hodge DO, Herges RM, et al. Trends in prevalence and outcome of heart failure with preserved election fraction. NEnglJ Med. 2006;355:

Clinical Risk Prediction Tools in Patients Hospitalized With Heart Failure

ManageMent Update Clinical Risk Prediction Tools in Patients Hospitalized With Heart Failure Gregg C. Fonarow, MD, FACC, FAHA Ahmanson UCLA Cardiomyopathy Center, University of California Los Angeles,