European Heart Journal Advance Access originally published online on April 19, 2006
European Heart Journal 2006 27(10):1216-1222; doi:10.1093/eurheartj/ehi859
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Prevalence and impact of worsening renal function in patients hospitalized with decompensated heart failure: results of the prospective outcomes study in heart failure (POSH)
1 National Heart and Lung Institute, Imperial College, London, UK
2 Department of Cardiology, Hôpital Pitié-Salpétrière, Paris, France
3 Biogen Idec Cambridge, MA, USA
Received 23 November 2004; revised 10 March 2006; accepted 17 March 2006; online publish-ahead-of-print 19 April 2006.
* Corresponding author. fax: +44 207 351 8148. E-mail address: m.cowie{at}imperial.ac.uk
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Abstract |
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Aims To determine the prevalence and risk factors for worsening renal function (WRF) among patients hospitalized for decompensated heart failure (HF) and the association with subsequent re-hospitalization and mortality.
Methods and results We prospectively enrolled 299 patients across eight European countries (mean age 68, 74% men). HF was defined using the European Society of Cardiology criteria, but only patients with a history of ejection fraction 
40% on echocardiography were recruited. WRF was defined as an increase in serum creatinine >26 µmol/L (
0.3 mg/dL) from admission. Follow-up was 95% complete to 6 months. Nearly one-third of patients [72 of 248 patients, 29% (95% CI 26–32%)] developed WRF during hospitalization, excluding patients who had a major in-hospital complication likely to compromise renal function. The risk of WRF in this group was independently associated with serum creatinine levels on admission [odds ratio (OR) 3.02 (95% CI 1.58–5.76)], pulmonary oedema [OR 3.35 (1.79–6.27)], and a history of atrial fibrillation [OR 0.35 (0.18–0.67)]. Although the mortality of WRF patients was not increased significantly, the length of stay was 2 days longer [median 11 days (90% range (4–41) vs. 9 days (4–34), P=0.006]. The re-hospitalization rate was similar in both groups.
Conclusion WRF is common in patients admitted to European hospitals with decompensated HF. Such patients have longer duration admissions, but a similar mortality and re-hospitalization rate to those without WRF (if patients experiencing a major in-hospital complication are excluded).
Key Words: Heart failure • Worsening renal function • Risk factors • Prognosis • Hospitalization
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Introduction |
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Several studies have reported the association between the development of worsening renal function (WRF) in patients admitted to hospital with decompensated heart failure (HF) and poor clinical outcomes. The mechanism of this association remains unclear, but WRF has been reported to be associated with higher mortality during hospitalization, longer duration of hospital stay, and increased all-cause re-hospitalization rates.1–5
Previous reports have largely derived from retrospectively collected data from US centres or from clinical trials of drug therapy.1,2,6,7 We report the results of the first prospective, multicentre European survey which sought to determine the frequency of WRF during hospital admission for decompensated HF, identify risk factors for WRF, and to evaluate the impact of WRF on the subsequent risk of re-hospitalization and in-hospital, 30-day and 180-day mortality.
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Methods |
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Consecutive patients admitted with decompensated HF to 17 centres in eight European countries were recruited between October 2001 and November 2002. The list of investigators and sites is given in the appendix.
Inclusion criteria
Patients were invited to participate if they were over 20 years of age and had a documented history of chronic HF defined according to the European Society of Cardiology criteria.8 Participants were also required to have documented evidence of impaired left ventricular systolic function, as demonstrated by an ejection fraction 40% on transthoracic echocardiography or other imaging technique on the index admission or within the preceding 6 months.
Exclusion criteria
Patients with a planned discharge within 24 h of admission were not enrolled into the study. Patients with an investigator-defined history of acute coronary syndrome or cardiogenic shock within 1 month prior to the index admission were excluded, as were patients who had received a new prescription for potentially nephrotoxic drugs within 2 days prior to admission. Patients presenting with severe aortic stenosis, valvular disease anticipated to require surgery within 6 months, ‘high output’ cardiac failure, or those undergoing chronic renal replacement therapy or cancer chemotherapy, were also excluded.
Baseline data
Baseline information was collected on demographics, medical history, physical examination, medication use, and biochemical parameters (including serum creatinine) at the time of admission. Loop diuretic dose was calculated as ‘furosemide equivalent’ for the few patients who were not given furosemide: bumetanide 1 mg or torasemide 10 mg was considered equivalent to furosemide 40 mg, based on the equivalence stated in the European Society of Cardiology guidelines for the diagnosis and treatment of chronic HF.8
Adverse events and procedures (such as cardiac catheterization) occurring during the hospitalization were also recorded. Major complications were defined as circulatory shock, cardiac arrest, clinically significant hypotension, systemic sepsis, and acute coronary syndromes. These data were collected using a standardized data abstraction form. The research nurses working at each of the study centres were specifically trained in the extraction process.
Determination of WRF
WRF was defined as an increase in serum creatinine of >26 µmol/L (0.3 mg/dL) from baseline during the index hospitalization up to day 15. Serial measurements of serum creatinine were made on days 2 and 3 of admission, then every other day until day 15 or hospital discharge (whichever came sooner). Creatinine clearance was estimated for each patient according to the Cockcroft–Gault equation9 and the Modification of Diet in Renal Disease (MDRD) formula.10
Endpoints
All-cause mortality during the initial hospitalization and within 30±7 days and 180±7 days of the index hospitalization were recorded. The date and cause of subsequent hospital re-admissions were also recorded.
Sample size
Assuming an expected frequency of WRF during hospital admission for decompensated HF of 25%, 300 patients were required to give a two-sided 95% CI for the frequency of WRF extending 5% from the observed proportion. Also, assuming an overall event rate of re-hospitalization or death of 50% by 6 months in the sample population, a sample size of 300 would provide 80% power to detect a 25% change in the event rate from the whole population to patients with WRF.
Statistical analyses
The proportion of patients developing WRF in the study population was expressed as a prevalence rate with a 95% CI. Continuous variables were described using mean and SD for those with a normal distribution and by median and 90% range for non-normally distributed variables. Associations between WRF and continuous variables were analysed using Student's t-test for normal data and Mann–Whitney U test for non-normal data. Associations with categorical variables were analysed using 
2 analysis and Fisher's exact test.
Forward stepwise logistic regression analysis was used to identify variables independently associated with WRF during admission, for patients without a major complication and for the whole cohort. The likelihood ratio test was performed at each step to identify the most parsimonious model predictive of the development of WRF. Co-variates with a P<0.10 on univariable analysis were taken into multivariable analysis, but only retained at an exit significance value of P<0.05. All tests were two-sided. We examined the strength and shape of the relationship of continuous variables with the log odds of WRF using cubic spline plots.11 The proportion of patients with missing data for variables entered into the model was low, but in order to minimize bias, missing values for these variables were calculated by imputation,11,12 based on the correlation between each variable with missing values and all other variables. Imputation was performed using the regression method available in STATATM 7.0. The final model was internally validated by bootstrapping, by sampling with replacement for 2000 iterations. The ability of the model to discriminate between patients who did and did not develop WRF was estimated using the concordance index (C-statistic), where the value of 0.5 indicates no predictive discrimination and a value of 1.0 indicates perfect separation of patients who developed WRF from those who did not, identical for this study to the area under the receiver operating characteristics (ROC) curve.13 Statistical analyses were performed with STATA 7.0 (Stat Corp., College Station, TX, USA) and SPSSTM 11.5 (SPSS Inc., Chicago, IL, USA).
Ethical considerations
The protocol was approved by the Institutional Ethics Committee at each participating centre and was fully compliant with the Declaration of Helsinki. Fully informed consent was obtained in writing from each patient before entry into the study.
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Results |
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Patient characteristics
The study population consisted of 299 consecutive patients who fulfilled the study criteria and who gave consent. The baseline characteristics are shown in Table 1. The mean age of the cohort was 68.0 (SD 11.6) years, with 15% of the participants over the age of 80. The majority (74%) was males, and almost all were Caucasian (99%). This reflects the characteristics of the patient populations at the centres enrolled in the study. Around half had a history of prior myocardial infarction, and a history of hypertension, atrial fibrillation, or peripheral arterial disease was common. The mean ejection fraction was 27.7% (SD 7.6%). On admission, 87% of patients were in NYHA class III or IV. The prior use of diuretics, angiotensin converting enzyme (ACE)-inhibitors, and beta-blockers was high (88, 89, and 42%, respectively). Twenty-four patients (8%) were only given torasemide, and eight patients (3%) were only given bumetanide. The median serum creatinine on admission was 127 µmol/L (1.42 mg/dL), with a mean (SD) of 141 µmol/L (68 µmol/L) or 1.58 mg/dL (0.76 mg/dL).
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Prevalence of WRF and associated clinical features
WRF developed in 98 patients [33% (95% CI 27–38%)]. The median time from admission to the development of WRF in the whole group was 4 days (90% range 1–12 days). Most of the patients who developed WRF (70%) did so within 7 days of hospitalization. If the 51 patients who developed major complications (cardiac arrest, shock, clinically significant hypotension, sepsis, acute coronary syndrome) are removed from the analysis, the proportion of patients developing WRF was similar [72/248; 29% (95% CI 26–32%)], as was the median time to WRF [4 days (90% range 1–11 days)].
On univariable analysis of those patients who did not develop a major complication (n=248), WRF was associated with insulin-treated diabetes (P=0.01), pulmonary oedema on initial chest radiograph (P=0.02), and a higher serum creatinine on admission (P<0.001), but not with NYHA functional class or ejection fraction (Table 2). A history of atrial fibrillation was more commonly reported among those without WRF than in those with WRF (44 vs. 25%, P=0.005). On multivariable analysis (using imputation for missing values), admission serum creatinine, atrial fibrillation, and pulmonary oedema were independently associated with WRF (Table 3). The area under the ROC curve for the bootstrapped model, equivalent to the C-statistic, was 0.72 for the multivariable model suggesting good discrimination between those who did and who did not develop WRF. When the multivariable analysis was performed on the whole cohort, thereby including those patients who experienced a major in-hospital complication, the results were broadly similar, but insulin-treated diabetes remained in the final model (Table 3). The discriminatory power of the model was poorer, with a C-statistic of 0.66.
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Concomitant drug therapy at the time of the index hospitalization was similar in patients who developed WRF and those who did not: ACE-inhibitors 75 vs. 78%; beta-blockers 62% in both groups; digoxin, 40 vs. 41%; NSAIDs 3% in both groups.
Patients who developed WRF were taking a similar dose of loop diuretic on admission (median 40 mg of furosemide in both groups, P=0.48). The maximal loop diuretic dose during the index hospitalization was somewhat higher in those who developed WRF than in those who did not (median 80 mg in both groups, but upper 90% range of 300 mg in WRF group compared with 250 mg in non-WRF group, P=0.04). Adding the peak furosemide dose to the multivariable model shown in Table 3 did not change the measures of association for serum creatinine, atrial fibrillation, or pulmonary oedema, and the peak furosemide dose itself was not statistically significant (P=0.13).
WRF and mortality
Follow-up was 98% complete at 30 days, and 95% complete at 180 days (6 months). During the 6-month period after the index admission, 61 deaths were recorded (21% of cohort). Those with WRF during the index admission experienced a significantly higher mortality, particularly during the early period. During initial hospitalization, the number of deaths among those with WRF was 12 (12%) rising to 14 (15%) by 30 days and 26 (28%) by 6 months. The comparative figures for those who did not develop WRF were 3 (2%), 9 (5%), and 35 (18%) (Table 4). However, just over one-third of the deaths (21/61) occurred in those with major complications, and if the analysis is confined to the 248 patients without these major complications, those with WRF did not have a statistically significant higher mortality than those who did not develop WRF, either during the initial hospitalization or out to 6 months (Table 4).
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WRF and length of hospital stay
The median length of stay during the index hospitalization was 10 days (90% range 4–38 days) for the whole group of 299 patients. Patients with WRF remained in hospital 4 days longer than those without WRF [13 days (90% range 4.9–44.0) vs. 9 days (4–31.2), P<0.001]. Excluding those patients with complications, the median length of stay was 9 days (90% range 4–34 days), with patients with WRF remaining in hospital 2 days longer than those without WRF [median 11 days (90% range 4–41) vs. median 9 days (4–34), P=0.006].
WRF and risk of re-hospitalization
Up to 30 days after the index admission, 59 patients were re-admitted to hospital. This rose to 128 by 6 months. Worsening HF was the reason for re-admission for 
50% of these patients at both 30 days (29/59) and 6 months (67/128) follow-up.
Excluding patients with a major complication during admission, there was no difference in re-hospitalization rate in those with WRF at either 30 or 180 days compared with those who did not develop WRF [relative risk 1.05 (0.55–2.01), P=0.87 and 1.12 (0.74–1.70), P=0.60, respectively].
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Discussion |
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This study is the first prospective multicentre study to report the prevalence of WRF in well-characterized patients admitted to hospital with decompensated HF due to left ventricular systolic dysfunction. The principal finding of our study was that one-third of all patients hospitalized for decompensated HF developed WRF during that hospitalization. Even excluding patients who had a major complication likely to impact on renal function (circulatory shock, hypotension, cardiac arrest, sepsis, acute coronary syndrome), the prevalence was 29%, similar to reports based on two retrospective case note reviews in the USA.1,6 A higher serum creatinine concentration at the time of admission and pulmonary oedema on the admission chest radiograph were independently associated with an increased risk of developing WRF. Also, WRF was associated with a clinically and statistically significant longer length of hospital stay.
Only 70% of all patients who developed WRF did so within 7 days of hospitalization—rather lower than that reported from the USA.1,6,7 This may reflect differences in patient characteristics or therapeutic management.
In agreement with previous studies,1,6,7 we report that serum creatinine concentration on admission is one of the strongest independent predictors of WRF in patients with decompensated HF. Such a measurement is easily and routinely available in clinical practice, unlike the measurement of creatinine clearance which in theory provides a more accurate measure of renal glomerular function. Estimation of creatinine clearance using the Cockcroft–Gault equation can be made,9 although this may not be accurate in patients with marked (and fluctuating) fluid retention. The Cockcroft–Gault equation was derived from hospitalized adult males, with the authors recommending a notional 15% reduction for females, and cautioning about its use in patients with muscle wasting, rapidly changing renal function, and excess body fat or fluid. Such factors may explain why creatinine clearance estimated using this equation based on admission weight and serum creatinine was not strongly associated with the risk of development of WRF in this study. Caution has been recently raised on the use of formulas estimating renal function in HF patients,14 although the MDRD equation10 appears more valid than the Cockcroft–Gault equation.15 In any case, both formulas produced similar results in our analyses.
Diabetes mellitus has been reported to be strongly associated with the risk of WRF in patients with decompensated HF.1,6,7 The mechanism is likely to be due to both macro- and micro-vascular dysfunction.16
There is a spectrum of severity of the clinical presentation of acutely decompensated HF, with pulmonary oedema being towards the more severe end of the spectrum.17 In the Killip classification, originally developed in the context of acute myocardial infarction, pulmonary oedema is graded as class III, with the only more severe category being cardiogenic shock.18 In our data set, patients who presented with pulmonary oedema were more than three times more likely to develop WRF than those who had a less severe clinical presentation of decompensation.
A history of atrial fibrillation appeared to confer some protection from WRF in our study. This has not been reported previously. The effect does not disappear on multivariable analysis. This observation may be due to chance, or be confounded by underyling cardiac disease severity or co-morbidity, which may not have been fully taken into account in the data collected in this study.
Patients with WRF received higher doses of loop diuretics during hospitalization than those who did not develop WRF, as has been reported previously.7 Diuretics aid relief of congestion and facilitate a return to the euvolaemic state but at the expense of increasing neurohormonal activation by plasma renin–angiotensin–aldosterone, norepinephrine, and the sympathetic nervous system,19 which in turn may decrease renal glomerular function. The poorer the renal glomerular function, the higher the dose of diuretic required to relieve congestion, and this may lead to a vicious cycle of decreasing renal function and higher doses of diuretics. It is also possible that a higher dose of diuretic is merely a marker of the therapeutic decision-making in response to deteriorating cardiac output and worsening fluid retention as the underlying HF deteriorates.
Even small deteriorations in renal function have been reported to be associated with increased all-cause mortality in patients with chronic HF, independently of age, left ventricular systolic function, and the presence of diabetes mellitus.4,5 The in-hospital and 30-day mortality for those with WRF was somewhat higher in our series than in these reports, and the risk of mortality associated with WRF was higher for the index admission and at 30 days.1,6,7 This is similar to reports from other surveys4 and from clinical trials of drug therapy in severe HF.3 However, if the patients who experienced a major complication are removed from the analysis, the impact of WRF on mortality largely disappears. It is possible that the association is at least partially explained by the impact of the major complication on both mortality risk and renal function—in other words, confounding rather than a direct causal association. Also, deterioration in renal function limits the administration of therapies known to prolong survival, such as ACE-inhibitors or spironolactone, prolongs in-hospital length of stay, and further exacerbates neurohormonal activation and presumably progression of the HF syndrome.
Increased length of hospital admission for patients with decompensated HF and WRF has been reported previously.1 Length of stay for all patients was longer in this European study than in US studies, reflecting different management strategies and health care pressures.20,21 This extended stay has major cost implications for the health care system: data from many European countries suggest that 60–70% of the total cost of managing HF relates to in-hospital costs.22 Even for those without major complications during admission, those with WRF had more prolonged admissions. It is likely that this relates to more time being required to optimize the fluid balance status of the patient. Efforts to preserve renal function during treatment of episodes of decompensation of HF may therefore have an impact on the total cost of managing HF, by reducing length of stay and accelerating optimization of therapy.
Limitations of study
Our study recruited patients from centres with an interest in Forman HF and may not be generalizable to all patients with decompensated HF. The multivariable model developed from this data set, and internally validated by bootstrapping, may not be as discriminatory in other patient populations. We cannot comment on ethnic differences in WRF as 99% of our population was Caucasian, reflecting the racial mix in the middle-aged and elderly population in Europe. We may have misclassified some individuals who only developed WRF after discharge from hospital, although this is likely to be a small number due to the prolonged period of inpatient observation for most patients.
Appendix
List of POSH Investigators
Finland: University Central Hospital, Helsinki, Finland (Professor Markku Nieminen, Dr Tiina Heliö); University Hospital, Kuopio, Finland (Associate Professor Sehto Lehto); France: Hopitaux de Paris, Groups Hospitalier Pitié-Salpétrière, Paris, France (Drs Richard Isnard and Francoise Pousset); CHU Nancy Brabois, Vandoeuvre-les-Nancy, France (Professor Yves Juilliere); Hôpital Guillaume et René Laënnec, Nantes, France (Professor Jean-Brieuc Bouhour); Germany: Martin Luther Universitat, Halle, Germany (Dr Mathias Rauchhaus); Herzzentrum, Ludwigshafen, Germany (Drs C Kilkowski and T Kleemann); Rotkreuzkrankenhaus, Munich, Germany (Professor Thomas von Arnim); Italy: Ospedale Generale, Pavia, Italy (Professor Luigi Tavazzi, Dr C Campana); Ospedali Riuniti, Bergamo, Italy (Dr Michele Senni, Dr Aurelia Grosu). Sweden: Malmo University Hospital, Malmo, Sweden (Dr Charles Cline); Switzerland: University Hospital, Zurich, Switzerland (Professor Ferenc Follath); The Netherlands: University Hospital, Gronigen, The Netherlands (Professor Dirk Jan van Veldhuisen); Medische Centrum, Alkmaar, The Netherlands (Dr Jan Hein Cornel); UK: Aberdeen Royal Infirmary, Aberdeen, UK (Dr Malcolm Metcalfe); Hillingdon Hospital, Middlesex, UK (Dr Simon Dubrey); Hull Royal Infirmary, Hull, UK (Professor John Cleland).
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The authors wish to thank the patients and investigators at each site and Biogen Idec, 14 Cambridge Center, Cambridge, MA, USA, for funding the costs of data collection.
Conflict of interest: B.T. is an employee of Biogen Idec and owns shares in the company.
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