© 2008 European Society of Cardiology
Acute heart failure in the emergency department: Short and long-term outcomes of elderly patients with heart failure
a Division of Cardiology, Department of Medicine University of Alberta Canada
b Canadian VIGOUR Center Canada
* Corresponding author. 2C2 Cardiology, University of Alberta, 8440-112 street, Edmonton, Alberta, Canada. Tel.: +1 780 407 8719; fax: +1 780 407 6452. E-mail address: justin.ezekowitz{at}ualberta.ca (J.A. Ezekowitz).
 |
Abstract |
|---|
 TopNotes Abstract 1. Introduction2. Methods3. Results4. Discussion5. Limitations6. ConclusionsAcknowledgmentsReferences |
|---|
Aims: Previous epidemiologic studies of acute heart failure (AHF) have involved patients admitted to hospital and fail to account for that unknown proportion discharged directly from the emergency department (ED). We examined discharge rates, and whether outcomes, including mortality, differed based on admission status in AHF.
Methods and results: This population-based cohort included all patients 
65 years presenting to an Alberta ED with HF (ICD9-CM 428.x; 1998 to 2001). Patients were either not admitted (Not-ADM) or directly admitted to hospital (ADM) and followed for one-year.
Of 10,415 AHF patients evaluated in the ED, 35% were Not-ADM whereas 65% were ADM. Thirty days after ED presentation the rates of death, re-ED or initial/re-hospitalisation were 3.3%, 44% and 19% for Not-ADM, and 10.9%, 33% and 21% for the ADM patients, respectively (all p<0.0001). At one-year, the rates of death, re-ED or initial/re-hospitalisation were 20%, 82% and 58% for Not-ADM, and 34%, 72% and 60% for ADM, respectively (all p<0.0001).
Conclusions: One third of AHF patients were not immediately admitted after an ED visit but most present again to the ED, two-thirds were hospitalised and 20% died within the first year. Our findings provide new impetus to undertake risk assessment and treatment strategies in the ED for AHF.
Key Words: Heart failure • Epidemiology • Survival
Received August 4, 2007; Revised November 30, 2007; Accepted January 24, 2008
|
1. Introduction |
|---|
|
TopNotesAbstract1. Introduction2. Methods3. Results4. Discussion5. Limitations6. ConclusionsAcknowledgmentsReferences |
|---|
Heart failure (HF) causes considerable morbidity and mortality and is responsible for a tremendous burden on the health care system worldwide. In 2003 in the US alone HF accounted for approximately 727,000 emergency department (ED) visits, 1 million hospital discharges and an estimated overall annual cost of $29 billion for 2006.[1,2] In addition to this, HF patients are at increased risk of mortality in the short-term. In the largest prospective cohort of hospitalised patients with acute heart failure (AHF), in-hospital mortality was 4% [3]; the Second EuroHeart Failure Survey had an in-hospital mortality rate of 6.7% [4]. Even if HF patients are discharged alive, they have a 7% to 16% rate of cardiovascular re-hospitalisation and a 45% rate of seeking emergency care by 30 days and a 32% mortality rate in the subsequent year [5].
Recent guidelines highlight the difficulty in characterizing and defining AHF as well as the paucity of information on outcomes of patients initially triaged in the ED [6-9]. All major HF registries have limited their enrolment to hospitalised patients, including the Acute Decompensated Heart Failure Registry (ADHERE), the Organized Program to Initiate Lifesaving Treatment in Hospitalised Patients with Heart Failure (OPTIMIZE-HF) and three European surveys [3,4,10,11]. Only two studies have identified HF patients in the ED [12,13]. In a study of 112 patients discharged from the ED after an episode of AHF, 61% were subsequently hospitalised, required a further ED visit or died within 3 months of their initial ED visit [12]. In another study involving a selected sample of US EDs, 2.9% of all ED visits were for AHF or pulmonary oedema, and 16% were admitted to the intensive care — little is known about the patients discharged directly from the ED [13].
To address this major public health issue, we studied a large cohort of patients presenting to the ED with AHF to describe: (1) the features of patients discharged from the ED; (2) their use of cardiovascular medications; and (3) their subsequent short- and long-term outcomes.
|
2. Methods |
|---|
|
TopNotesAbstract1. Introduction2. Methods3. Results4. Discussion5. Limitations6. ConclusionsAcknowledgmentsReferences |
|---|
2.1. Databases
The Alberta Chronic Heart Failure (ABCHF) database was created by linking five databases maintained by the Ministry of Health and Wellness in Alberta, Canada: (1) the Discharge Abstract Database, which records information (including dates, diagnoses and procedures) on all admissions to acute care facilities; (2) the Ambulatory Care Database, which tracks all visits to hospital-based physicians' offices and all emergency departments;(3) the Physician Claims Database, which tracks all physician claims for outpatient services (by diagnostic code); (4) the Alberta Health Care Insurance Registry, which tracks the vital status of all 3.1 million Albertans; and (5) the Blue Cross Medication Database which includes medication data (which is entered electronically when the prescription is filled on a single system throughout the province based on the nationally assigned Drug identification number) on all patients over 65 years [5,14]. Each individual has a scrambled unique personal identifier by which patient information can be tracked through each of the databases. This database was further linked with the Statistics Canada 2000 neighbourhood income data, assigning a median neighbourhood household income to patients based on their recorded place of residence.
2.2. Data elements and variable definitions
The ABCHF database was used to identify patients who had been seen at any of the 107 Alberta emergency departments at least once for a cardiovascular cause (n=104,931) between April 1, 1998, and March 31, 2001. From this, 12,484 patients with a most responsible ED diagnosis of HF (International Classification of Diseases, 9th revision clinical modification [ICD-9-CM] code 428.x, 404.(01, 03, 11,13, 91, 93), 402.(01,11,91) were identified. After removing patients <65 years (16%) and 0.4% that died in the ED, the final cohort consisted of 10,415 patients. Patients were defined as either admitted to hospital (ADM) or discharged directly (not admitted [Not-ADM]), by identifying an immediate hospital admission following the ED visit; admission included up to 48 h from entry into the ED to allow for interhospital transfers or delays in admission. All patients were followed for one-year. As a sensitivity analysis, a cohort of incident cases was established by instituting a one-year washout period, i.e., excluding patients admitted with a principal diagnosis of HF in the preceding year; the rate of ED discharge, age, gender, comorbidity and one-year outcomes were similar to the overall cohort.
Identification of comorbidities was done utilizing the ICD-9-CM codes at the incident or during subsequent hospitalisations and supplemented by a search in the prior year for comorbidity in the ambulatory care database in order to reduce bias towards the hospitalised patients having more identified codes since only six secondary codes are available in emergency diagnostic coding. No significant differences in outcomes were noted between these cohorts. The use of discharge coding to identify cases and comorbidities, and hospital and specialist information have been described elsewhere [5,14]. To address misclassification bias for the ED coding of heart failure, a random 30% sample (483 charts) from the local health region (serving a catchment area of 1 million individuals, 6 hospitals and their EDs) with a primary diagnosis from the ED by ICD-10 I-50 code were reviewed by trained abstracters using standardized definitions of which 448 (93%) met pre-specified diagnostic criteria for heart failure (based on the Framingham criteria, and due to limited documentation and observation time in the ED, the physicians final diagnosis was also utilized).
Cardiovascular medications were defined as angiotensin converting enzyme inhibitors (ACE), beta-blockers, digoxin and spironolactone, based on the 2001 heart failure guidelines for systolic dysfunction, recognizing that some patients would have a contraindication or diastolic heart failure (for whom there are no proven efficacious medications) [15,16]. Medication usage was defined by identifying medication claims 90 days prior to the ED visit. A window of 90 days (and for sensitivity analysis up to 120 days; no significant difference was seen in prescription rates) following the hospital or ED discharge was used to identify prescriptions that could be linked to the ED or hospital visit.
Hospital-specific variables were created by identifying clusters of hospitals based on the number of available acute care beds (median 28, IQR 20 to 75), the average annual ED visits (median 2509, IQR 1221 to 4438) and the annual cardiovascular (CV) ED visits (median 719, IQR 354 to 1326). A series of multivariate normal models were fit to the hospital-level descriptors and three clusters were identified, representing small (n=56), medium (n=37) and large (n=14) hospital-based services.
2.3. Outcomes
The primary endpoint was short-term (30-day) and long-term (one-year) mortality reflecting the potential early hazard as well as the long-term complications. Repeat or first hospitalisation was examined for all-cause hospitalisation, and then as a sensitivity analysis, only CV or HF hospitalisations (any of ICD-9-CM codes 390-459 as the most responsible diagnosis) were examined. This process was repeated for both 30-day and one-year repeat ED visits. Location of death was divided into ED, hospital or out-of-hospital.
2.4. Statistical analysis
Categorical data were summarized in terms of percentages and group differences tested using the 
2 test; continuous variables were summarized in terms of medians and interquartile ranges and group differences tested using the appropriate non-parametric tests. Kaplan-Meier analysis was used to examine unadjusted survival patterns across patient groups. Due to the competing risk of hospitalisation with death, the Kaplan-Meier for hospitalisation was adjusted for the cumulative probability of re-hospitalisation or first hospitalisation conditional on being alive [17]. To adjust for differences in baseline variables including patient demographics, baseline characteristics in Table 1, neighbourhood income, seasonality, physician specialty and hospital-specific variables mentioned above, multivariable logistic regression was performed using a stepwise method for predicting admission to hospital, entering all variables with p<0.15 on univariable analysis into the model. A stepwise Cox proportional hazards regression was used to estimate adjusted hazard ratios for 30-day and one-year outcomes between patients Not-ADM vs. ADM. Proportionality assumptions for the Cox model were tested with both the goodness-of-fit test and log-minus-log test and were met for all analyses. All tests were two-sided, with the level of significance set at p<0.05, and performed using the SAS V9.1 (Cary, NC).
|
|
3. Results |
|---|
|
TopNotesAbstract1. Introduction2. Methods3. Results4. Discussion5. Limitations6. ConclusionsAcknowledgmentsReferences |
|---|
Thirty-five percent of patients were discharged directly from the ED, and 65% admitted to the hospital. Baseline patient characteristics, medications and hospital characteristics by admission status are shown in Table 1. ED discharged patients were younger, more frequently male and more likely to have a previous malignancy, they were less likely to have atrial fibrillation, diabetes or pulmonary disease. Prior medication use was similar between the two groups, with trends towards more ACE or ARB, diuretics, spironolactone or statin prescriptions and fewer digoxin or nitrate prescriptions in the Not-ADM patients.
After the index ED visit, ADM patients were more likely to have ACE inhibitors or beta-blockers initiated and less likely to have all four cardiovascular medications discontinued than the Not-ADM patients (all p<0.001; Table 2). ED rates of hyperkalemia, digoxin toxicity or renal failure were 0.4% (p=0.03), 1.2% (p=0.11), and 0.05% (p=0.66), respectively.
|
3.1. Factors associated with immediate discharge from the ED
Several variables predicted discharge from the ED, including younger age and male gender; several key comorbidities predicted admission (including atrial fibrillation, diabetes and pulmonary disease; Table 4). The use of certain medications were associated with discharge, including ACE, beta-blockers, digoxin, spironolactone, warfarin and statins, whereas nitrates and sulfonylureas were more commonly associated with ADM patients. Being seen in a small or medium sized hospital (compared to large hospitals) was associated with ED discharge.
3.2. Subsequent ED, hospitalisation and mortality outcomes
Patients who were Not-ADM had higher rates of re-ED (44% vs. 33%, p<0.0001, Fig. 1A) but lower rates of re-hospitalisation (19% vs. 21%, p<0.0001, Fig. 1B) in the next 30 days compared to the ADM patients (Table 3). In the Not-ADM patients, the median time to first admission was 71 days (IQR 19 to 167 days). The 30-day re-hospitalisation rate for heart failure (expressed as percent of all-cause hospitalisations) as a principal diagnosis was not significantly different (Not-ADM 14% vs. ADM 15%, p=0.42) nor was any cardiovascular admission (Not-ADM 51% vs. ADM 51%, p=0.94). The 1-year re-hospitalisation rate for heart failure (expressed as percent of all-cause hospitalisations) as a principal diagnosis was significantly different (Not-ADM 20.0% vs. ADM 22.8%, p=0.01) however any cardiovascular admission (Not-ADM 56.9% vs. ADM 59.1%, p=0.096) trended towards statistical significance.
|
|
The 30-day mortality rate was 3.3% for patients Not-ADM, and 10.9% for those ADM (p<0.0001, Fig. 1c) and the one-year mortality rates were 20% and 34%, respectively (p<0.0001). Of the Not-ADM patients that died, 31% died outside the hospital; in the first 30 days after index ED visit, 11% of deaths occurred outside of hospital. In a sensitivity analysis regarding age, the patients in the lowest quartile (n=2602, <74 years of age) were compared to the rest of the patients (n=7813): unadjusted 30-day mortality was significantly different (5.9% vs. 9.0%, p<0.0001) as was one-year mortality (21.1% vs. 31.8%, p<0.001).
3.3. Factors associated with mortality or re-hospitalisation
Among patients Not-ADM, predictors of hospitalisation in the next 30 days included the presence of ischaemic heart disease, pulmonary disease, anaemia and malignancy whereas warfarin was associated with a lower risk for hospitalisation (Table 4). Patients with atrial fibrillation were all admitted in the next 30 days to hospital so a hazard ratio could not be estimated. Compared to a large hospital, being seen in a smaller or medium sized hospital predicted subsequent 30-day hospitalisation. Predictors of increased 30-day mortality in these patients was the presence of atrial fibrillation and malignancy, whereas being on ACE, ARB, a beta-blocker or warfarin was associated with a lower mortality.
|
For all patients, predictors of increased one-year mortality were age, male gender, ischaemic heart disease, peripheral vascular, pulmonary or renal disease, anaemia or a malignancy; whereas baseline prescriptions for ACE, ARB, beta-blockers, spironolactone, statins, calcium channel blockers or warfarin were associated with a lower mortality rate. Being admitted at the index ED visit was also associated with increased mortality at one-year.
|
4. Discussion |
|---|
|
TopNotesAbstract1. Introduction2. Methods3. Results4. Discussion5. Limitations6. ConclusionsAcknowledgmentsReferences |
|---|
In this large, unique population-based analysis of elderly patients presenting to the emergency department for heart failure, we describe the characteristics and outcomes of a previously unexamined cohort. Our three principal novel findings are: (1) 35% of patients are discharged from the ED after a visit for acute heart failure; (2) this group has a high likelihood of attending the ED or being admitted in the next year; and (3) these patients are at risk for short-term (3.3% at 30 days) and long-term mortality (20% at one-year).
This population-level analysis was performed by linking information from multiple databases in order to identify a broad range of patient and process of care characteristics associated with admission from the ED after a visit for AHF. In a survey of selected hospitals conducted as part of the National Hospital and Ambulatory Medical Care Survey (NHAMCS; a rotating 4 week survey of 
500 US hospitals of differing geographic regions), 73% of patients presenting with HF or pulmonary oedema were admitted directly to hospital [13]. The present study adds to the NHAMCS by providing both short and long-term clinical outcomes and also provides a description and adjustment for baseline and subsequent medications, prior diagnoses, socioeconomic status, seasonality and hospital-level characteristics. Our administrative data did not allow adjustment for physiological (e.g. blood pressure, heart rate), electrocardiographic, or laboratory data (e.g. haemoglobin, creatinine) recently shown to be predictors of in-hospital mortality [3]. However, variables such as hospital size (clustered by the number of acute care beds and ED visits) were significant predictors of discharge from the ED. We surmise that smaller hospitals may have elected to diagnose and treat a patient directly in the ED, avoiding hospital admission possibly secondary to resource issues (e.g. geographic isolation, available monitored beds, patient preferences). While the current analysis cannot directly address the basis for this finding, nor necessarily apply to other populations outside the province of Alberta, Canada, it should be considered hypothesis generating. We believe however that it will be of some interest to hospital planners as well as those developing risk models in acute heart failure.
It is challenging to risk-stratify HF patients discharged from an ED setting and provide a timely and appropriate outpatient assessment. Rame and colleagues studied 112 ED discharged HF patients seen at an urban county hospital ED, 61% "failed outpatient therapy" (37 were seen again for AHF, 30 were hospitalised and 1 death occurred) all occurring a median of 30 days after the index ED visit [12]. The timing of follow-up care is critical as it allows for a window of opportunity during which patients could be seen and potentially avert an ED visit or admission to hospital — our 30-day re-ED rate of 44% indicates that there is substantial room for improvement. A recent consensus panel has identified when HF patients should be seen based upon their acuity: although based only on expert opinion these appear to have reasonable and potentially achievable benchmarks [18]. Given the broad risk categories of patients presenting to community, tertiary and academic centres with AHF, more clinical information is needed to further refine models for prediction in heart failure; inclusion of the one-third of AHF patients not admitted would further enhance the applicability to clinicians.
Despite the health burden of acute heart failure, no tools exist in order to risk-stratify patients in the ED. Other acute cardiovascular diseases, such as acute coronary syndromes, have established practical, widely used diagnostic and risk stratification tools [19] and established acute care therapies. However, AHF has a mortality rate of 3.3% at 30 days for ED discharged patients in our dataset, exceeding that of patients in with ST-elevation myocardial infarction [20]. Despite this, 35% of patients are discharged home from the ED. Difficulty in the diagnosis, lack of proven acute care therapies, and practice patterns that limit involvement from specialty services or fail to emphasize continuity or collaborative care models may all contribute to this care gap. Furthermore, there is likely limited recognition of the substantial risk of these patients, despite many well validated tools to aid risk stratification of patients once admitted [3,21] or as outpatients [22].
Did the high-risk patients in our study get admitted once heart failure was identified in the ED? Although we do not have all the clinical or laboratory data bearing on this question, several inferences can be made. First, the mortality rate was substantially lower in the subsequent 30 days for those patients discharged directly from the ED as compared to those admitted. It is noteworthy that 11% of the deaths in ED discharged patients occurred outside of hospital within 30 days of ED evaluation; while it is not possible to determine if these outcomes could have been avoided by hospitalisation, there are potential implications for patients and physicians regarding the scrutiny of outpatient follow up. Over half of the hospitalisations in the following year were for a cardiovascular cause and one fifth for heart failure — while there was a trend towards a difference at one-year, this highlights the risk of these patients and the need for both overall cardiovascular and non-cardiovascular risk. Secondly, the characteristics of discharge from the ED included younger age and less comorbidity, indicating that while physicians in the ED may be effectively risk stratifying patients they may still underestimate their level of absolute risk. For example, patients on more cardiovascular medications were more likely to be sent home from the ED, and patients on an ACE inhibitor, ARB, beta-blocker or warfarin were less likely to die in the next 30-days. The timing of the association of a lower mortality risk with these medications is consistent with a systematic review of clinical trials for ACE inhibitors initiated for patients hospitalised with left ventricular dysfunction with or without myocardial infarction [23], and a clinical trial of beta-blockers in high-risk hospitalised heart failure patients [24].
Our patient cohort exhibited a high usage of cardiovascular medications considering its inclusion of data from patients as early as 1999. Nearly 88% were on either an ACE inhibitor or an angiotensin receptor blocker, and almost 50% were on a beta-blocker. In a recent survey of 3580 patients from 133 European centres from 2004 to 2005, only 63% of AHF patients were on an ACE or ARB, and on 43% were on a beta-blocker [4]. We demonstrated that one modest incremental effect of admission was the net addition of a cardiovascular medication and more ED discharge patients had these same medications stopped. Because we could not identify dose changes, contraindications, compliance or side-effects, causality cannot be inferred from our data and the usual caution applies to our study and others using administrative data [25]. However, low rates of hyperkalaemia (only 42 patients) and other adverse events were identified and fewer patients were on cardiovascular medications in the subsequent 90-days if they were discharged directly from the ED.
|
5. Limitations |
|---|
|
TopNotesAbstract1. Introduction2. Methods3. Results4. Discussion5. Limitations6. ConclusionsAcknowledgmentsReferences |
|---|
Certain limitations of administrative data deserve consideration. The retrospective methodology of the validation cohort did not allow for validation of symptoms that could otherwise have been assigned to another disease, for example, chronic obstructive pulmonary disease. In addition, due to limited documentation in the ED, criteria such as the Framingham criteria could not be equally applied to both ED discharged and hospitalised HF patients, therefore reliance on the physician's most responsible diagnosis was necessary in the validation cohort. This is an important area for future research. In addition, Alberta constitutes approximately 10% of Canada's population, so the results may not apply to the rest of Canada with respect to baseline demographics, treatments or outcomes. However, Alberta's 90 day and 1-year hospital readmission rate and index hospitalisation mortality rate are similar to the national average [26].
|
6. Conclusions |
|---|
|
TopNotesAbstract1. Introduction2. Methods3. Results4. Discussion5. Limitations6. ConclusionsAcknowledgmentsReferences |
|---|
One third of patients seen in the emergency department for heart failure are discharged; their subsequent ED use and need for hospitalisation is substantial. This finding, coupled with evidence of an increased early and late mortality rate, indicates that greater attention to this key population would be worthwhile with particular emphasis on better tools for risk stratification, treatment and follow-up.
|
Acknowledgments |
|---|
|
TopNotesAbstract1. Introduction2. Methods3. Results4. Discussion5. Limitations6. ConclusionsAcknowledgmentsReferences |
|---|
We thank Dr. Wei-Ching Chang for statistical support, Dr. Ross Tsuyuki for information on the validation cohort and Dr. Finlay McAlister for review of the manuscript. None of the authors have a conflict of interest to disclose. Although the study is based in part on data provided by Alberta Health and Wellness, the interpretation and conclusions contained herein are those of the researchers and do no necessarily represent the views of the Government of Alberta. The authors had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Neither the Government nor Alberta Health and Wellness express any opinion in relation to this study.
|
Notes |
|---|
|
TopNotesAbstract1. Introduction2. Methods3. Results4. Discussion5. Limitations6. ConclusionsAcknowledgmentsReferences |
|---|
1 Justin A.Ezekowitz and Padma Kaul are supported by the Canadian Institute of Health Research.
|
References |
|---|
|
TopNotesAbstract1. Introduction2. Methods3. Results4. Discussion5. Limitations6. ConclusionsAcknowledgmentsReferences |
|---|
- Thom T., Haase N., Rosamond W., et al. Heart disease and stroke statistics — 2006 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation (2006) 113(6):e85–e151.
[Free Full Text] - Schappert S.M., Burt C.W. Ambulatory care visits to physician offices, hospital outpatient departments, and emergency departments: United States, 2001-02. Vital Health Stat (2006) 13(159):1–66.
- Fonarow G.C., Adams K.F. Jr., Abraham W.T., Yancy C.W., Boscardin W.J. Risk stratification for in-hospital mortality in acutely decompensated heart failure: classification and regression tree analysis. JAMA (2005) 293(5):572–580.
[Abstract/Free Full Text] - Nieminen M.S., Brutsaert D., Dickstein K., et al. EuroHeart Failure Survey II (EHFS II): a survey on hospitalized acute heart failure patients: description of population. Eur Heart J (2006) 27(22):2725–2736.
[Abstract/Free Full Text] - Ezekowitz J.A., van W.C., McAlister F.A., Armstrong P.W., Kaul P. Impact of specialist follow-up in outpatients with congestive heart failure. CMAJ (2005) 172(2):189–194.
[Abstract/Free Full Text] - Heart Failure Society Of America. HFSA 2006 comprehensive heart failure practice guideline. J Card Fail (2006) 12(1):e1–e2.[CrossRef][Medline]
- Arnold J.M., Liu P., Demers C., et al. Canadian Cardiovascular Society consensus conference recommendations on heart failure 2006: diagnosis and management. Can J Cardiol (2006) 22(1):23–45.[Web of Science][Medline]
- Hunt S.A., Abraham W.T., Chin M.H., et al. ACC/AHA 2005 guideline update for the diagnosis and management of chronic heart failure in the adult: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines (writing committee to update the 2001 guidelines for the evaluation and management of heart failure). J Am Coll Cardiol (2005) 46:e1–e82.
[Free Full Text] - Nieminen M.S., Bohm M., Cowie M.R., et al. Executive summary of the guidelines on the diagnosis and treatment of acute heart failure: the Task Force on Acute Heart Failure of the European Society of Cardiology. Eur Heart J (2005) 26(4):384–416.
[Free Full Text] - Cleland J.G.F., et alfor the Study Group on Diagnosis of the Working Group on Heart Failure of the European Society of Cardiology. The EuroHeart Failure survey programme — a survey on the quality of care among patients with heart failure in Europe: Part 1: patient characteristics and diagnosis. Eur Heart J (2003) 24(5):442–463.
[Abstract/Free Full Text] - Komajda M., Follath F., et alThe Study Group of Diagnosis of the Working Group on Heart Failure of the European Society of Cardiology. The EuroHeart Failure Survey programme — a survey on the quality of care among patients with heart failure in Europe: Part 2: treatment. Eur Heart J (2003) 24(5):464–474.
[Abstract/Free Full Text] - Rame J.E., Sheffield M.A., Dries D.L., et al. Outcomes after emergency department discharge with a primary diagnosis of heart failure. Am Heart J (2001) 142(4):714–719.[CrossRef][Web of Science][Medline]
- Hugli O., Braun J.E., Kim S., Pelletier A.J., Camargo C.A. Jr. United States emergency department visits for acute decompensated heart failure, 1992 to 2001. Am J Cardiol (2005) 96(11):1537–1542.[CrossRef][Web of Science][Medline]
- Chang W.C., Kaul P., Westerhout C.M., et al. Impact of sex on long-term mortality from acute myocardial infarction vs unstable angina. Arch Intern Med (2003) 163(20):2476–2484.
[Abstract/Free Full Text] - Liu P., Arnold M., Belenkie I., et al. The 2001 Canadian Cardiovascular Society consensus guideline update for the management and prevention of heart failure. Can J Cardiol (2001) 17(Suppl_E):5E–25E.[Medline]
- Hunt S.A., Baker D.W., Chin M.H., et al. ACC/AHA guidelines for the evaluation and management of chronic heart failure in the adult: executive summary a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee to Revise the 1995 Guidelines for the Evaluation and Management of Heart Failure). Circulation (2001) 104(24):2996.
[Free Full Text] - Gray R.J. A class of K-sample tests for comparing the cumulative incidence of a competing risk. Ann Stat (1988) 16(3):1141–1154.[CrossRef][Web of Science]
- Ross H., Howlett J., Arnold J.M., et al. Treating the right patient at the right time: access to heart failure care. Can J Cardiol (2006) 22(9):749–754.[Web of Science][Medline]
- Antman E.M., Cohen M., Bernink P.J., et al. The TIMI risk score for unstable angina/non-ST elevation MI: a method for prognostication and therapeutic decision making. JAMA (2000) 284(7):835–842.
[Abstract/Free Full Text] - Steg P.G., Lopez-Sendon J., Lopez de S.E., et al. External validity of clinical trials in acute myocardial infarction. Arch Intern Med (2007) 167(1):68–73.
[Abstract/Free Full Text] - Lee D.S., Austin P.C., Rouleau J.L., Liu P.P., Naimark D., Tu J.V. Predicting mortality among patients hospitalized for heart failure: derivation and validation of a clinical model. JAMA (2003) 290(19):2581–2587.
[Abstract/Free Full Text] - Levy W.C., Mozaffarian D., Linker D.T., et al. The Seattle Heart Failure Model: prediction of survival in heart failure. Circulation (2006) 113(11):1424–1433.
[Abstract/Free Full Text] - Flather M.D., Yusuf S., Kober L., et al. Long-term ACE-inhibitor therapy in patients with heart failure or left-ventricular dysfunction: a systematic overview of data from individual patients. Lancet (2000) 355(9215):1575–1581.[CrossRef][Web of Science][Medline]
- Krum H., Roecker E.B., Mohacsi P., et al. Effects of initiating carvedilol in patients with severe chronic heart failure: results from the COPERNICUS study. JAMA (2003) 289(6):712–718.
[Abstract/Free Full Text] - Juurlink D.N., Mamdani M.M., Lee D.S., et al. Rates of hyperkalemia after publication of the Randomized Aldactone Evaluation Study. N Engl J Med (2004) 351(6):543–551.
[Abstract/Free Full Text] - Lee D.S., Johansen H., Gong Y., Hall R.E., Tu J.V., Cox J.L. Regional outcomes of heart failure in Canada. Can J Cardiol (2004) 20(6):599–607.[Web of Science][Medline]
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  J. A. Ezekowitz, P. Kaul, J. A. Bakal, P. W. Armstrong, R. C. Welsh, and F. A. McAlister Declining in-hospital mortality and increasing heart failure incidence in elderly patients with first myocardial infarction. J. Am. Coll. Cardiol., January 6, 2009; 53(1): 13 - 20. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. van Diepen, S. R. Majumdar, J. A. Bakal, F. A. McAlister, and J. A. Ezekowitz Heart Failure Is a Risk Factor for Orthopedic Fracture: A Population-Based Analysis of 16 294 Patients Circulation, November 4, 2008; 118(19): 1946 - 1952. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. S. Nieminen and V.-P. Harjola Heart failure in the elderly: How risky is it to be discharged? Eur J Heart Fail, March 1, 2008; 10(3): 222 - 223. [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||