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In this issue of Academic Emergency Medicine, Stiell and colleagues[1] present results from a prospective cohort study, the purpose of which was to derive a risk stratification tool to aid in disposition decision making in emergency department (ED) patients with acute heart failure (AHF). This is a timely and important article, as the resource utilization for AHF admissions and readmissions has come under an unprecedented degree of scrutiny. The authors appropriately hypothesized that improved risk stratification could assist the emergency physician (EP) in selecting patients for ED discharge who are at low risk of significant adverse events (SAEs). They enrolled a convenience sample of 559 patient visits and prospectively collected historical, physical examination, and laboratory findings that were available in the first 15 hours of care in six large Canadian EDs. In addition, they incorporated a measure of response to initial therapy by collecting data on a 3-minute walk test. The use of natriuretic peptides is not common in Canadian EDs, so 45% of patients had values of N-terminal–pro brain-natriuretic peptide (NT-proBNP) imputed. In contrast to the typical U.S. ED admission rate of 80%, only 38% of patients in the Canadian cohort were admitted to the hospital. Their predictive instrument, composed of 10 variables (and 15 total points), had an area under the receiver operating characteristic curve of 0.77. While there were relatively few SAEs (n = 65) for the number of degrees of freedom included in their model, there was good calibration between predicted and expected events, especially in those with few high-risk markers. The authors suggest that, once validated, this could be a useful tool to aid in ED risk stratification.

This study is important for EPs as it focuses on the cohort of AHF patients we need to better identify: those who can be safely discharged home from the ED. Too often previous studies have identified patients at high risk for mortality as the primary outcome.[2, 3] From an ED perspective, these prediction rules geared toward identifying high-risk patients have very little effect on decision-making. Stated another way, when EPs are already admitting four out of five patients with AHF to the hospital, will markers of high risk really alter practice patterns?

However, there are limitations that should be considered when interpreting the results of this article. Patients were included based on a clinical definition of AHF, which may be reflective of real-world management, but introduces significant variability to a prospective study. The author's definition of an SAE did not include repeat ED visits or hospital admission to an “ambulatory” unit (equivalent to the standard floor bed in the United States), and most events were only tracked by chart review during the 14 days after ED presentation. While events that occur soon after ED or hospital discharge are likely more temporally related to initial management decisions, U.S. hospitals are under intense pressure to prevent readmission within 30 days. While validation is a necessary next step as suggested by the authors, how the rule augments current decision-making is an even more important future step prior to its implementation. Finally, the inclusion of variables up to 12 hours after initial ED presentation suggests that many of the subjects in this cohort had prolonged ED stays, which would be more reflective of an observation unit (OU) in the United States, rather than primary ED management. Practice patterns are dramatically different between the United States and Canada. While the low admission rate in the current study may reduce some of the confounding that occurs with hospitalization, it is difficult to know the true effect of hospitalization on the patient and his or her probability of an SAE. Previous data suggest that life expectancy decreases with each AHF hospitalization, although whether this is related to the hospitalization process, or the fact that the patient is in need of hospitalization, is unclear.[4, 5]

Will we ever have a risk tool which, when added to clinical gestalt, substantially improves our ability to directly discharge ED patients with AHF? While some models appear promising, how they augment clinical decision-making is unclear.[6] With the complexity and comorbidity that accompanies each AHF patient, we are increasingly skeptical that such a readily implementable, dichotomous risk-stratification tool will be found. Faced with this reality, we need to recalibrate our approach to ED patients with AHF. Clearly those with cardiogenic shock, acute pulmonary edema, cardiorenal syndrome, or a plethora of simultaneously decompensating comorbidities require hospital admission. But this represents a relatively small proportion of ED patients. What happens during inpatient management to the large subset of ED patients without these features who are hospitalized for AHF? The data are striking: 1) very few patients receive invasive procedures that require intense monitoring, 2) the vast majority receive intravenous (IV) diuretics until symptoms improve, and 3) only a minority of patients requires IV inotropic agents or mechanical circulatory support.[7-9] It is not clear that care delivered during hospitalization is either necessary or sufficient to “prevent” further AHF events in many patients, as it does for many other disease processes such as sepsis, acute coronary syndromes, and acute stroke.

While we continue to search for the Holy Grail, alternative means of AHF management are needed that could avoid inpatient hospitalization. An intermediate goal, prior to development of a risk-stratification tool for ED discharge, would be correctly identifying (U.S.) ED patients who would benefit from OU management. The AHF care delivered in a hospital bed is readily provided in an ED-based OU. Preliminary data suggest that OU management of AHF is safe and effective.[10-12] In an OU, patients can simultaneously receive treatment and undergo further risk stratification to determine the need for hospitalization. Blood pressure control, diuresis, home medication reconciliation, AHF education, and further diagnostic testing can occur. Serial electrolytes, cardiac troponin measurement, and echocardiography, if required, can be easily obtained. Early outpatient follow-up, which may be as important as therapeutic decisions, and has been show to decrease hospital readmission, can also be facilitated.[13] Those OU patients with symptomatic improvement who do not develop high-risk features such as low blood pressure, renal dysfunction, hyponatremia, or an elevated troponin, can then be readily discharged. Finally, the “round-the-clock” nature of ED-based OUs also facilitates discharge at times other than midafternoon discharge encountered in most hospital settings.

Stiell and colleagues have taken a necessary first step in attempting to identify a cohort of ED patients who may be safely discharged home. However, significant work needs to be done before a risk-stratification tool can be implemented in the ED. In the meantime, a period of observation and treatment in an ED-based OU may be a reasonable alternative to hospital admission in many ED patients with AHF.

References

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  2. References
  • 1
    Stiell I, Clement C, Brison R, et al. A risk scoring system to identify emergency department patients with heart failure at high risk for serious adverse events. Acad Emerg Med. 2013; 20:1726.
  • 2
    Fonarow GC, Adams KF Jr, Abraham WT, Yancy CW, Boscardin WJ. Risk stratification for in-hospital mortality in acutely decompensated heart failure: classification and regression tree analysis. JAMA. 2005; 293:57280.
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    Lee DS, Stitt A, Austin PC, et al. Prediction of heart failure mortality in emergent care: a cohort study. Ann Intern Med. 2012; 156:76775.
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    Gheorghiade M, De Luca L, Fonarow GC, Filippatos G, Metra M, Francis GS. Pathophysiologic targets in the early phase of acute heart failure syndromes. Am J Cardiol. 2005; 96:11G17G.
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    Setoguchi S, Stevenson LW, Schneeweiss S. Repeated hospitalizations predict mortality in the community population with heart failure. Am Heart J. 2007; 154:2606.
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    Hsieh M, Auble TE, Yealy DM. Validation of the acute heart failure index. Ann Emerg Med. 2008; 51:3744.
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    Fonarow GC, Abraham WT, Albert NM, et al. Factors identified as precipitating hospital admissions for heart failure and clinical outcomes: findings from OPTIMIZE-HF. Arch Intern Med. 2008; 168:84754.
  • 8
    Gheorghiade M, Pang PS, Ambrosy AP, et al. A comprehensive, longitudinal description of the in-hospital and post-discharge clinical, laboratory, and neurohormonal course of patients with heart failure who die or are re-hospitalized within 90 days: analysis from the EVEREST trial. Heart Fail Rev. 2012; 17:485509.
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    Fonarow GC, Stough WG, Abraham WT, et al. Characteristics, treatments, and outcomes of patients with preserved systolic function hospitalized for heart failure: a report from the OPTIMIZE-HF Registry. J Am Coll Cardiol. 2007; 50:76877.
  • 10
    Storrow AB, Collins SP, Lyons MS, Wagoner LE, Gibler WB, Lindsell CJ. Emergency department observation of heart failure: preliminary analysis of safety and cost. Congest Heart Fail. 2005; 11:6872.
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    Peacock WF, Young J, Collins S, Diercks D, Emerman C. Heart failure observation units: optimizing care. Ann Emerg Med. 2006; 47:2233.
  • 12
    Ross MA, Aurora T, Graff L, et al. State of the art: emergency department observation units. Crit Pathw Cardiol. 2012; 11:12838.
  • 13
    Hernandez AF, Greiner MA, Fonarow GC, et al. Relationship between early physician follow-up and 30-day readmission among Medicare beneficiaries hospitalized for heart failure. JAMA. 2010; 303:171622.