A risk scoring system to identify emergency department patients with heart failure at high risk for serious adverse events

The HEARTRISK6 Scale: Predicting Short-Term Serious Outcomes in Emergency Department Acute Heart Failure Patients

Background

Acute heart failure (AHF) is a common emergency department (ED) presentation that may have poor outcomes but often does not require hospital admission. There is little evidence to guide dispositional decisions.

Objectives

The authors sought to create a risk score for predicting short-term serious outcomes (SSO) in patients with AHF.

Methods

We pooled data from 3 prospective cohorts: 2 published studies and 1 new cohort. The 3 cohorts prospectively enrolled patients who required treatment for AHF at 10 tertiary care hospital EDs. The primary outcome was SSO, defined as death <30 days, intubation or noninvasive ventilation (NIV), myocardial infarction, or relapse to ED <14 days. The logistic regression model evaluated 13 predictors, used an AIC-based step-down procedure, and bootstrapped internal validation.

Results

Of the 2,246 patients in the 3 cohorts (N = 559; 1,100; 587), the mean age was 77.4 years, 54.5% were male, 3.1% received intravenous nitroglycerin, 5.2% received ED NIV, and 48.6% were admitted to the hospital. There were 281 (12.5%) SSOs including 70 deaths (3.1%) with many in discharged patients. The final HEARTRISK6 Scale included 6 variables: valvular heart disease, tachycardia, need for NIV, creatinine, troponin, and failed reassessment (walk test). Choosing HEARTRISK6 total-point admission thresholds of ≥1 or ≥2 would yield, respectively, sensitivities of 88.3% (95% CI: 83.9%-91.8%) and 71.5% (95% CI: 65.9%-76.7%) and specificities of 24.7% (95% CI: 22.8%-26.7%) and 50.1% (95% CI: 47.9%-52.4%) for SSO.

Conclusions

Using 3 large prospectively collected datasets, we created a concise and sensitive risk scale for patients with AHF in the ED. Implementation of the HEARTRISK6 scale could lead to safer and more efficient disposition decisions.

Heart failure management at home: a non-randomised prospective case-controlled trial (HeMan at Home)

BACKGROUND/OBJECTIVES

Heart failure (HF) is a growing clinical and economic burden for patients and health systems. The COVID-19 pandemic has led to avoidance and delay in care, resulting in increased morbidity and mortality among many patients with HF. The increasing burden of HF during the COVID-19 pandemic led us to evaluate the quality and safety of the Hospital at Home (HAH) for patients presenting to their community providers or emergency department (ED) with symptoms of acute on chronic HF (CHF) requiring admission.

DESIGN/OUTCOMES

A non-randomised prospective case-controlled of patients enrolled in the HAH versus admission to the hospital (usual care, UC). Primary outcomes included length of stay (LOS), adverse events, discharge disposition and patient satisfaction. Secondary outcomes included 30-day readmission rates, 30-day ED usage and ED dwell time.

RESULTS

Sixty patients met inclusion/exclusion criteria and were included in the study. Of the 60 patients, 40 were in the HAH and 20 were in the UC group. Primary outcomes demonstrated that HAH patients had slightly longer LOS (6.3 days vs 4.7 days); however, fewer adverse events (12.5% vs 35%) compared with the UC group. Those enrolled in the HAH programme were less likely to be discharged with postacute services (skilled nursing facility or home health). HAH was associated with increased patient satisfaction compared with Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) score in North Carolina. Secondary outcomes of 30-day readmission and ED usage were similar between HAH and UC.

CONCLUSIONS

The HAH pilot programme was shown to be a safe and effective alternative to hospitalisation for the appropriately selected patient presenting with acute on CHF.

What are the Data for Current Prognostic Tools Used to Determine the Risk of Short-Term Adverse Events in Patients with Acute Heart Failure?

BACKGROUND

Acute heart failure (AHF) is a common condition evaluated in the emergency department (ED). Patients may present with a wide range of signs and symptoms, comorbidities, exacerbating factors, and ability to follow-up. Having a decision tool to objectively assess the risk of near-term events would help guide disposition decisions in these patients.

CLINICAL QUESTION

What are the data for current tools used to determine the short-term risk of adverse events of patients with AHF in the ED setting?

EVIDENCE REVIEW

Studies retrieved included six prospective studies and three retrospective cohort studies that evaluated the following five different risk scores that may predict the risk of serious adverse events in those with AHF: Ottawa Heart Failure Risk Score (OHFRS), Emergency Heart Failure Mortality Risk Grade (EHMRG), EHMRG at 30 days with addition of an ST depression variable (EHMRG30-ST), Multiple Estimation of Risk Based on the Emergency Department Spanish 40 Score in Patients with AHF Score (MEESSI-AHF), and the Improving Heart Failure Risk Stratification in the ED (STRATIFY) tool.

CONCLUSIONS

Based on the available literature, risk scores, including the OHFRS; EHMRG; EHMRG30-ST; MEESSI-AHF; and STRATIFY, can help identify short-term risk of adverse events, but are insufficient in isolation. Clinicians should use these tools in conjunction with other factors, such as the patient's symptom trajectory, hemodynamics, and access to follow-up care.

Candrive-Development of a Risk Stratification Tool for Older Drivers

BACKGROUND

Assessing an older adult's fitness-to-drive is an important part of clinical decision making. However, most existing risk prediction tools only have a dichotomous design, which does not account for subtle differences in risk status for patients with complex medical conditions or changes over time. Our objective was to develop an older driver risk stratification tool (RST) to screen for medical fitness-to-drive in older adults.

METHODS

Participants were active drivers aged 70 and older from 7 sites across 4 Canadian provinces. They underwent in-person assessments every 4 months with an annual comprehensive assessment. Participant vehicles were instrumented to provide vehicle and passive Global Positioning System (GPS) data. The primary outcome measure was police-reported, expert-validated, at-fault collision adjusted per annual kilometers driven. Predictor variables included physical, cognitive, and health assessment measures.

RESULTS

A total of 928 older drivers were recruited for this study beginning in 2009. The average age at enrollment was 76.2 (standard deviation [SD] = 4.8) with 62.1% male participants. The mean duration for participation was 4.9 (SD = 1.6) years. The derived Candrive RST included 4 predictors. Out of 4 483 person-years of driving, 74.8% fell within the lowest risk category. Only 2.9% of person-years were in the highest risk category where the relative risk for at-fault collisions was 5.26 (95% confidence interval = 2.81-9.84) compared to the lowest risk group.

CONCLUSIONS

For older drivers whose medical conditions create uncertainty regarding their fitness-to-drive, the Candrive RST may assist primary health care providers when initiating a conversation about driving and to guide further evaluation.

Outcomes of acute heart failure patients managed in the emergency department

BACKGROUND

Acute heart failure is a serious condition commonly seen in the emergency department (ED). The HEARTRISK6 Scale has been recently developed to identify the risk of poor outcomes but has not been tested. We sought to describe the management and outcomes of ED patients with acute heart failure and to evaluate the potential impact of the HEARTRISK6 Scale.

METHODS

We conducted a health records review of 300 consecutive acute heart failure patients presenting to two tertiary care EDs. Two evaluators abstracted clinical variables, ED management and treatment details, and patient outcomes using the electronic health records platform (EPIC) and attending physicians verified the data. The primary outcome measure was a short-term serious outcome, as shown in Results. In addition, the HEARTRISK6 score was calculated retrospectively.

RESULTS

We included 300 patients with mean age of 78.5 years, 51.0% male, 56.3% arrival by ambulance, and 67.0% admitted to hospital. 25.3% experienced a short-term serious outcome 1) after admission (N = 201): non-invasive ventilation 14.9%, intubation 1.5%, major cardiac procedure 5.0%, myocardial infarction 2.0%, death 8.5%; 2) after ED discharge (N = 99): return to ED 21.2%, death 4.0%. Those initially admitted experienced a much higher proportion of serious outcomes compared to those discharged (29.9% vs. 16.2%). A HEARTRISK6 Scale cut-point score of ≥ 1 would have had a sensitivity of 91.0%, specificity 24.5%, and negative likelihood ratio 0.37 for short-term serious outcomes and suggested hospital admission for 80.7% of cases.

CONCLUSION

There was a large range of severity of illness of acute heart failure patients and a wide variety of treatments were administered in the ED. Both admitted and discharged patients experienced a high proportion of poor outcomes. The HEARTRISK6 Scale showed a high sensitivity for short-term serious outcomes but with the potential to increase hospital admissions. Further validation of the HEARTRISK6 Scale is required before routine clinical use.

Emergency department risk assessment and disposition of acute heart failure patients: existing evidence and ongoing challenges

Heart failure (HF) is a global public health burden, characterized by frequent emergency department (ED) visits and hospitalizations. Identifying successful strategies to avoid admissions is crucial for the management of acutely decompensated HF, let alone resource utilization. The primary challenge for ED management of patients with acute heart failure (AHF) lies in the identification of those who can be safely discharged home instead of being admitted. This is an elaborate decision, based on limited objective evidence. Thus far, current biomarkers and risk stratification tools have had little impact on ED disposition decision-making. A reliable definition of a low-risk patient profile is warranted in order to accurately identify patients who could be appropriate for early discharge. A brief period of observation can facilitate risk stratification and allow for close monitoring, aggressive treatment, continuous assessment of response to initial therapy and patient education. Lung ultrasound may represent a valid bedside tool to monitor cardiogenic pulmonary oedema and determine the extent of achieved cardiac unloading after treatment in the observation unit setting. Safe discharge mandates multidisciplinary collaboration and thoughtful assessment of socioeconomic and behavioural factors, along with a clear post-discharge plan put forward and a close follow-up in an outpatient setting. Ongoing research to improve ED risk stratification and disposition of AHF patients may mitigate the tremendous public health challenge imposed by the HF epidemic.

Point-of-care echocardiography of the right heart improves acute heart failure risk stratification for low-risk patients: The REED-AHF prospective study

OBJECTIVES

Validated acute heart failure (AHF) clinical decision instruments (CDI) insufficiently identify low-risk patients meriting consideration of outpatient treatment. While pilot data show that tricuspid annulus plane systolic excursion (TAPSE) is associated with adverse events, no AHF CDI currently incorporates point-of-care echocardiography (POCecho). We evaluated whether TAPSE adds incremental risk stratification value to an existing CDI.

METHODS

Prospectively enrolled patients at two urban-academic EDs had POCechos obtained before or <1 h after first intravenous diuresis, positive pressure ventilation, and/or nitroglycerin. STEMI and cardiogenic shock were excluded. AHF diagnosis was adjudicated by double-blind expert review. TAPSE, with an a priori cutoff of ≥17 mm, was our primary measure. Secondary measures included eight additional right heart and six left heart POCecho parameters. STRATIFY is a validated CDI predicting 30-day death/cardiopulmonary resuscitation, mechanical cardiac support, intubation, new/emergent dialysis, and acute myocardial infarction or coronary revascularization in ED AHF patients. Full (STRATIFY + POCecho variable) and reduced (STRATIFY alone) logistic regression models were fit to calculate adjusted odds ratios (aOR), category-free net reclassification index (NRI_cont ), ΔSensitivity (NRI_events ), and ΔSpecificity (NRI_nonevents ). Random forest assessed variable importance. To benchmark risk prediction to standard of care, ΔSensitivity and ΔSpecificity were evaluated at risk thresholds more conservative/lower than the actual outcome rate in discharged patients.

RESULTS

A total of 84/120 enrolled patients met inclusion and diagnostic adjudication criteria. Nineteen percent experiencing the primary outcome had higher STRATIFY scores compared to those event free (233 vs. 212, p = 0.009). Five right heart (TAPSE, TAPSE/PASP, TAPSE/RVDD, RV-FAC, fwRVLS) and no left heart measures improved prediction (p < 0.05) adjusted for STRATIFY. Right heart measures also had higher variable importance. TAPSE ≥ 17 mm plus STRATIFY improved prediction versus STRATIFY alone (aOR 0.24, 95% confidence interval [CI] 0.06-0.91; NRI_cont  0.71, 95% CI 0.22-1.19), and specificity improved by 6%-32% (p < 0.05) at risk thresholds more conservative than the standard-of-care benchmark without missing any additional events.

CONCLUSIONS

TAPSE increased detection of low-risk AHF patients, after use of a validated CDI, at risk thresholds more conservative than standard of care.

Evaluation of the HEFESTOS scale to predict outcomes in emergency department acute heart failure patients

The HEFESTOS scale was developed in 14 Spanish primary care centres and validated in 9 primary care centres of other European countries. It showed good performance to predict death/hospitalisation during the first 30 days after an episode of acute heart failure (AHF), with c-statistics of 0.807/0.730 in the derivation/validation cohorts. We evaluated this scale in the emergency department (ED) setting, comparing it to the EHMRG and MEESSI scales in the ED and the EFFECT and GWTG scales in hospitalised patients, to predict 30-day outcomes, including death and hospitalisation. Consecutive AHF patients were enrolled in 34 Spanish EDs in January-February 2016, 2018, and 2019 with variables needed to calculate outcome scores. Thirty-day hospitalisation/death (together and separately) and post-discharge combined adverse event (ED revisit or hospitalisation for AHF or all-cause death) were determined for patients discharged home after ED care. Predictive capacity was assessed by c-statistic with 95% confidence intervals. Of 10,869 patients, 4,044 were included (median age: 83 years, 54% women). The performance of HEFESTOS was modest for 30-day hospitalisation/death, c-statistic=0.656 (0.637-0.675), hospitalisation, 0.650 (0.631-0.669), and death, 0.610 (0.576-0.644). Of 1,034 patients with scores for the 5 scales, HEFESTOS had the numerically highest c-statistic for hospitalisation/death at 30 days, 0.666 (0.627-0.704), vs. MEESSI= 0.650 (0.612-0.687, p=0.51), EFFECT=0.633 (0.595-0.672, p=0.21), GWTG=0.618 (0.578-0.657, p=0.06) and EHMRG=0.617 (0.577-0.704, p=0.07). Similar modest performances were observed for predicting hospitalisation [ranging from HEFESTOS=0.656 (0.618-0.695) to GWTG=0.603 (0.564-0.643)]. Conversely, prediction of 30-day death was good with the MEESSI=0.787 (0.728-845), EFFECT=0.754 (0.691-0.818) and GWTG=0.749 (0.689-0.809) scales, and modest with EHMRG=0.649 (0.581-0.717) and HEFESTOS=0.610 (0.538-0.683). Although the HEFESTOS scale was numerically better for predicting 30-day hospitalisation/death in ED AHF patients, its modest performance precludes routine use. Only 30-day mortality was adequately predicted by some scales, with the MEESSI achieving the best results.

Implementation of EHMRG Risk Model in an Italian Population of Elderly Patients with Acute Heart Failure

Acute heart failure (AHF) is a cardiac emergency with an increasing incidence, especially among elderly patients. The Emergency Heart failure Mortality Risk Grade (EHMRG) has been validated to assess the 7-days AHF mortality risk, suggesting the management of patients admitted to an emergency department (ED). EHMRG has never been implemented in Italian ED nor among elderly patients. We aimed to assess EHMRG score accuracy in predicting in-hospital death in a retrospective cohort of elderly subjects admitted for AHF from the ED to an Internal Medicine Department. We enrolled, in a 24-months timeframe, all the patients admitted to an Internal Medicine Department from ED for AHF. We calculated the EHMRG score, subdividing patients into six categories, and assessing in-hospital mortality and length of stay. We evaluated EHMRG accuracy with ROC curve analysis and survival with Kaplan−Meier and Cox models. We collected 439 subjects, with 45 in-hospital deaths (10.3%), observing a significant increase of in-hospital death along with EHMRG class, from 0% (class 1) to 7.7% (class 5b; p < 0.0001). EHMRG was fairly accurate in the whole cohort (AUC: 0.75; 95%CI: 0.68−0.83; p < 0.0001), with the best cutoff observed at >103 (Se: 71.1%; Sp: 72.8%; LR+: 2.62; LR-: 0.40; PPV: 23.0%; NPV: 95.7%), but performed better considering the events in the first seven days of admission (AUC: 0.83; 95%; CI: 0.75−0.91; p < 0.0001). In light of our observations, EHMRG can be useful also for the Italian emergency system to predict the risk of short-term mortality for AHF among elderly patients. EHMRG performance was better in the first seven days but remained acceptable when considering the whole period of hospitalization.

Prognostic risk scores for patients with heart failure

Heart failure has many causes. Although new drugs, devices and technologies are available, the survival rate and prognosis of patients with heart failure remain poor, placing a significant burden on individuals and society. Attempts to improve outcomes for patients with heart failure include developing prognostic risk scores. With medical advances, however, previous heart failure risk scores are not fully applicable to current practice, particularly because of the classification as heart failure with reduced ejection fraction, heart failure with mildly reduced ejection fraction, and heart failure with preserved ejection fraction. This article describes the use of risk prediction scores for heart failure patients with different clinical status and discusses their clinical applicability.

Improving the EHMRG Prognostic Evaluation of Acute Heart Failure with TAPSE/PASp: A Sequential Approach

The Emergency Heart Failure Mortality Risk Grade (EHMRG) can predict short-term mortality in patients admitted for acute heart failure (AHF) in the emergency department (ED). This paper aimed to evaluate if TAPSE/PASp, an echocardiographic marker of ventricular desynchronization, can improve in-hospital death prediction in patients at moderate-to-high risk, according to EHMRG score classification. From 1 January 2018 to 30 December 2019, we retrospectively enrolled all the consecutive subjects admitted to our Internal Medicine Department for AHF from the ED. We performed bedside echocardiography within the first 24 h of admission. We evaluated EHMRG and NYHA in the ED, days of admission in Internal Medicine, and in-hospital mortality. We assessed cutoffs with ROC curve analysis and survival with Kaplan–Meier and Cox regression. We obtained a cohort of 439 subjects; 10.3% underwent in-hospital death. Patients with normal TAPSE/PASp in EHMRG Classes 4, 5a, and 5b had higher survival rates (100%, 100%, and 94.3%, respectively), while subjects with pathologic TAPSE/PASp had lower survival rates (81.8%, 78.3%, and 43.4%, respectively) (p < 0.0001, log-rank test). TAPSE/PASp, an echocardiographic marker of ventricular desynchronization, can further stratify the risk of in-hospital death evaluated by EHMRG.

Disease evolution and risk-based disease trajectories in congestive heart failure patients

Congestive Heart Failure (CHF) is among the most prevalent chronic diseases worldwide, and is commonly associated with comorbidities and complex health conditions. Consequently, CHF patients are typically hospitalized frequently, and are at a high risk of premature death. Early detection of an envisaged patient disease trajectory is crucial for precision medicine. However, despite the abundance of patient-level data, cardiologists currently struggle to identify disease trajectories and track the evolution patterns of the disease over time, especially in small groups of patients with specific disease subtypes. The present study proposed a five-step method that allows clustering CHF patients, detecting cluster similarity, and identifying disease trajectories, and promises to overcome the existing difficulties. This work is based on a rich dataset of patients' records spanning ten years of hospital visits. The dataset contains all the health information documented in the hospital during each visit, including diagnoses, lab results, clinical data, and demographics. It utilizes an innovative Cluster Evolution Analysis (CEA) method to analyze the complex CHF population where each subject is potentially associated with numerous variables. We have defined sub-groups for mortality risk levels, which we used to characterize patients' disease evolution by refined data clustering in three points in time over ten years, and generating patients' migration patterns across periods. The results elicited 18, 23, and 25 clusters respective to the first, second, and third visits, uncovering clinically interesting small sub-groups of patients. In the following post-processing stage, we identified meaningful patterns. The analysis yielded fine-grained patient clusters divided into several finite risk levels, including several small-sized groups of high-risk patients. Significantly, the analysis also yielded longitudinal patterns where patients' risk levels changed over time. Four types of disease trajectories were identified: decline, preserved state, improvement, and mixed-progress. This stage is a unique contribution of the work. The resulting fine partitioning and longitudinal insights promise to significantly assist cardiologists in tailoring personalized interventions to improve care quality. Cardiologists could utilize these results to glean previously undetected relationships between symptoms and disease evolution that would allow a more informed clinical decision-making and effective interventions.

Risk stratification in heart failure decompensation in the community: HEFESTOS score

Aims

Because evidence regarding risk stratification predicting prognosis of patients with heart failure (HF) decompensation attended in primary care is lacking, we developed and externally validated a model to forecast death/hospitalization during the first 30 days after an episode of decompensation. The predictive model is based on variables easily obtained in primary care settings.

Methods and results

HEFESTOS is a multinational study consisting of a derivation cohort of HF patients recruited in 14 primary healthcare centres in Barcelona and a validation cohort from primary healthcare in 9 other European countries. The derivation and validation cohorts included 561 and 250 patients, respectively. Percentages of women in the derivation and validation cohorts were 56.3% and 47.6% (P = 0.026), respectively. Mean age was 82.2 years (SD 8.03) in the derivation cohort, and 79.3 years (SD 10.3) in the validation one (P = 0.001). HF with preserved ejection fraction represented 72.1% in the derivation cohort and 58.8% in the validation one (P = 0.004). Mortality/hospitalization during the first 30 days after a decompensation episode was 30.5% and 26% (P = 0.225) for the derivation and validation cohorts, respectively. Multivariable logistic regression models were performed to develop a score of risk. The identified predictors were worsening of dyspnoea [odds ratio (OR): 2.5; P = 0.001], orthopnoea (OR: 2.16; P = 0.01), paroxysmal nocturnal dyspnoea (OR: 2.25; P = 0.01), crackles (OR: 2.35; P = 0.01), New York Heart Association functional class III/IV (OR: 2.11; P = 0.001), oxygen saturation ≤ 90% (OR: 4.98; P < 0.001), heart rate > 100 b.p.m. (OR: 2.72; P = 0.002), and previous hospitalization due to HF (OR: 2.45; P < 0.001). The model showed an area under the curve (AUC) of 0.807, 95% confidence interval (CI): [0.770; 0.845] in the derivation cohort and AUC 0.73, 95% CI: [0.660; 0.808] in the validation one. No significant differences between both cohorts were observed (P = 0.08). Regarding probability of hospitalization/death, three risk groups were defined: low <5%, medium 5–20%, and high >20%. Outcome incidence was 2.7% for the low‐risk group, 12.8% for medium risk, and 46.2% for high risk in the derivation cohort, and 9.1%, 12.9%, and 39.6% in the validation one.

Conclusions

The HEFESTOS score, based on variables easily accessible in a community setting and validated in an external European cohort, properly predicted the risk of death/hospitalization during the first 30 days after an HF decompensation episode.

Disposition of acute decompensated heart failure from the emergency department: An evidence-based review

INTRODUCTION

Acute heart failure (HF) exacerbation is a serious and common condition seen in the Emergency Department (ED) that has significant morbidity and mortality. There are multiple clinical decision tools that Emergency Physicians (EPs) can use to reach an appropriate evidence-based disposition for these patients.

OBJECTIVE

This narrative review is an evidence-based discussion of clinical decision-making tools aimed to assist EPs risk stratify patients with AHF and determine disposition.

DISCUSSION

Risk stratification in patients with AHF exacerbation presenting to the ED is paramount in reaching an appropriate disposition decision. High risk features include hypotension, hypoxemia, elevated brain natriuretic peptide (BNP) and/or troponin, elevated creatinine, and hyponatremia. Patients who require continuous vasoactive infusions, respiratory support, or are initially treatment-resistant generally require intensive care unit admission. In most instances, new-onset AHF patients should be admitted for further evaluation. Other AHF patients in the ED can be risk stratified with the Ottawa HF Risk Score (OHFRS), the Multiple Estimation of Risk Based on Spanish Emergency Department Score (MEESSI), or the Emergency HF Mortality Risk Grade (EHFMRG). These tools take various factors into account such as mode of arrival to the ED, vital signs, laboratory values like troponin and pro-BNP, and clinical course. If used appropriately, these scores can predict patients at low risk for adverse outcomes.

CONCLUSION

This article discusses evidence-based disposition of patients in acute decompensated HF presenting to the ED. Knowledge of these factors and risk tools can assist emergency clinicians in determining appropriate disposition of patients with HF.

A Home Hospitalisation Strategy for Patients with an Acute Episode of Heart Failure Using a Digital Health-Supported Platform: A Multicentre Feasibility Study - A Rationale and Study Design

BACKGROUND

Heart failure (HF) is a common cause of hospitalisation and mortality in elderly. The frequent rehospitalisations put a serious burden on patients, health-care budgets, and health-care capacity. Frequent hospital admissions are also associated with a substantial additional hazard for serious complications and reduced quality of life. The NWE-Chance project will explore the feasibility and scalability of providing home hospitalisation supported by a newly developed digital health-supported platform and daily visits of specialised nurses.

METHODS/DESIGN

Hundred patients with chronic HF will be recruited over a 1-year period. The digital health-supported home hospitalisation strategy will be tested in 3 hospitals with different experience in delivering home hospitalisation: Isala Zwolle, Maastricht UMC+, both in The Netherlands, and Jessa Hospital, Hasselt in Belgium. The home hospitalisation intervention will have a maximal duration of 14 days. Feasibility will be measured with acceptability, satisfaction, and usability questionnaires for patients, nurses, and physicians. Furthermore, safety and costs will be assessed for 30 days after the start of the home hospitalisation intervention.

DISCUSSION

The NWE-Chance project will be one of the first studies to examine the feasibility of a digital health-supported home hospitalisation platform for HF patients. It has the potential to augment current standard HF care and quality of life of HF patients and to innovate the standard HF care to potentially lower the hospitalisation-related complications, the burden of HF on health-care systems, and to potentially implement more patient-centred care strategies.

Derivation and validation of a mortality risk prediction model using global longitudinal strain in patients with acute heart failure

AIMS

To develop a mortality risk prediction model in patients with acute heart failure (AHF), using left ventricular (LV) function parameters with clinical factors.

METHODS AND RESULTS

In total, 4312 patients admitted for AHF were retrospectively identified from three tertiary centres, and echocardiographic parameters including LV ejection fraction (LV-EF) and LV global longitudinal strain (LV-GLS) were measured in a core laboratory. The full set of risk factors was available in 3248 patients. Using Cox proportional hazards model, we developed a mortality risk prediction model in 1859 patients from two centres (derivation cohort) and validated the model in 1389 patients from one centre (validation cohort). During 32 (interquartile range 13-54) months of follow-up, 1285 patients (39.6%) died. Significant predictors for mortality were age, diabetes, diastolic blood pressure, body mass index, natriuretic peptide, glomerular filtration rate, failure to prescribe beta-blockers, failure to prescribe renin-angiotensin system blockers, and LV-GLS; however, LV-EF was not a significant predictor. Final model including these predictors to estimate individual probabilities of mortality had C-statistics of 0.75 [95% confidence interval (CI) 0.73-0.78; P < 0.001] in the derivation cohort and 0.78 (95% CI 0.75-0.80; P < 0.001) in the validation cohort. The prediction model had good performance in both heart failure (HF) with reduced EF, HF with mid-range EF, and HF with preserved EF.

CONCLUSION

We developed a mortality risk prediction model for patients with AHF incorporating LV-GLS as the LV function parameter, and other clinical factors. Our model provides an accurate prediction of mortality and may provide reliable risk stratification in AHF patients.

Risk stratification scores for patients with acute heart failure in the Emergency Department: A systematic review

AIMS

This study aimed to systematically identify and summarise all risk scores evaluated in the emergency department setting to stratify acute heart failure patients.

METHODS AND RESULTS

A systematic review of PubMed and Web of Science was conducted including all multicentre studies reporting the use of risk predictive models in emergency department acute heart failure patients. Exclusion criteria were: (a) non-original articles; (b) prognostic models without predictive purposes; and (c) risk models without consecutive patient inclusion or exclusively tested in patients admitted to a hospital ward. We identified 28 studies reporting findings on 19 scores: 13 were originally derived in the emergency department (eight exclusively using acute heart failure patients), and six in emergency department and hospitalised patients. The outcome most frequently predicted was 30-day mortality. The performance of the scores tended to be higher for outcomes occurring closer to the index acute heart failure event. The eight scores developed using acute heart failure patients only in the emergency department contained between 4-13 predictors (age, oxygen saturation and creatinine/urea included in six scores). Five scores (Emergency Heart Failure Mortality Risk Grade, Emergency Heart Failure Mortality Risk Grade 30 Day mortality ST depression, Epidemiology of Acute Heart Failure in Emergency department 3 Day, Acute Heart Failure Risk Score, and Multiple Estimation of risk based on Emergency department Spanish Score In patients with Acute Heart Failure) have been externally validated in the same country, and two (Emergency Heart Failure Mortality Risk Grade and Multiple Estimation of risk based on Emergency department Spanish Score In patients with Acute Heart Failure) further internationally validated. The c-statistic for Emergency Heart Failure Mortality Risk Grade to predict seven-day mortality was between 0.74-0.81 and for Multiple Estimation of risk based on Emergency department Spanish Score In patients with Acute Heart Failure to predict 30-day mortality was 0.80-0.84.

CONCLUSIONS

There are several scales for risk stratification of emergency department acute heart failure patients. Two of them are accurate, have been adequately validated and may be useful in clinical decision-making in the emergency department i.e. about whether to admit or discharge.

Performance of Emergency Heart Failure Mortality Risk Grade in the Emergency Department

INTRODUCTION

The purpose of this study was to validate and assess the performance of the Emergency Heart Failure Mortality Risk Grade (EHMRG) to predict seven-day mortality in US patients presenting to the emergency department (ED) with acute congestive heart failure (CHF) exacerbation.

METHODS

We performed a retrospective chart review on patients presenting to the ED with acute CHF exacerbation between January 2014-January 2016 across eight EDs in New York. We identified patients using codes from the International Classification of Diseases, 9th and 10 Revisions, or who were diagnosed with CHF in the ED. Inclusion criteria were patients ≥ 18 years of age who presented to the ED for acute CHF. Exclusion criteria included the following: end-stage renal disease related heart failure; < 18 years of age; pregnancy; palliative care; renal failure; and "do not resuscitate" directive. The primary outcome was seven-day mortality. We used mixed-effects logistic regression models to estimate C-statistics and continuous net reclassification index for events and nonevents.

RESULTS

We identified 3,320 ED visits associated with suspected CHF among 2,495 unique patients. Of the 3,320 ED visits, 94.7% patients were admitted to the hospital and 3.4% were discharged. The median age was 78.6 (interquartile range 68.01 - 86.76). There was an overall seven-day mortality of 2%, an inpatient mortality rate of 2.4%, and no mortality among the discharge group. Adding EHMRG to the risk prediction model improved the C-statistic (from 0.748 to 0.772) and led to a higher degree of reclassification for both events and nonevents.

CONCLUSION

The EHMRG can be used as a valuable and effective screening tool in the US while considering disposition decision for patients with acute CHF exacerbation. Emergency medical services transport and metolazone use is much higher in the US population as compared to the Canadian population. We observed minimal to no short-term mortality among discharged CHF patients from the ED.

Interdepartmental program to improve outcomes for acute heart failure patients seen in the emergency department

INTRODUCTION

Acute heart failure patients often have an uncertain or delayed follow-up after discharge from the ED. Our goal was to introduce rapid-access specialty clinics to ensure acute heart failure patients were seen within 7 days, in an effort to reduce admissions and improve follow-up care.

METHODS

This prospective cohort study was conducted at two campuses of a large tertiary care hospital. We enrolled acute heart failure patients who presented to the ED with shortness of breath and were later discharged. Following a 12-month before period, we introduced rapid-access acute heart failure clinics staffed by cardiology and internal medicine. We allowed for a 3-month implementation period and then observed outcomes over the subsequent 12-month after period. The primary outcome was hospital admission within 30 days. Secondary outcomes included mortality and actual access to specialty care.

RESULTS

Patients in the before (N = 355) and after periods (N = 374) were similar for age and most characteristics. Segmented autoregression analysis demonstrated there was a pre-existing trend to fewer admissions. Attendance at a specialty clinic increased from 17.8 to 42.1% (P < 0.01) and the median days to the clinic decreased from 13 to 6 days (P < 0.01). 30-days mortality did not change.

CONCLUSION

Implementation of rapid-access clinics for acute heart failure patients discharged from the ED did not lead to an overall decrease in hospital admissions. It did, however, lead to increased access to specialist care, reduced follow-up times, without an increase in return ED visits or mortality. Widespread use of this rapid-access approach to a specialist can improve care for acute heart failure patients discharged home from the ED.

Adverse Events Among Emergency Department Patients With Cardiovascular Conditions: A Multicenter Study

STUDY OBJECTIVE

We aim to determine incidence and type of adverse events (adverse outcomes related to emergency care) among emergency department (ED) patients discharged with recent-onset atrial fibrillation, acute heart failure, and syncope.

METHODS

This 5-year prospective cohort study included high-acuity adult patients discharged with the 3 sentinel diagnoses from 6 tertiary care Canadian EDs. We screened all ED visits for eligibility and performed telephone interviews 14 days postdischarge to identify flagged outcomes: death, hospital admission, return ED visit, health care provider visit, and new or worsening symptoms. We created case summaries describing index ED visit and flagged outcomes, and trained emergency physicians reviewed case summaries to identify adverse events. We reported adverse event incidence and rates with 95% confidence intervals and contributing factor themes.

RESULTS

Among 4,741 subjects (mean age 70.2 years; 51.2% men), we observed 170 adverse events (3.6 per 100 patients; 95% confidence interval 3.1 to 4.2). Patients discharged with acute heart failure were most likely to experience adverse events (5.3%), followed by those with atrial fibrillation (2.0%) and syncope (0.8%). We noted variation in absolute adverse event rates across sites from 0.7 to 6.0 per 100 patients. The most common adverse event types were management issues, diagnostic issues, and unsafe disposition decisions. Frequent contributing factor themes included failure to recognize underlying causes and inappropriate management of dual diagnoses.

CONCLUSION

Among adverse events after ED discharge for patients with these 3 sentinel cardiovascular diagnoses, we identified quality improvement opportunities such as strengthening dual diagnosis detection and evidence-based clinical practice guideline adherence.

Evidence-Based Management of Acute Heart Failure

Acute heart failure (AHF) is a complex, heterogeneous, clinical syndrome with high morbidity and mortality, incurring significant health care costs. Patients transition from home to the emergency department, the hospital, and home again and require decisions surrounding diagnosis, treatment, and prognosis at each step of the way. The purpose of this review is to examine the epidemiology, etiology, and classifications of AHF and specifically focus on practical information relevant to the clinician. We examine the mechanisms of decompensation relevant to clinical presentations-including precipitating factors, neuroendocrine interactions, and inflammation-along with how consideration of these factors may help select therapies for an individual patient. The prevalence and significance of end-organ manifestations such as renal, gastrointestinal, respiratory, and neurologic manifestations are discussed. We also highlight how the development of renal dysfunction relates to the choice of a variety of diuretics that may be useful in specific circumstances and review guideline-directed medical therapy. We discuss the practical use (and pitfalls) of a variety of evidence-based clinical scoring criteria available to risk stratify patients with AHF. Finally, evidence-based management of AHF is discussed, including both pharmacologic and nonpharmacologic therapies, including the lack of evidence for using old and new vasodilators and the recent evidence regarding initiation of newer therapies in hospital. Overall, we suggest that clinicians consider implementing the newer data in AHF and subject existing practice patterns and treatments to the same rigour as new therapies.

Use of Machine Learning to Develop a Risk-Stratification Tool for Emergency Department Patients With Acute Heart Failure

STUDY OBJECTIVE

We use variables from a recently derived acute heart failure risk-stratification rule (STRATIFY) as a basis to develop and optimize risk prediction using additional patient clinical data from electronic health records and machine-learning models.

METHODS

Using a retrospective cohort design, we identified all emergency department (ED) visits for acute heart failure between January 1, 2017, and December 31, 2018, among adult health plan members of a large system with 21 EDs. The primary outcome was any 30-day serious adverse event, including death, cardiopulmonary resuscitation, balloon-pump insertion, intubation, new dialysis, myocardial infarction, or coronary revascularization. Starting with the 13 variables from the STRATIFY rule (base model), we tested whether predictive accuracy in a different population could be enhanced with additional electronic health record-based variables or machine-learning approaches (compared with logistic regression). We calculated our derived model area under the curve (AUC), calculated test characteristics, and assessed admission rates across risk categories.

RESULTS

Among 26,189 total ED encounters, mean patient age was 74 years, 51.7% were women, and 60.7% were white. The overall 30-day serious adverse event rate was 18.8%. The base model had an AUC of 0.76 (95% confidence interval 0.74 to 0.77). Incorporating additional variables led to improved accuracy with logistic regression (AUC 0.80; 95% confidence interval 0.79 to 0.82) and machine learning (AUC 0.85; 95% confidence interval 0.83 to 0.86). We found that 11.1%, 25.7%, and 48.9% of the study population had predicted serious adverse event risk of less than or equal to 3%, less than or equal to 5%, and less than or equal to 10%, respectively, and 28% of those with less than or equal to 3% risk were admitted.

CONCLUSION

Use of a machine-learning model with additional variables improved 30-day risk prediction compared with conventional approaches.

Does a brief functional assessment in the emergency department predict outcomes of patients admitted with heart failure? The FASTER-HF study

BACKGROUND

Evaluation of patients with acute decompensated heart failure includes symptom review, biomarker measurement and comorbidity assessment. Early objective evaluation of functional status is generally not performed.

AIM

To investigate whether a simple low-impact functional assessment and measurement of sarcopenia would be safe, feasible and predictive of hospital length of stay and all-cause 30-day hospital readmission.

METHODS

We administered 3-minute bicycle ergometry and hand grip strength tests at admission and discharge to patients for whom a decision to admit for heart failure management was made in the emergency department. Associations were examined between test results and length of stay and 30-day readmission. Exclusion criteria included acute coronary syndrome, hypoxia, end-stage renal disease, dementia/delirium and inability to sit at bedside. The Kansas City Cardiomyopathy Questionnaire-12, the Patient Health Questionnaire-2 and the visual analogue scale for dyspnoea were administered at admission, the visual analogue scale at discharge and the Kansas City Cardiomyopathy Questionnaire-12 at 30 days.

RESULTS

Fifty patients were enrolled: 58% were female; the mean age was 66.2±12.5 years; 24% had heart failure with preserved ejection fraction. Bicycle ergometry variables did not correlate with outcomes. Change in handgrip strength correlated with readmission, but not after adjustment (r_partial=0.14; P=0.35). Total diuretic dose correlated with length of stay; only discharge visual analogue scale and baseline lung disease had significant adjusted correlations with readmission.

CONCLUSIONS

Functional assessment in the emergency department of patients admitted for heart failure did not predict outcomes. However, the prognostic value of these assessments for decision-making about disposition (admission or discharge) may still be warranted.

MEESSI-AHF risk score performance to predict multiple post-index event and post-discharge short-term outcomes

BACKGROUND

The multiple estimation of risk based on the emergency department Spanish score in patients with acute heart failure (MEESSI-AHF) is a risk score designed to predict 30-day mortality in acute heart failure patients admitted to the emergency department. Using a derivation cohort, we evaluated the performance of the MEESSI-AHF risk score to predict 11 different short-term outcomes.

METHODS

Patients with acute heart failure from 41 Spanish emergency departments (n=7755) were recruited consecutively in two time periods (2014 and 2016). Logistic regression models based on the MEESSI-AHF risk score were used to obtain c-statistics for 11 outcomes: three with follow-up from emergency department admission (inhospital, 7-day and 30-day mortality) and eight with follow-up from discharge (7-day mortality, emergency department revisit and their combination; and 30-day mortality, hospital admission, emergency department revisit and their two combinations with mortality).

RESULTS

The MEESSI-AHF risk score strongly predicted mortality outcomes with follow-up starting at emergency department admission (c-statistic 0.83 for 30-day mortality; 0.82 for inhospital death, P=0.121; and 0.85 for 7-day mortality, P=0.001). Overall, mortality outcomes with follow-up starting at hospital discharge predicted slightly less well (c-statistic 0.80 for 7-day mortality, P=0.011; and 0.75 for 30-day mortality, P<0.001). In contrast, the MEESSI-AHF score predicted poorly outcomes involving emergency department revisit or hospital admission alone or combined with mortality (c-statistics 0.54 to 0.62).

CONCLUSIONS

The MEESSI-AHF risk score strongly predicts mortality outcomes in acute heart failure patients admitted to the emergency department, but the model performs poorly for outcomes involving hospital admission or emergency department revisit. There is a need to optimise this risk score to predict non-fatal events more effectively.

Outpatient treatment of worsening heart failure with intravenous and subcutaneous diuretics: a systematic review of the literature

Aims

In the coming decade, heart failure (HF) represents a major global healthcare challenge due to an ageing population and rising prevalence combined with scarcity of medical resources and increasing healthcare costs. A transitional care strategy within the period of clinical worsening of HF before hospitalization may offer a solution to prevent hospitalization. The outpatient treatment of worsening HF with intravenous or subcutaneous diuretics as an alternative strategy for hospitalization has been described in the literature.

Methods and results

In this systematic review, the available evidence for the efficacy and safety of outpatient treatment with intravenous or subcutaneous diuretics of patients with worsening HF is analysed. A search was performed in the electronic databases MEDLINE and EMBASE. Of the 11 included studies 10 were single‐centre, using non‐randomized, observational registries of treatment with intravenous or subcutaneous diuretics for patients with worsening HF with highly variable selection criteria, baseline characteristics, and treatment design. One study was a randomized study comparing subcutaneous furosemide with intravenous furosemide. In a total of 984 unique individual patients treated in the reviewed studies, only a few adverse events were reported. Re‐hospitalization rates for HF at 30 and 180 days were 28 and 46%, respectively. All‐cause re‐hospitalization rates at 30 and 60 days were 18–37 and 22%, respectively. The highest HF re‐hospitalization was 52% in 30 days in the subcutaneous diuretic group and 42% in 30 days in the intravenous diuretic group.

Conclusions

The reviewed studies present practice‐based results of treatment of patients with worsening HF with intravenous or subcutaneous diuretics in an outpatient HF care unit and report that it is effective by relieving symptoms with a low risk of adverse events. The studies do not provide satisfactory evidence for reduction in rates of re‐hospitalization or improvement in mortality or quality of life. The conclusions drawn from these studies are limited by the quality of the individual studies. Prospective randomized studies are needed to determine the safety and effectiveness of outpatient intravenous or subcutaneous diuretic treatment for patient with worsening HF.

Diagnosis of Acute Heart Failure in the Emergency Department: An Evidence-Based Review

Heart failure is a common presentation to the emergency department (ED), which can be confused with other clinical conditions. This review provides an evidence-based summary of the current ED evaluation of heart failure. Acute heart failure is the gradual or rapid decompensation of heart failure, resulting from either fluid overload or maldistribution. Typical symptoms can include dyspnea, orthopnea, or systemic edema. The physical examination may reveal pulmonary rales, an S3 heart sound, or extremity edema. However, physical examination findings are often not sensitive or specific. ED assessments may include electrocardiogram, complete blood count, basic metabolic profile, liver function tests, troponin, brain natriuretic peptide, and a chest radiograph. While often used, natriuretic peptides do not significantly change ED treatment, mortality, or readmission rates, although they may decrease hospital length of stay and total cost. Chest radiograph findings are not definitive, and several other conditions may mimic radiograph findings. A more reliable modality is point-of-care ultrasound, which can facilitate the diagnosis by assessing for B-lines, cardiac function, and inferior vena cava size. These modalities, combined with clinical assessment and gestalt, are recommended.

Characteristics and prognosis of patients with acute heart failure without troponin determination: The EAHFE-TROPICA3 study

BACKGROUND

The absence of cardiac troponin (cTn) determination in an episode of acute heart failure (AHF) is frequent. The characteristics of these patients are not well known; nor is it known whether they have a better prognosis than patients in whom cTn is determined.

AIM

The objective of the EAHFE-TROPICA3 study was to analyse the characteristics of patients consulting for AHF in whom cTn was not determined (nocTn), and to evaluate the relationship of cTn determination (wcTn) with patient outcomes.

METHODS

This was an analysis of the multipurpose prospective EAHFE registry of patients with AHF consulting at the emergency departments of 34 Spanish hospitals.

RESULTS

Data from 8850 patients with AHF were analysed; cTn was not determined in 4216 of these patients (47.6%), who had a lower prevalence of ischaemic heart disease, more frequent use of loop diuretics at baseline, a greater rate of oedema in the acute episode, more frequent history of heart failure, and less use of angiotensin-converting enzyme inhibitors or aldosterone receptor antagonists and beta-blockers at baseline. Compared with the wcTn group, the nocTn group had the same in-hospital mortality (adjusted odds ratio [OR] 1.21, 95% confidence interval [CI] 0.98-1.50), mortality at 30 days (adjusted OR 1.07, 95% CI 0.90-1.28) and reconsultation at 30 days (adjusted OR 0.90, 95% CI 0.80-1.02).

CONCLUSIONS

Patients presenting with AHF with and without cTn determination have different characteristics. These differences are not related to a better prognosis.

External Validation and Refinement of Emergency Heart Failure Mortality Risk Grade Risk Model in Patients With Heart Failure in the Emergency Department

Background

Emergency Heart Failure Mortality Risk Grade (EHMRG) assesses the risk of death within 7 days of emergency department (ED) presentation for patients with acute heart failure (AHF). We aimed to externally validate and refine the EHMRG model in patients who presented to the ED with AHF.

Methods

We performed a cohort study using administrative data for all ambulance-transported patients from Alberta (2012-2016) presenting to the ED with a primary diagnosis of AHF.

Results

Among 6708 patients with AHF, the 7-day mortality was 0.0%, 0.8%, 1.6%, 4.0%, 4.2%, and 12.0% across EHMRG risk categories (1-4, 5A and 5B). The EHMRG score had a c-index of 0.73 (95% confidence interval [CI], 0.71-0.76) for 7-day mortality and 0.71 (95% CI, 0.70-0.73) for 30-day mortality, but lower c-statistics for other outcomes (0.61-0.67). The inclusion of natriuretic peptides to the EHMRG model improved prediction (Net Reclassification Improvement, 0.268; 95% CI, 0.173-0.363; P < 0.01) for 7-day mortality, as did the addition of the Canadian Triage and Acuity Scale (Net Reclassification Improvement, 0.111; 95% CI, 0.005-0.218; P = 0.04).

Conclusion

The EHMRG model exhibited moderate discriminative ability in a large population-based cohort of patients with AHF in the ED. Revision of the EHMRG score through factor inclusion and exclusion could improve the model’s performance.

Untapped potential of multicenter studies: a review of cardiovascular risk prediction models revealed inappropriate analyses and wide variation in reporting

BACKGROUND

Clinical prediction models are often constructed using multicenter databases. Such a data structure poses additional challenges for statistical analysis (clustered data) but offers opportunities for model generalizability to a broad range of centers. The purpose of this study was to describe properties, analysis, and reporting of multicenter studies in the Tufts PACE Clinical Prediction Model Registry and to illustrate consequences of common design and analyses choices.

METHODS

Fifty randomly selected studies that are included in the Tufts registry as multicenter and published after 2000 underwent full-text screening. Simulated examples illustrate some key concepts relevant to multicenter prediction research.

RESULTS

Multicenter studies differed widely in the number of participating centers (range 2 to 5473). Thirty-nine of 50 studies ignored the multicenter nature of data in the statistical analysis. In the others, clustering was resolved by developing the model on only one center, using mixed effects or stratified regression, or by using center-level characteristics as predictors. Twenty-three of 50 studies did not describe the clinical settings or type of centers from which data was obtained. Four of 50 studies discussed neither generalizability nor external validity of the developed model.

CONCLUSIONS

Regression methods and validation strategies tailored to multicenter studies are underutilized. Reporting on generalizability and potential external validity of the model lacks transparency. Hence, multicenter prediction research has untapped potential.

REGISTRATION

This review was not registered.

External Validation of the MEESSI Acute Heart Failure Risk Score: A Cohort Study

BACKGROUND

The MEESSI-AHF (Multiple Estimation of risk based on the Emergency department Spanish Score In patients with AHF) score was developed to predict 30-day mortality in patients presenting with acute heart failure (AHF) to emergency departments (EDs) in Spain. Whether it performs well in other countries is unknown.

OBJECTIVE

To externally validate the MEESSI-AHF score in another country.

DESIGN

Prospective cohort study. (ClinicalTrials.gov: NCT01831115).

SETTING

Multicenter recruitment of dyspneic patients presenting to the ED.

PARTICIPANTS

The external validation cohort included 1572 patients with AHF.

MEASUREMENTS

Calculation of the MEESSI-AHF score using an established model containing 12 independent risk factors.

RESULTS

Among 1572 patients with adjudicated AHF, 1247 had complete data that allowed calculation of the MEESSI-AHF score. Of these, 102 (8.2%) died within 30 days. The score predicted 30-day mortality with excellent discrimination (c-statistic, 0.80). Assessment of cumulative mortality showed a steep gradient in 30-day mortality over 6 predefined risk groups (0 patients in the lowest-risk group vs. 35 [28.5%] in the highest-risk group). Risk was overestimated in the high-risk groups, resulting in a Hosmer-Lemeshow P value of 0.022. However, after adjustment of the intercept, the model showed good concordance between predicted risks and observed outcomes (P = 0.23). Findings were confirmed in sensitivity analyses that used multiple imputation for missing values in the overall cohort of 1572 patients.

LIMITATIONS

External validation was done using a reduced model. Findings are specific to patients with AHF who present to the ED and are clinically stable enough to provide informed consent. Performance in patients with terminal kidney failure who are receiving long-term dialysis cannot be commented on.

CONCLUSION

External validation of the MEESSI-AHF risk score showed excellent discrimination. Recalibration may be needed when the score is introduced to new populations.

PRIMARY FUNDING SOURCE

The European Union, the Swiss National Science Foundation, the Swiss Heart Foundation, the Cardiovascular Research Foundation Basel, the University of Basel, and University Hospital Basel.

Design and rationale of a randomized trial: Using short stay units instead of routine admission to improve patient centered health outcomes for acute heart failure patients (SSU-AHF)

Nearly 85% of acute heart failure (AHF) patients who present to the emergency department (ED) with acute heart failure are hospitalized. Once hospitalized, within 30 days post-discharge, 27% of patients are re-hospitalized or die. Attempts to improve outcomes with novel therapies have all failed. The evidence for existing AHF therapies are poor: No currently used AHF treatment is known to improve long-term outcomes. ED treatment is largely the same today as 40 years ago. Admitting patients who could have avoided hospitalization may contribute to adverse outcomes. Hospitalization is not benign; patients enter a vulnerable phase post-discharge, at increased risk for morbidity and mortality. When hospitalization is able to be shortened or avoid completely, certain risks can be mitigated, including risk of medication errors, in-hospital falls, delirium, nosocomial infections, and other iatrogenic complications. Additionally, patients would prefer to be home, not hospitalized. Furthermore, hospitalization and re-hospitalization for AHF predominantly affects patients of lower socioeconomic status (SES). Avoiding hospitalization in patients who do not require admission may improve outcomes and quality of life, while reducing costs. Short stay unit (SSU: <24 h, also referred to as an 'observation unit') management of AHF may be effective for lower risk patients. However, to date there have only been small studies or retrospective analyses on the SSU management for AHF patients. In addition, SSU management has been considered 'cheating' for hospitals trying to avoid 30-day readmission penalties, as SSUs or observation units do not count as an admission. However, more recent analyses demonstrate differential use of observation status has not led to decreases in re-admission, suggesting this concern may be misplaced. Thus, we propose a robust clinical effectiveness trial to demonstrate the effectiveness of this patient-centered strategy.

Misconceptions in acute heart failure diagnosis and Management in the Emergency Department

INTRODUCTION

Acute heart failure (AHF) accounts for a significant number of emergency department (ED) visits, and the disease may present along a spectrum with a variety of syndromes.

OBJECTIVE

This review evaluates several misconceptions concerning heart failure evaluation and management in the ED, followed by several pearls.

DISCUSSION

AHF is a heterogeneous syndrome with a variety of presentations. Physicians often rely on natriuretic peptides, but the evidence behind their use is controversial, and these should not be used in isolation. Chest radiograph is often considered the most reliable imaging test, but bedside ultrasound (US) provides a more sensitive and specific evaluation for AHF. Diuretics are a foundation of AHF management, but in pulmonary edema, these medications should only be provided after vasodilator administration, such as nitroglycerin. Nitroglycerin administered in high doses for pulmonary edema is safe and effective in reducing the need for intensive care unit admission. Though classically dopamine is the first vasopressor utilized in patients with hypotensive cardiogenic shock, norepinephrine is associated with improved outcomes and lower mortality. Disposition is complex in patients with AHF, and risk stratification tools in conjunction with other assessments allow physicians to discharge patients safely with follow up.

CONCLUSION

A variety of misconceptions surround the evaluation and management of heart failure including clinical assessment, natriuretic peptide use, chest radiograph and US use, nitroglycerin and diuretics, vasopressor choice, and disposition. This review evaluates these misconceptions while providing physicians with updates in evaluation and management of AHF.

The Usefulness of the MEESSI Score for Risk Stratification of Patients With Acute Heart Failure at the Emergency Department

INTRODUCTION AND OBJECTIVES

The MEESSI scale stratifies acute heart failure (AHF) patients at the emergency department (ED) according to the 30-day mortality risk. We validated the MEESSI risk score in a new cohort of Spanish patients to assess its accuracy in stratifying patients by risk and to compare its performance in different settings.

METHODS

We included consecutive patients diagnosed with AHF in 30 EDs during January and February 2016. The MEESSI score was calculated for each patient. The c-statistic measured the discriminatory capacity to predict 30-day mortality of the full MEESSI model and secondary models. Further comparisons were made among subgroups of patients from university and community hospitals, EDs with high-, medium- or low-activity and EDs that recruited or not patients in the original MEESSI derivation cohort.

RESULTS

We analyzed 4711 patients (university/community hospitals: 3811/900; high-/medium-/low-activity EDs: 2695/1479/537; EDs participating/not participating in the previous MEESSI derivation study: 3892/819). The distribution of patients according to the MEESSI risk categories was: 1673 (35.5%) low risk, 2023 (42.9%) intermediate risk, 530 (11.3%) high risk and 485 (10.3%) very high risk, with 30-day mortality of 2.0%, 7.8%, 17.9%, and 41.4%, respectively. The c-statistic for the full model was 0.810 (95%CI, 0.790-0.830), ranging from 0.731 to 0.785 for the subsequent secondary models. The discriminatory capacity of the MEESSI risk score was similar among subgroups of hospital type, ED activity, and original recruiter EDs.

CONCLUSIONS

The MEESSI risk score successfully stratifies AHF patients at the ED according to the 30-day mortality risk, potentially helping clinicians in the decision-making process for hospitalizing patients.

Prediction of Early Adverse Events in Emergency Department Patients With Acute Heart Failure: A Systematic Review

BACKGROUND

Acute heart failure (AHF) accounts for a substantial proportion of Emergency Department (ED) visits and hospitalizations. Previous studies have shown that emergency physicians' clinical gestalt is not sufficient to stratify patients with AHF into severe and requiring hospitalization vs nonsevere and safe to be discharged. Various prognostic algorithms have been developed to risk-stratify patients with AHF, however there is no consensus as to the best-performing risk assessment tool in the ED.

METHODS

A systematic review of Medline, PubMed, and Embase up to May 2016 was conducted using established methods. Major cardiology and emergency medicine conference proceedings from 2010 to 2016 were also screened. Two independent reviewers identified studies that evaluated clinical risk scores in adult (ED) patients with AHF, with risk prognostication for mortality or significant morbidity within 7-30 days. Studies included patients who were discharged or admitted.

RESULTS

The systematic review search generated 2950 titles that were screened according to title and abstract. Nine articles, describing 6 risk prediction tools met full inclusion criteria, however, prognostic performance and ease of bedside application is limited for most. Because of clinical heterogeneity in the prognostic tools and study outcomes, a meta-analysis was not performed.

CONCLUSIONS

Several risk scores exist for predicting short-term mortality or morbidity in ED patients with AHF. No single risk tool is clearly superior, however, the Emergency Heart Failure Mortality Risk Grade might aid in prognostication of mortality and the Ottawa Heart Failure Risk Score might provide useful prognostic information in patients suitable for ED discharge.

What's Next for Acute Heart Failure Research?

Each year over one million patients with acute heart failure (AHF) present to a United States emergency department (ED). The vast majority are hospitalized for further management. The length of stay and high postdischarge event rate in this cohort have changed little over the past decade. Therapeutic trials have failed to yield substantive improvement in postdischarge outcomes; subsequently, AHF care has changed little in the past 40 years. Prior research studies have been fragmented as either "inpatient" or "ED-based." Recognizing the challenges in identification and enrollment of ED patients with AHF, and the lack of robust evidence to guide management, an AHF clinical trials network was developed. This network has demonstrated, through organized collaboration between cardiology and emergency medicine, that many of the hurdles in AHF research can be overcome. The development of a network that supports the collaboration of acute care and HF researchers, combined with the availability of federally funded infrastructure, will facilitate more efficient conduct of both explanatory and pragmatic trials in AHF. Yet many important questions remain, and in this document our group of emergency medicine and cardiology investigators have identified four high-priority research areas.

Short-Term Outcomes and Factors Associated With Adverse Events Among Adults Discharged From the Emergency Department After Treatment for Acute Heart Failure

BACKGROUND

Although 80% of patients with heart failure seen in the emergency department (ED) are admitted, less is known about short-term outcomes and demand for services among discharged patients.

METHODS AND RESULTS

We examined adult members of a large integrated delivery system who visited an ED for acute heart failure and were discharged from January 1, 2013, through September 30, 2014. The primary outcome was a composite of repeat ED visit, hospital admission, or death within 7 days of discharge. We identified multivariable baseline patient-, provider-, and facility-level factors associated with adverse outcomes within 7 days of ED discharge using logistic regression. Among 7614 patients, mean age was 77.2 years, 51.9% were women, and 28.4% were people of color. Within 7 days of discharge, 75% had outpatient follow-up (clinic, telephone, or e-mail), 7.1% had an ED revisit, 4.7% were hospitalized, and 1.2% died. Patients who met the primary outcome were more likely to be older, smokers, have a history of hemorrhagic stroke, hypothyroidism, and dementia, and less likely to be treated in a facility with an observation unit. In multivariable analysis, higher comorbidity scores and history of smoking were associated with a higher odds of the primary outcome, whereas treatment in a facility with an observation unit and presence of outpatient follow-up within 7 days were associated with a lower odds.

CONCLUSIONS

We identified selected hospital and patient characteristics associated with short-term adverse outcomes. Further understanding of these factors may optimize safe outpatient management in ED-treated patients with heart failure.

Creation and validation of the acute heart failure risk score: AHFRS

Our aims were to create and validate a clinical decision rule to assess severity in acute heart failure. We conducted a prospective cohort study of patients with symptoms of acute heart failure who attended the emergency departments (EDs) of three hospitals between April 2011 and April 2013. The following data were collected on arrival to or during the stay in the ED: baseline severity of symptoms; presence of decompensated comorbidities; number of hospital admissions/visits to EDs for acute heart failure during the previous 24 months; triggers of the exacerbation; clinical signs and symptoms; results of ancillary tests requested in the ED; treatments prescribed; and response to the initial treatment in the ED. The main outcome was poor course during the acute phase, in-hospital for admitted patients and during the first week following the ED visit for discharged patients, this being a composite endpoint that included death, admission to an intensive care unit, need for invasive mechanical ventilation, cardiac arrest and use of non-invasive mechanical ventilation. Multivariate logistic regression models were developed. Predictors of poor course in acute heart failure were oedema on chest radiography, visits to the ED and/or admissions in the previous two years, and levels of glycemia and blood urea nitrogen (areas under the curve of 0.83 in the derivation sample, and 0.82 in the validation sample). Four clinical predictors available in the ED can be used to create a simple score to predict poor course in acute heart failure.Clinical Trials.gov ID: NCT02437058.

Acute Heart Failure in the Emergency Department: the SAFE-SIMEU Epidemiological Study

BACKGROUND

Patients with acute heart failure (AHF) have high rates of attendance to emergency departments (EDs), with significant health care costs.

OBJECTIVES

We aimed to describe the clinical characteristics of patients attending Italian EDs for AHF and their diagnostic and therapeutic work-up.

METHODS

We carried out a retrospective analysis on 2683 cases observed in six Italian EDs for AHF (January 2011 to June 2012).

RESULTS

The median age of patients was 84 years (interquartile range 12), with females accounting for 55.8% of cases (95% confidence interval [CI] 53.5-57.6%). A first episode of AHF was recorded in 55.3% (95% CI 55.4-57.2%). Respiratory disease was the main precipitating factor (approximately 30% of cases), and multiple comorbidities were recorded in > 50% of cases (history of acute coronary syndrome, chronic obstructive pulmonary disease, diabetes, chronic kidney disease, valvular heart disease). The treatment was based on oxygen (69.7%; 67.9-71.5%), diuretics (69.2%; 67.9-71.5%), nitroglycerin (19.7%; 18.3-21.4%), and noninvasive ventilation (15.2%; 13.8-16.6%). Death occurred within 6 h in 2.5% of cases (2.0-3.1%), 6.4% (5.5-7.3%) were referred to the care of their general practitioners within a few hours from ED attendance or after short-term (< 24 h) observation 13.9% (12.6-15.2%); 60.4% (58.5-62.2%) were admitted to the hospital, and 16.8% (15.4-18.3%) were cared for in intensive care units according to disease severity.

CONCLUSIONS

Our study reporting the "real-world" clinical activity indicates that subjects attending the Italian EDs for AHF are rather different from those reported in international registries. Subjects are older, with a higher proportion of females, and high prevalence of cardiac and noncardiac comorbidities.

Cardiovascular Conditions in the Observation Unit: Beyond Chest Pain

The first emergency department observation units (EDOUs) focused on chest pain and potential acute coronary syndromes. However, most EDOUs now cover multiple other conditions that lend themselves to protocolized, aggressive diagnostic and therapeutic regimens. In this article, the authors discuss the management of 4 cardiovascular conditions that have been successfully deployed in EDOUs around the country.

Anemia considerations when assessing natriuretic peptide levels in ED patients

INTRODUCTION

The incidence of heart failure (HF) has reached epidemic levels in western populations, and the majority of these patients are admitted to hospitals through the emergency department (ED). We aimed to aid clinicians assessing natriuretic peptide (NP) levels in cases with suspected HF. In this study, we investigated the effect of anemia on amino-terminal pro-BNP (NT-proBNP) and on B-type natriuretic peptide (BNP) levels.

METHODS

This retrospective study examined patients who were admitted to the ED with suspected HF. After admission, the treating physician requested complete blood count and creatinine tests with NT-proBNP (n=2.637) or BNP (n=11.159). The exclusion criteria were used to minimize the factors that could affect the NT-proBNP and BNP results. We examined the data using the Mann-Whitney U test, Chi-square test, Spearman correlation test, and multivariate linear regression analyses.

RESULTS

The NT-proBNP and BNP levels were statistically higher in the groups with anemia (p=0.016 and p=0.009, respectively). There was a statistically significant negative correlation between hemoglobin and NP levels (r=-0.272, p<0.001 for NT-proBNP and r=-0.179, p<0.001 for BNP). The results indicated that advanced age and low hemoglobin levels were significantly associated with the increase in NT-proBNP (p=0.024 and p=0.004, respectively). Advanced age, low hemoglobin and low GFR-MDRD levels were significantly associated with the increase in BNP (p<0.001, p=0.002 and p=0.013, respectively).

DISCUSSION

The data suggest that clinicians examining patients admitted to the ED with suspected HF should consider that anemia could lead to increases in NT-proBNP and BNP levels.