Identification of Emergency Department Patients With Acute Heart Failure at Low Risk for 30-Day Adverse Events: The STRATIFY Decision Tool

Blood pressure and heart failure: focused on treatment

Heart failure (HF) remains a significant global health burden, and hypertension is known to be the primary contributor to its development. Although aggressive hypertension treatment can prevent heart changes in at-risk patients, determining the optimal blood pressure (BP) targets in cases diagnosed with HF is challenging owing to insufficient evidence. Notably, hypertension is more strongly associated with HF with preserved ejection fraction than with HF with reduced ejection fraction. Patients with acute hypertensive HF exhibit sudden symptoms of acute HF, especially those manifested with severely high BP; however, no specific vasodilator therapy has proven beneficial for this type of acute HF. Since the majority of medications used to treat HF contribute to lowering BP, and BP remains one of the most important hemodynamic markers, targeted BP management is very concerned in treatment strategies. However, no concrete guidelines exist, prompting a trend towards optimizing therapies to within tolerable ranges, rather than setting explicit BP goals. This review discusses the connection between BP and HF, explores its pathophysiology through clinical studies, and addresses its clinical significance and treatment targets.

Acute Heart Failure: From The Emergency Department to the Intensive Care Unit

Acute heart failure (AHF) is a frequent cause of hospitalization around the world and is associated with high in-hospital and post-discharge morbidity and mortality. This review summarizes data on diagnosis and management of AHF from the emergency department to the intensive care unit. While more evidence is needed to guide risk stratification and care of patients with AHF, hospitalization is a key opportunity to optimize evidence-based medical therapy for heart failure. Close linkage to outpatient care is essential to improve post-hospitalization outcomes.

Clinical Review of Hypertensive Acute Heart Failure

Although acute heart failure (AHF) is a common disease associated with significant symptoms, morbidity and mortality, the diagnosis, risk stratification and treatment of patients with hypertensive acute heart failure (H-AHF) still remain a challenge in modern medicine. Despite great progress in diagnostic and therapeutic modalities, this disease is still accompanied by a high rate of both in-hospital (from 3.8% to 11%) and one-year (from 20% to 36%) mortality. Considering the high rate of rehospitalization (22% to 30% in the first three months), the treatment of this disease represents a major financial blow to the health system of each country. This disease is characterized by heterogeneity in precipitating factors, clinical presentation, therapeutic modalities and prognosis. Since heart decompensation usually occurs quickly (within a few hours) in patients with H-AHF, establishing a rapid diagnosis is of vital importance. In addition to establishing the diagnosis of heart failure itself, it is necessary to see the underlying cause that led to it, especially if it is de novo heart failure. Given that hypertension is a precipitating factor of AHF and in up to 11% of AHF patients, strict control of arterial blood pressure is necessary until target values are reached in order to prevent the occurrence of H-AHF, which is still accompanied by a high rate of both early and long-term mortality.

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.

The significance of historical troponin elevation in acute heart failure: Not as reassuring as previously assumed

BACKGROUND

Historical cardiac troponin (cTn) elevation is commonly interpreted as lessening the significance of current cTn elevations at presentation for acute heart failure (AHF). Evidence for this practice is lacking. Our objective was to determine the incremental prognostic significance of historical cTn elevation compared to cTn elevation and ischemic heart disease (IHD) history at presentation for AHF.

METHODS

A total of 341 AHF patients were prospectively enrolled at five sites. The composite primary outcome was death/cardiopulmonary resuscitation, mechanical cardiac support, intubation, new/emergent dialysis, and/or acute myocardial infarction (AMI)/percutaneous coronary intervention (PCI)/coronary artery bypass grafting (CABG) at 90 days. Secondary outcomes were 30-day AMI/PCI/CABG and in-hospital AMI. Logistic regression compared outcomes versus initial emergency department (ED) cTn, the most recent electronic medical record cTn, estimated glomerular filtration rate, age, left ventricular ejection fraction, and IHD history (positive, negative by prior coronary workup, or unknown/no prior workup).

RESULTS

Elevated cTn occurred in 163 (49%) patients, 80 (23%) experienced the primary outcome, and 29 had AMI (9%). cTn elevation at ED presentation, adjusted for historical cTn and other covariates, was associated with the primary outcome (adjusted odds ratio [aOR] 2.39, 95% confidence interval [CI] 1.30-4.38), 30-day AMI/PCI/CABG, and in-hospital AMI. Historical cTn elevation was associated with greater odds of the primary outcome when IHD history was unknown at ED presentation (aOR 5.27, 95% CI 1.24-21.40) and did not alter odds of the outcome with known positive (aOR 0.74, 95% CI 0.33-1.70) or negative IHD history (aOR 0.79, 95% CI 0.26-2.40). Nevertheless, patients with elevated ED cTn were more likely to be discharged if historical cTn was also elevated (78% vs. 32%, p = 0.025).

CONCLUSIONS

Historical cTn elevation in AHF patients is a harbinger of worse outcomes for patients who have not had a prior IHD workup and should prompt evaluation for underlying ischemia rather than reassurance for discharge. With known IHD history, historical cTn elevation was neither reassuring nor detrimental, failing to add incremental prognostic value to current cTn elevation alone.

Physicians' Perceptions of Clinical Decision Support to Treat Patients With Heart Failure in the ED

Importance

Clinical decision support (CDS) could help emergency department (ED) physicians treat patients with heart failure (HF) by estimating risk, collating relevant history, and assisting with medication prescribing if physicians' perspectives inform its design and implementation.

Objective

To evaluate CDS usability and workflow integration in the hands of ED physician end users who use it in clinical practice.

Design, Setting, and Participants

This mixed-methods qualitative study administered semistructured interviews to ED physicians from 2 community EDs of Kaiser Permanente Northern California in 2023. The interview guide, based on the Usability Heuristics for User Interface Design and the Sociotechnical Environment models, yielded themes used to construct an electronic survey instrument sent to all ED physicians.

Main Outcomes and Measures

Main outcomes were physicians' perceptions of using CDS to complement clinical decision-making, usability, and integration into ED clinical workflow.

Results

Seven key informant physicians (5 [71.4%] female, median [IQR] 15.0 [9.5-15.0] years in practice) were interviewed and survey responses from 51 physicians (23 [45.1%] female, median [IQR] 14.0 [9.5-17.0] years in practice) were received from EDs piloting the CDS intervention. Response rate was 67.1% (51 of 76). Physicians suggested changes to CDS accessibility, functionality, and workflow integration. Most agreed that CDS would improve patient care and fewer than half of physicians expressed hesitation about their capacity to consistently comply with its recommendations, citing workload concerns. Physicians preferred a passive prompt that encouraged, but did not mandate, interaction with the CDS.

Conclusions and Relevance

In this qualitative study of physicians who were using a novel CDS intervention to assist with ED management of patients with acute HF, several opportunities were identified to improve usability as well as several key barriers and facilitators to CDS implementation.

Hospital at Home as a Treatment Strategy for Worsening Heart Failure

Hospital at home (HaH) is an innovative care model that may be particularly suited for heart failure (HF). Outpatient visits and inpatient care have been the 2 traditional settings for HF care, yet may not match the social and medical needs of patients at all times. Alternative models such as HaH may represent an effective and patient-centered option for select patients with worsening HF. To date, limited research in HF and other disease states has supported HaH as being safe and lower cost than traditional inpatient admission. Supporting HaH are new payment structures, such as Medicare's Acute Hospital Care at Home waiver program. In combination with outpatient visits, outpatient intravenous diuretic clinics, inpatient care, and cardiac intensive care, HaH could be a core component of a comprehensive care model with the potential to match resource utilization with the needs of patients across the spectrum of HF severity, and improve patient outcomes.

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.

Construction of a web-based dynamic nomogram for predicting the prognosis in acute heart failure

AIMS

The early identification and appropriate management may provide clinically meaningful and substained benefits in patients with acute heart failure (AHF). This study aimed to develop an integrative nomogram with myocardial perfusion imaging (MPI) for predicting the risk of all-cause mortality in AHF patients.

METHODS AND RESULTS

Prospective study of 147 patients with AHF who received gated MPI (59.0 [47.5, 68.0] years; 78.2% males) were enrolled and followed for the primary endpoint of all-cause mortality. We analysed the demographic information, laboratory tests, electrocardiogram, and transthoracic echocardiogram by the least absolute shrinkage and selection operator (LASSO) regression for selection of key features. A multivariate stepwise Cox analysis was performed to identify independent risk factors and construct a nomogram. The predictive values of the constructed model were compared by Kaplan-Meier curve, area under the curves (AUCs), calibration plots, continuous net reclassification improvement, integrated discrimination improvement, and decision curve analysis. The 1, 3, and 5 year cumulative rates of death were 10%, 22%, and 29%, respectively. Diastolic blood pressure [hazard ratio (HR) 0.96, 95% confidence interval (CI) 0.93-0.99; P = 0.017], valvular heart disease (HR 3.05, 95% CI 1.36-6.83; P = 0.007), cardiac resynchronization therapy (HR 0.37, 95% CI 0.17-0.82; P = 0.014), N-terminal pro-B-type natriuretic peptide (per 100 pg/mL; HR 1.02, 95% CI 1.01-1.03; P < 0.001), and rest scar burden (HR 1.03, 95% CI 1.01-1.06; P = 0.008) were independent risk factors for patients with AHF. The cross-validated AUCs (95% CI) of nomogram constructed by diastolic blood pressure, valvular heart disease, cardiac resynchronization therapy, N-terminal pro-B-type natriuretic peptide, and rest scar burden were 0.88 (0.73-1.00), 0.83 (0.70-0.97), and 0.79 (0.62-0.95) at 1, 3, and 5 years, respectively. Continuous net reclassification improvement and integrated discrimination improvement were also observed, and the decision curve analysis identified the greater net benefit of the nomogram across a wide range of threshold probabilities (0-100% at 1 and 3 years; 0-61% and 62-100% at 5 years) compared with dismissing the included factors or using either factor alone.

CONCLUSIONS

A predictive nomogram for the risk of all-cause mortality in patients with AHF was developed and validated in this study. The nomogram incorporated the rest scar burden by MPI is highly predictive, and may help to better stratify clinical risk and guide treatment decisions in patients with AHF.

A Suggested Model for the Vulnerable Phase of Heart Failure: Assessment of Risk Factors, Multidisciplinary Monitoring, Cardiac Rehabilitation, and Addressing the Social Determinants of Health

The vulnerable phase (VP) of heart failure (HF) is 30 to 90 days after hospital discharge and is associated with increased rehospitalization and mortality rates. The pathophysiological mechanism that drives the VP is due to the progressive increase in left ventricular filling pressure, which can cause hemodynamic congestion and long-term multiorgan injury. Our team analyzed English-written, peer-reviewed research through PubMed from 2018 to 2022, to gather current information on the VP and generate a multipronged approach toward the assessment and intervention of patients with posthospitalization HF. It is our opinion that a structured approach using remote vital monitoring and risk-stratifying tools will be best to identify patients at risk for decompensatory HF during the VP. Medical management can then be targeted toward these high-risk patients by using an organized multidisciplinary team and a disease management program, which includes remote patient-monitoring systems, addressing social determinants of health, and cardiac rehabilitation, to improve rehospitalization and mortality rates.

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.

Barriers and Opportunities Regarding Implementation of a Machine Learning-Based Acute Heart Failure Risk Stratification Tool in the Emergency Department

Hospital admissions for patients with acute heart failure (AHF) remain high. There is an opportunity to improve alignment between patient risk and admission decision. We recently developed a machine learning (ML)-based model that stratifies emergency department (ED) patients with AHF based on predicted risk of a 30-day severe adverse event. Prior to deploying the algorithm and paired clinical decision support, we sought to understand barriers and opportunities regarding successful implementation. We conducted semi-structured interviews with eight front-line ED providers and surveyed 67 ED providers. Audio-recorded interviews were transcribed and analyzed using thematic analysis, and we had a 65% response rate to the survey. Providers wanted decision support to be streamlined into workflows with minimal disruptions. Most providers wanted assistance primarily with ED disposition decisions, and secondarily with medical management and post-discharge follow-up care. Receiving feedback on patient outcomes after risk tool use was seen as an opportunity to increase acceptance, and few providers (<10%) had significant hesitations with using an ML-based tool after education on its use. Engagement with key front-line users on optimal design of the algorithm and decision support may contribute to broader uptake, acceptance, and adoption of recommendations for clinical decisions.

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.

Incidence of Timely Outpatient Follow-Up Care After Emergency Department Encounters for Acute Heart Failure

BACKGROUND

Patients who are discharged from the emergency department (ED) after an encounter for acute heart failure are at high risk for return hospitalization. These patients may benefit from timely outpatient follow-up care to reassess volume status, adjust medications, and reinforce self-care strategies. This study examines the incidence of outpatient follow-up care after ED encounters for acute heart failure and describes patient characteristics associated with obtaining timely follow-up care.

METHODS

We conducted a retrospective cohort study using an administrative claims database for a large US commercial insurer, from January 1, 2012 to June 30, 2019. Participants included adult patients discharged from the ED with principal diagnosis of acute heart failure. The primary outcome was obtaining an in-person outpatient clinic visit for heart failure within 30 days. We also examined the competing risk of all-cause hospitalization within 30 days and without an intervening outpatient clinic visit. We estimated competing risk regression models to identify patient characteristics associated with obtaining outpatient follow-up and report cause-specific hazard ratios.

RESULTS

The cohort included 52 732 patients, with mean age of 73.9 years (95% CI, 73.8-74.0) and 27 395 (52.0% [95% CI, 51.5-52.4]) female patients. Within 30 days of the ED encounter, 12 279 (23.2%) patients attended an outpatient clinic visit for heart failure, with 8382 (15.9%) patients hospitalized before they could obtain an outpatient clinic visit. In the adjusted analysis, patients that were younger, women, reporting non-Hispanic Black race, and had fewer previous clinic visits were less likely to obtain outpatient follow-up care.

CONCLUSIONS

Few patients obtain timely outpatient follow-up after ED visits for heart failure, although nearly 20% require hospitalization within 30 days. Improved transitions following discharge from the ED may represent an opportunity to improve outcomes for patients with acute heart failure.

Data standards for heart failure: the European Unified Registries for Heart Care Evaluation and Randomized Trials (EuroHeart)

Standardized data definitions are essential for assessing the quality of care and patient outcomes in observational studies and randomized controlled trials. The European Unified Registries for Heart Care Evaluation and Randomized Trials (EuroHeart) project of the European Society of Cardiology (ESC) aims to create contemporary pan-European data standards for cardiovascular diseases, including heart failure (HF). We followed the EuroHeart methodology for cardiovascular data standard development. A Working Group including experts in HF registries, representatives from the Heart Failure Association of the ESC, and the EuroHeart was formed. Using Embase and Medline (2016-21), we conducted a systematic review of the literature on data standards, registries, and trials to identify variables pertinent to HF. A modified Delphi method was used to reach a consensus on the final set of variables. For each variable, the Working Group developed data definitions and agreed on whether it was mandatory (Level 1) or additional (Level 2). In total, 84 Level 1 and 79 Level 2 variables were selected for nine domains of HF care. These variables were reviewed by an international Reference Group with the Level 1 variables providing the dataset for registration of patients with HF on the EuroHeart IT platform. By means of a structured process and interaction with international stakeholders, harmonized data standards for HF have been developed. In the context of the EuroHeart, this will facilitate quality improvement, international observational research, registry-based randomized trials, and post-marketing surveillance of devices and pharmacotherapies across Europe.

A multidisciplinary approach to heart failure care in the hospital: improving the patient journey

Despite advancements in care for patients with heart failure (HF), morbidity and mortality remain high. Hospitalizations and readmissions for HF have been the focus of significant attention among health care providers and payers, with an eye towards reducing health care costs. However, considerable variability exists with regard to inpatient workflows and management for patients with HF, which represents a significant opportunity to improve care. Here we provide a summary of optimal inpatient management strategies for HF, focusing on the multidisciplinary team of emergency medicine providers, admitting hospitalists, cardiovascular consultants, pharmacists, nurses, and social workers. The patient journey serves as the template for this review article, from the initial presentation in the emergency department, to decongestion and stabilization, optimization of guideline-directed medical therapy, and discharge and appropriate disposition. Lastly, this review aims not to be proscriptive but rather to provide best practices that are clinically relevant and actionable, with the goal of improving care for patients during the sentinel hospitalization for HF.

Risk adjusted 30‐day mortality and serious adverse event rates among a large, multi‐center cohort of emergency department patients with acute heart failure

Background

Admission rates for emergency department (ED) patients with acute heart failure (AHF) remain elevated. Use of a risk stratification tool could improve disposition decision making by identifying low‐risk patients who may be safe for outpatient management.

Methods

We performed a secondary analysis of a retrospective, multi‐center cohort of 26,189 ED patients treated for AHF from January 1, 2017 to December 31, 2018. We applied a 30‐day risk model we previously developed and grouped patients into 4 categories (low, low/moderate, moderate, and high) of predicted 30‐day risk of a serious adverse event (SAE). SAE consisted of death or cardiopulmonary resuscitation (CPR), intra‐aorta balloon pump, endotracheal intubation, renal failure requiring dialysis, or acute coronary syndrome. We measured the 30‐day mortality and composite SAE rates among patients by risk category according to ED disposition: direct discharge, discharge after observation, and hospital admission.

Results

The observed 30‐day mortality and total SAE rates were less than 1% and 2%, respectively, among 25% of patients in the low and low/moderate risk groups. These rates did not vary significantly by ED disposition. An additional 23% of patients were moderate risk and experienced an approximate 2% 30‐day mortality rate.

Conclusion

Use of a risk stratification tool could help identify lower risk AHF patients who may be appropriate for ED discharge. These findings will help inform prospective testing to determine how this risk tool can augment ED decision making.

Troponin is unrelated to outcomes in heart failure patients discharged from the emergency department

Background

Prior data has demonstrated increased mortality in hospitalized patients with acute heart failure (AHF) and troponin elevation. No data has specifically examined the prognostic significance of troponin elevation in patients with AHF discharged after emergency department (ED) management.

Objective

Evaluate the relationship between troponin elevation and outcomes in patients with AHF who are treated and released from the ED.

Methods

This was a secondary analysis of the Get with the Guidelines to Reduce Disparities in AHF Patients Discharged from the ED (GUIDED‐HF) trial, a randomized, controlled trial of ED patients with AHF who were discharged. Patients with elevated conventional troponin not due to acute coronary syndrome (ACS) were included. Our primary outcome was a composite endpoint: time to 30‐day cardiovascular death and/or heart failure‐related events.

Results

Of the 491 subjects included in the GUIDED‐HF trial, 418 had troponin measured during the ED evaluation and 66 (16%) had troponin values above the 99th percentile. Median age was 63 years (interquartile range, 54‐70), 62% (n = 261) were male, 63% (n = 265) were Black, and 16% (n = 67) experienced our primary outcome. There were no differences in our primary outcome between those with and without troponin elevation (12/66, 18.1% vs 55/352, 15.6%; P = 0.60). This effect was maintained regardless of assignment to usual care or the intervention arm. In multivariable regression analysis, there was no association between our primary outcome and elevated troponin (hazard ratio, 1.00; 95% confidence interval,  0.49–2.01, P = 0.994)

Conclusion

If confirmed in a larger cohort, these findings may facilitate safe ED discharge for a group of patients with AHF without ACS when an elevated troponin is the primary reason for admission.

Hemodynamic profiles by non-invasive monitoring of cardiac index and vascular tone in acute heart failure patients in the emergency department: External validation and clinical outcomes

Background

Non-invasive finger-cuff monitors measuring cardiac index and vascular tone (SVRI) classify emergency department (ED) patients with acute heart failure (AHF) into three otherwise-indistinguishable subgroups. Our goals were to validate these “hemodynamic profiles” in an external cohort and assess their association with clinical outcomes.

Methods

AHF patients (n = 257) from five EDs were prospectively enrolled in the validation cohort (VC). Cardiac index and SVRI were measured with a ClearSight finger-cuff monitor (formerly NexFin, Edwards Lifesciences) as in a previous study (derivation cohort, DC, n = 127). A control cohort (CC, n = 127) of ED patients with sepsis was drawn from the same study as the DC. K-means cluster analysis previously derived two-dimensional (cardiac index and SVRI) hemodynamic profiles in the DC and CC (k = 3 profiles each). The VC was subgrouped de novo into three analogous profiles by unsupervised K-means consensus clustering. PERMANOVA tested whether VC profiles 1–3 differed from profiles 1–3 in the DC and CC, by multivariate group composition of cardiac index and vascular tone.

Profiles in the VC were compared by a primary outcome of 90-day mortality and a 30-day ranked composite secondary outcome (death, mechanical cardiac support, intubation, new/emergent dialysis, coronary intervention/surgery) as time-to-event (survival analysis) and binary events (odds ratio, OR). Descriptive statistics were used to compare profiles by two validated risk scores for the primary outcome, and one validated score for the secondary outcome.

Results

The VC had median age 60 years (interquartile range {49–67}), and was 45% (n = 116) female. Multivariate profile composition by cardiac index and vascular tone differed significantly between VC profiles 1–3 and CC profiles 1–3 (p = 0.001, R² = 0.159). A difference was not detected between profiles in the VC vs. the DC (p = 0.59, R² = 0.016).

VC profile 3 had worse 90-day survival than profiles 1 or 2 (HR = 4.8, 95%CI 1.4–17.1). The ranked secondary outcome was more likely in profile 1 (OR = 10.0, 1.2–81.2) and profile 3 (12.8, 1.7–97.9) compared to profile 2. Diabetes prevalence and blood urea nitrogen were lower in the high-risk profile 3 (p<0.05). No significant differences between profiles were observed for other clinical variables or the 3 clinical risk scores.

Conclusions

Hemodynamic profiles in ED patients with AHF, by non-invasive finger-cuff monitoring of cardiac index and vascular tone, were replicated de novo in an external cohort. Profiles showed significantly different risks of clinically-important adverse patient outcomes.

A Survival Prediction for Acute Heart Failure Patients via Web-Based Dynamic Nomogram with Internal Validation: A Prospective Cohort Study

Purpose

The current study aimed to develop a convenient and accurate prognostic dynamic nomogram model for the risk of all-cause death in acute heart failure (AHF) patients that incorporates clinical characteristics including N-terminal pro-brain natriuretic peptide (NT-pro BNP) and growth stimulation expresses gene 2 protein (ST2).

Patients and Methods

We prospectively studied 537 consecutive AHF patients and derived a clinical prediction model. The least absolute shrinkage and selection operator regression model combined with clinical characteristics were used for dimensional reduction and feature selection. Multivariate Cox proportional hazard analysis and “Dynnom” package were used to build the dynamic nomogram for prediction of 1-,2-,and 5-year overall survival for AHF. With bootstrap validation, the time-dependent concordance index (C-index) and calibration curves were used to assess predictive discrimination and accuracy. The contributions of NT-pro BNP and ST2 to the nomogram were evaluated using integrated discrimination improvement (IDI) and net reclassification improvement (NRI), while decision curve analysis (DCA) was used to assess clinical value.

Results

Patients were randomly divided into derivation (74.9%, n=402) and validation (25.1%, n=135) cohorts. Optimal independent prognostic factors for 1-,2-, and 5-year all-cause mortality were BS-ACMR (B: NT-pro BNP; S: ST2; A: age; C: complete right bundle branch block; M: mean arterial pressure; and R: red cell distribution width >14.5%); these were incorporated into the dynamic nomogram (https://bs-acmr-nom.shinyapps.io/dynnomapp/) with bootstrap validation. The C-indexes in the derivation (0.793) and validation (0.782) cohorts were consistent with comparable performance parameters. The calibration curve showed good agreement between the nomogram-predicted and actual survival. Adding NT-pro BNP and ST2 provided a significant net benefit and improved performance over other less adequate schemes in terms of DCA of survival probability compared to those neglecting either of these two factors.

Conclusion

The study constructed a dynamic BS-ACMR nomogram, which is a convenient, practical and effective clinical decision-making tool for providing accurate prognosis in AHF patients.

Rivaroxaban Once-Daily vs. Dose-Adjusted Vitamin K Antagonist on Biomarkers in Acute Decompensated Heart Failure and Atrial Fibrillation (ROAD HF-AF): Rationale and Design of an Investigator-Initiated Multicenter Randomized Prospective Open-Labeled Pilot Clinical Study

Background: Clinical trials of non-vitamin K antagonist oral anticoagulants (NOACs) in patients with chronic heart failure and atrial fibrillation (AF) have demonstrated reduced risks of stroke and bleeding compared with vitamin K antagonists (VKAs). Here, we aim to assess the clinical efficacy and safety of rivaroxaban, a NOAC, compared with warfarin, a VKA, and the effects of rivaroxaban on cardiovascular biomarkers in patients with acute decompensated heart failure (ADHF) with reduced ejection fraction (≤40%) and AF. Methods: Rivaroxaban Once-daily vs. dose-adjusted vitamin K antagonist on biomarkers in Acute Decompensated Heart Failure and Atrial Fibrillation (ROAD HF-AF) is a randomized, open-labeled, controlled, prospective, multicenter pilot study designed to assess cardiovascular biomarkers and the safety of rivaroxaban (20 or 15 mg in patients with creatinine clearance 30-49 mL/min per day) compared with VKA (target international normalized range: 2-3) in 150 patients hospitalized with ADHF and AF. The primary endpoint is the change in circulating high-sensitivity cardiac troponin (hsTn) during hospitalization. The secondary endpoints are bleeding, hospital stay duration, in-hospital mortality, and changes in cardiovascular, renal, and thrombosis biomarkers. Patients will be followed for 180 days. Conclusion: We hypothesize that rivaroxaban will reduce myocardial injury and hemodynamic stress, as reflected by the biomarker status, within 72 h in patients with ADHF and AF, compared with VKA. We hope to facilitate future biomarker-based, large-scale outcome trials using NOACs in patients with ADHF and AF, based on the results of this multicenter, randomized, controlled study.

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.

Congestion in Patients with Advanced Heart Failure: Assessment and Treatment

Heart failure (HF) is characterized by frequent hospital admissions due to acute decompensation and shortened life span with a progressive clinical course leading to an advanced stage where traditional therapies become ineffective. Due to aging of the population and improved therapies, only a small of proportion of patients with advanced HF are candidates for surgical treatments, such as mechanical circulatory support or heart transplantation. In most cases, prompt identification and management of congestion is paramount to improving symptoms and quality of life and avoiding progression to severe multiorgan dysfunction and death.

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.

Acute heart failure in elderly patients: a review of invasive and non-invasive management

Acute heart failure (AHF) is a major cause of unplanned hospitalisations in the elderly and is associated with high mortality. Its prevalence has grown in the last years due to population aging and longer life expectancy of chronic heart failure patients. Although international societies have provided guidelines for the management of AHF in the general population, scientific evidence for geriatric patients is often lacking, as these are underrepresented in clinical trials. Elderly have a different risk profile with more comorbidities, disability, and frailty, leading to increased morbidity, longer recovery time, higher readmission rates, and higher mortality. Furthermore, therapeutic options are often limited, due to unfeasibility of invasive strategies, mechanical circulatory support and cardiac transplantation. Thus, the in-hospital management of AHF should be tailored to each patient's clinical situation, cardiopulmonary condition and geriatric assessment. Palliative care should be considered in some cases, in order to avoid unnecessary diagnostics and/or treatments. After discharge, a strict follow-up through outpatient clinic or telemedicine is can improve quality of life and reduce rehospitalisation rates. The aim of this review is to offer an insight on current literature and provide a clinically oriented, patient-tailored approach regarding assessment, treatment and follow-up of elderly patients admitted for AHF.

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.

Assessment of acute heart failure prognosis: the promising role of prognostic models and biomarkers

Numerous models and biomarkers have been proposed to estimate prognosis and improve decision-making in patients with acute heart failure (AHF). The present literature review provides a critical appraisal of externally validated prognostic models in AHF, combining clinical data and biomarkers. We perform a literature review of clinical studies, using the following terms: "acute heart failure," "acute decompensated heart failure," "prognostic models," "risk scores," "mortality," "death," "hospitalization," "admission," and "biomarkers." We searched MEDLINE and EMBASE databases from 1990 to 2020 for studies documenting prognostic models in AHF. External validation of each prognostic model to another AHF cohort, containing at least one biomarker, was prerequisites for study selection. Among 358 initially screened studies, 9 of them fulfilled all searching criteria. The majority of prognostic models were simplified, including a narrow number of variables (up to 10), with good performance regarding calibration and discrimination (c-statistics > 0.65). Unfortunately, the derived and validated cohorts showed a wide variety in patients' characteristics (e.g., cause of AHF and therapy). Moreover, the prognostic models used various time-points and a plethora of combinations of variables determining different cut-off values. Although the application of valid prognostic models in AHF population is quite promising, a precise methodological approach should be set for the derivation and validation of prognostic models in AHF with unified characteristics to establish an effective performance in clinical practice.

Outcomes among acute heart failure emergency department patients by preserved vs. reduced ejection fraction

Aims

This study aimed to assess short‐term outcomes among emergency department (ED) patients with acute heart failure (AHF) by preserved (≥50%) vs. reduced (<50%) ejection fraction (EF).

Methods and results

We conducted a retrospective, multicentre study of adult ED patients with AHF from 2017 to 2018 in an integrated healthcare system with 21 hospitals. Among patients with known EF, our primary outcome was 30 day all‐cause mortality, comparing patients with heart failure with preserved EF (HFpEF) and heart failure with reduced EF (HFrEF), adjusted for known risk factors. We ran separate multivariate regression models to compare 30 day mortality between HFpEF and HFrEF patients stratified by ED disposition (admit, observe, and discharge). Our secondary outcomes were adjusted 30 day all‐cause return hospital admission and rates of non‐fatal serious adverse events, including new intra‐aorta balloon pump, endotracheal intubation, renal failure requiring dialysis, myocardial infarction, or coronary revascularization. We conducted a sensitivity analysis among patients with EF ≤ 40% and compared our primary and secondary outcomes among patients with EF ≤ 40% with those with EF ≥ 50%. Among the 26 050 total ED encounters for AHF, 15 275 (58.6%) had known EF and 62.4% had HFpEF. The mean age was 76, 49.6% were women, and 60.5% were white. We found that 62.4% of patients were admitted, 18.3% were observed, and 19.3% were discharged from the ED. The 30 day all‐cause mortality rate was lowest among discharged patients (3.9%), intermediate among observed patients (5.9%), and highest among admitted patients (13.9%). Overall, the adjusted 30 day mortality rate was significantly higher among HFpEF patients compared with HFrEF patients (10.2% vs. 8.4%, P = 0.0004). HFpEF patients had higher mortality regardless of ED disposition, although the difference was only significant among admitted patients. The adjusted 30 day return hospital admission rates were not significantly different between HFpEF and HFrEF patients (17.9% vs. 17.8%, P = 0.89). The adjusted 30 day non‐fatal serious adverse event rates were significantly higher among HFrEF patients compared with HFpEF patients (13.7% vs. 11.1%, P < 0.0001), driven by myocardial infarction and coronary revascularization. We found that 3692 patients had EF ≤ 40%. Patients with EF ≥ 50% had significantly higher adjusted 30 day mortality rates compared with those with EF ≤ 40% (10.2% vs. 8.4%, P < 0.05).

Conclusion

In a contemporary population, almost three quarters of ED patients with AHF and known EF have HFpEF. These patients have higher 30 day adjusted mortality compared with those with HFrEF. Further studies might evaluate the underlying factors associated with this difference and target interventions to improve outcomes.

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.

Blood Pressure Reduction in Hypertensive Acute Heart Failure

PURPOSE OF REVIEW

To review the key clinical and research questions regarding blood pressure (BP) reduction with vasodilators in the early management of hypertensive acute heart failure (H-AHF).

RECENT FINDINGS

Despite numerous AHF vasodilator clinical trials in the past two decades, virtually none has studied a population where vasoconstriction is the predominant physiology, and with the agents and doses most commonly used in contemporary practice. AHF patients are remarkably heterogenous by vascular tone, and this heterogeneity is not always discernible through BP or clinical exam. Emerging data suggest that diastolic BP may be a stronger correlate of vascular tone in AHF than systolic BP, despite the latter historically serving as a key inclusion criterion for vasodilator clinical trials. Existing data are limited. A clinical trial that evaluates vasodilators in a manner of use consistent with contemporary practice, specifically within the subpopulation of patients with true H-AHF, is greatly needed. Until then, observational data supports long-standing vasodilators such as nitroglycerin, administered by IV bolus, and with goal reduction of SBP ≤25% as a safe first-line approach for patients with severe H-AHF presentations.

Effect of a Self-care Intervention on 90-Day Outcomes in Patients With Acute Heart Failure Discharged From the Emergency Department: A Randomized Clinical Trial

Importance

Up to 20% of patients who present to the emergency department (ED) with acute heart failure (AHF) are discharged without hospitalization. Compared with rates in hospitalized patients, readmission and mortality are worse for ED patients.

Objective

To assess the impact of a self-care intervention on 90-day outcomes in patients with AHF who are discharged from the ED.

Design, Setting, and Participants

Get With the Guidelines in Emergency Department Patients With Heart Failure was an unblinded, parallel-group, multicenter randomized trial. Patients were randomized 1:1 to usual care vs a tailored self-care intervention. Patients with AHF discharged after ED-based management at 15 geographically diverse EDs were included. The trial was conducted from October 28, 2015, to September 5, 2019.

Interventions

Home visit within 7 days of discharge and twice-monthly telephone-based self-care coaching for 3 months.

Main Outcomes and Measures

The primary outcome was a global rank of cardiovascular death, HF-related events (unscheduled clinic visit due to HF, ED revisit, or hospitalization), and changes in the Kansas City Cardiomyopathy Questionnaire-12 (KCCQ-12) summary score (SS) at 90 days. Key secondary outcomes included the global rank outcome at 30 days and changes in the KCCQ-12 SS score at 30 and 90 days. Intention-to-treat analysis was performed for the primary, secondary, and safety outcomes. Per-protocol analysis was conducted including patients who completed a home visit and had scheduled outpatient follow-up in the intervention arm.

Results

Owing to slow enrollment, 479 of a planned 700 patients were randomized: 235 to the intervention arm and 244 to the usual care arm. The median age was 63.0 years (interquartile range, 54.7-70.2), 302 patients (63%) were African American, 305 patients (64%) were men, and 178 patients (37%) had a previous ejection fraction greater than 50%. There was no significant difference in the primary outcome between patients in the intervention vs usual care arm (hazard ratio [HR], 0.89; 95% CI, 0.73-1.10; P = .28). At day 30, patients in the intervention arm had significantly better global rank (HR, 0.80; 95% CI, 0.64-0.99; P = .04) and a 5.5-point higher KCCQ-12 SS (95% CI, 1.3-9.7; P = .01), while at day 90, the KCCQ-12 SS was 2.7 points higher (95% CI, -1.9 to 7.2; P = .25).

Conclusions and Relevance

The self-care intervention did not improve the primary global rank outcome at 90 days in this trial. However, benefit was observed in the global rank and KCCQ-12 SS at 30 days, suggesting that an early benefit of a tailored self-care program initiated at an ED visit for AHF was not sustained through 90 days.

Trial Registration

ClinicalTrials.gov Identifier: NCT02519283.

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.

Focused Cardiac Ultrasound in Dyspnea of Unclear Etiology in the Emergency Department: Utility of the FLUID Score

OBJECTIVES

We evaluated the utility of focused cardiac ultrasound to predict the length of stay in patients presenting to the emergency department with dyspnea of unclear etiology.

METHODS

Patients with focused cardiac ultrasound examinations performed in the emergency department for dyspnea over a 34-month period were retrospectively identified. Patients were excluded if they had a prior diagnosis of heart failure, dialysis requirement, or an etiology of dyspnea unrelated to the volume status. Left ventricular function was categorized as normal or reduced, and the inferior vena cava was categorized as normal or increased volume. A fast limited ultrasound to investigate dyspnea (FLUID) score was calculated by adding 1 point for reduced left ventricular function and 1 point for increased volume, producing a score of 0, 1, or 2.

RESULTS

There were 123 patients included. There was a significant correlation between the FLUID score and length of stay, with longer stays for higher scores (FLUID score 0, 7.4 hours median; FLUID score 1, 2.34 days; FLUID score 2, 5.56 days; analysis of variance P < .001). Of the other variables collected, only age, hypertension, diabetes, heart rate, and brain natriuretic peptide were significantly correlated with the length of stay. A multivariate analysis including those variables and the FLUID score showed that the FLUID score was the strongest independent predictor of the length of stay.

CONCLUSIONS

Focused cardiac ultrasound and calculation of a FLUID score for patients with undifferentiated dyspnea can be a powerful tool to predict the hospital length of stay.

Derivation and Validation of Clinical Prediction Models for Rapid Risk Stratification for Time-Sensitive Management for Acute Heart Failure

Early and rapid risk stratification of patients with acute heart failure (AHF) is crucial for appropriate patient triage and outcome improvements. We aimed to develop an easy-to-use, in-hospital mortality risk prediction tool based on data collected from AHF patients at their initial presentation. Consecutive patients’ data pertaining to 2006–2017 were extracted from the West Tokyo Heart Failure (WET-HF) and National Cerebral and Cardiovascular Center Acute Decompensated Heart Failure (NaDEF) registries (n = 4351). Risk model development involved stepwise logistic regression analysis and prospective validation using data pertaining to 2014–2015 in the Registry Focused on Very Early Presentation and Treatment in Emergency Department of Acute Heart Failure Syndrome (REALITY-AHF) (n = 1682). The final model included data describing six in-hospital mortality risk predictors, namely, age, systolic blood pressure, blood urea nitrogen, serum sodium, albumin, and natriuretic peptide (SOB-ASAP score), available at the time of initial triage. The model showed excellent discrimination (c-statistic = 0.82) and good agreement between predicted and observed mortality rates. The model enabled the stratification of the mortality rates across sixths (from 14.5% to <1%). When assigned a point for each associated factor, the integer score’s discrimination was similar (c-statistic = 0.82) with good calibration across the patients with various risk profiles. The models’ performance was retained in the independent validation dataset. Promptly determining in-hospital mortality risks is achievable in the first few hours of presentation; they correlate strongly with mortality among AHF patients, potentially facilitating clinical decision-making.

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.

Risk assessment of post-discharge mortality among recently hospitalized Medicare heart failure patients with reduced or preserved ejection fraction

Objective: Targeted care management for hospitalized patients with acute decompensated heart failure (ADHF) with reduced or preserved ejection fraction (HFrEF/HFpEF) who are at higher risk for post-discharge mortality may mitigate this outcome. However, identification of the most appropriate population for intervention has been challenging. This study developed predictive models to assess risk of 30 day and 1 year post-discharge all-cause mortality among Medicare patients with HFrEF or HFpEF recently hospitalized with ADHF.Methods: A retrospective study was conducted using the 100% Centers for Medicare Services fee-for-service sample with complementary Part D files. Eligible patients had an ADHF-related hospitalization and ICD-9-CM diagnosis code for systolic or diastolic heart failure between 1 January 2010 and 31 December 2014. Data partitioned into training (60%), validation (20%) and test sets (20%) were used to evaluate the three model approaches: classification and regression tree, full logistic regression, and stepwise logistic regression. Performance across models was assessed by comparing the receiver operating characteristic (ROC), cumulative lift, misclassification rate, the number of input variables and the order of selection/variable importance.Results: In the HFrEF (N = 83,000) and HFpEF (N = 123,644) cohorts, 30 day all-cause mortality rates were 6.6% and 5.5%, respectively, and 1 year all-cause mortality rates were 33.6% and 29.5%. The stepwise logistic regression models performed best across both cohorts, having good discrimination (test set ROC of 0.75 for both 30 day mortality models and 0.74 for both 1 year mortality models) and the lowest number of input variables (18-34 variables).Conclusions: Post-discharge mortality risk models for recently hospitalized Medicare patients with HFrEF or HFpEF were developed and found to have good predictive ability with ROCs of greater than or equal to 0.74 and a reasonable number of input variables. Applying this risk model may help providers and health systems identify hospitalized Medicare patients with HFrEF or HFpEF who may benefit from more targeted care management.

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.

Heart failure readmissions: a losing battle or an opportunity for improvement?

Despite great strides in diagnosis and management of heart failure (HF), this chronic illness continues to be a worldwide epidemic with approximately 23 million people afflicted across the globe. In the US, over 6.5 million carry a HF diagnosis with almost 90% of all HF deaths occurring in patients over the age of 70. Since one in five Americans are expected to be older than 65 years by 2050, almost 1,000,000 new HF cases are expected to be diagnosed every year. The staggering nature of these numbers only pales in comparison to current dismal HF survival statistics. The unavoidable natural history of HF continues to be characterized by the occurrence of repetitive hospital admissions. Not only are hospital readmissions demarcated as one of the most important risk factors associated with mortality; but also, a well-recognized trigger for additional hospital readmissions. Even when HF treatment guidelines have been recently updated; the mere fact that four HF societies have issued individual recommendations without reaching a common unifying consensus statement adds to the complexity of HF patient management. The purpose of this Editorial not only to fuel more interest on this topic but also to spark the notion that we have a potential catastrophe in our hands and is the responsibility of all health-care professionals to attend to this vital issue.