Analysis of Worsening Heart Failure Events in an Integrated Health Care System

Applying natural language processing to identify emergency department and observation encounters for worsening heart failure

AIMS

Worsening heart failure (WHF) events occurring in non-inpatient settings are becoming increasingly recognized, with implications for prognostication. We evaluate the performance of a natural language processing (NLP)-based approach compared with traditional diagnostic coding for non-inpatient clinical encounters and left ventricular ejection fraction (LVEF).

METHODS AND RESULTS

We compared characteristics for encounters that did vs. did not meet WHF criteria, stratified by care setting [i.e. emergency department (ED) and observation stay]. Overall, 8407 (22%) encounters met NLP-based criteria for WHF (3909 ED visits and 4498 observation stays). The use of an NLP-derived definition adjudicated 3983 (12%) of non-primary HF diagnoses as meeting consensus definitions for WHF. The most common diagnosis indicated in these encounters was dyspnoea. Results were primarily driven by observation stays, in which 2205 (23%) encounters with a secondary HF diagnosis met the WHF definition by NLP.

CONCLUSIONS

The use of standard claims-based adjudication for primary diagnosis in the non-inpatient setting may lead to misclassification of WHF events in the ED and overestimate observation stays. Primary diagnoses alone may underestimate the burden of WHF in non-hospitalized settings.

Treatment Patterns, Outcomes, and Persistence to Newly Started Heart Failure Medications in Patients with Worsening Heart Failure: A Cohort Study from the United States and Germany

BACKGROUND

Data are limited regarding guideline-directed medical therapy (GDMT) treatment patterns in patients with worsening heart failure (HF).

METHODS

We used administrative claims databases in Germany and the USA to conduct a retrospective cohort study of patients with worsening HF. Two cohorts of patients with prevalent HF and a HF hospitalization (HFH) from 2016 to 2019, alive at discharge (N = 75,140 USA; N = 47,003 Germany) were identified. Index date was the first HFH during the study period. One-year HF rehospitalization and mortality rates were calculated and a composite endpoint of both outcomes assessed using Kaplan-Meier estimation. We evaluated HF medication patterns in the 6 months before and after the index date. New users of a HF medication (at discharge/after index HFH) were followed for 1 year to evaluate persistence (no treatment gaps > 2 months) RESULTS: One-year HF rehospitalization rates were 36.2% (USA) and 47.7% (Germany). One year mortality rates were 30.0% (USA) and 23.0% (Germany), and the composite endpoint (mortality/HF rehospitalization) was reached in 55.1 % (USA) and 56.6% (Germany). Kaplan-Meier plots showed the risk for the composite endpoint was high in the early post discharge period. Comparison of patterns pre- and postindex HFH showed some increase in use of mineralocorticoid receptor antagonists (MRAs), angiotensin receptor-neprilysin inhibitor (ARNI), and triple therapy; use of angiotensin-converting enzyme (ACE) inhibitor/ angiotensin receptor blocker (ARB) plus beta-blockers remained constant/slightly declined; < 20% patients received triple therapy (ACE inhibitor/ARB plus beta-blocker plus MRA). A third of patients were new users; 1 year persistence rates were often low.

CONCLUSIONS

Morbidity, mortality, and rehospitalization risk is high among patients with worsening HF; uptake and continuation of GDMT is suboptimal.

Clinical impact of remote heart failure management using the multiparameter ICD HeartLogic alert

INTRODUCTION AND OBJECTIVES

The multiparametric implantable cardioverter-defibrillator HeartLogic index has proven to be a sensitive and timely predictor of impending heart failure (HF) decompensation. We evaluated the impact of a standardized follow-up protocol implemented by nursing staff and based on remote management of alerts.

METHODS

The algorithm was activated in HF patients at 19 Spanish centers. Transmitted data were analyzed remotely, and patients were contacted by telephone if alerts were issued. Clinical actions were implemented remotely or through outpatient visits. The primary endpoint consisted of HF hospitalizations or death. Secondary endpoints were HF outpatient visits. We compared the 12-month periods before and after the adoption of the protocol.

RESULTS

We analyzed 392 patients (aged 69±10 years, 76% male, 50% ischemic cardiomyopathy) with implantable cardioverter-defibrillators (20%) or cardiac resynchronization therapy defibrillators (80%). The primary endpoint occurred 151 times in 86 (22%) patients during the 12 months before the adoption of the protocol, and 69 times in 45 (11%) patients (P<.001) during the 12 months after its adoption. The mean number of hospitalizations per patient was 0.39±0.89 pre- and 0.18±0.57 postadoption (P<.001). There were 185 outpatient visits for HF in 96 (24%) patients before adoption and 64 in 48 (12%) patients after adoption (P<.001). The mean number of visits per patient was 0.47±1.11 pre- and 0.16±0.51 postadoption (P<.001).

CONCLUSIONS

A standardized follow-up protocol based on remote management of HeartLogic alerts enabled effective remote management of HF patients. After its adoption, we observed a significant reduction in HF hospitalizations and outpatient visits.

Sex-Based Differences in the Epidemiology, Clinical Characteristics, and Outcomes Associated with Worsening Heart Failure Events in a Learning Health System

BACKGROUND

Differences in demographics, risk factors, and clinical characteristics may contribute to variation in men and women in terms of prevalence, clinical setting, and outcomes associated with worsening heart failure (WHF) events.

OBJECTIVES

To describe sex-based differences in the epidemiology, clinical characteristics, and outcomes associated with WHF events across clinical settings.

METHODS

We examined adults diagnosed with HF from 2010-2019 within a large, integrated healthcare delivery system. Electronic health record data were accessed for hospitalizations, emergency department (ED) visits/observation stays, and outpatient encounters. WHF was identified using validated natural language processing algorithms and defined as ≥1 symptom, ≥2 objective findings (including ≥1 sign), and ≥1 change in HF-related therapy. Incidence rates and associated outcomes for WHF were compared across care setting by sex.

RESULTS

We identified 1,122,368 unique clinical encounters with a diagnosis code for HF, with 124,479 meeting WHF criteria. These WHF encounters existed among 102,116 patients, of which 48,543 (47.5%) were women and 53,573 (52.5%) were men. Women experiencing WHF were older and more likely to have HF with preserved ejection fraction compared to men. The clinical settings of WHF were similar among women and men: hospitalizations (36.8% vs. 37.7%), ED visits or observation stays (11.8% vs. 13.4%), and outpatient encounters (4.4% vs. 4.9%). Women had lower odds of 30-day mortality following an index hospitalization (adjusted odds ratio [aOR] 0.88, 95% confidence interval [CI] 0.83-0.93) or ED visit/observation stay (aOR 0.86, 95% 0.75-0.98) for WHF.

CONCLUSION

Women and men contribute similarly to WHF events across diverse clinical settings despite marked differences in age and left ventricular ejection fraction.

Current Approaches to Worsening Heart Failure: Pathophysiological and Molecular Insights

Worsening heart failure (WHF) is a severe and dynamic condition characterized by significant clinical and hemodynamic deterioration. It is characterized by worsening HF signs, symptoms and biomarkers, despite the achievement of an optimized medical therapy. It remains a significant challenge in cardiology, as it evolves into advanced and end-stage HF. The hyperactivation of the neurohormonal, adrenergic and renin-angiotensin-aldosterone system are well known pathophysiological pathways involved in HF. Several drugs have been developed to inhibit the latter, resulting in an improvement in life expectancy. Nevertheless, patients are exposed to a residual risk of adverse events, and the exploration of new molecular pathways and therapeutic targets is required. This review explores the current landscape of WHF, highlighting the complexities and factors contributing to this critical condition. Most recent medical advances have introduced cutting-edge pharmacological agents, such as guanylate cyclase stimulators and myosin activators. Regarding device-based therapies, invasive pulmonary pressure measurement and cardiac contractility modulation have emerged as promising tools to increase the quality of life and reduce hospitalizations due to HF exacerbations. Recent innovations in terms of WHF management emphasize the need for a multifaceted and patient-centric approach to address the complex HF syndrome.

Uptake of Sodium-Glucose Cotransporter-2 Inhibitors in Hospitalized Patients With Heart Failure: Insights From the Veterans Affairs Healthcare System

BACKGROUND

The use of sodium-glucose cotransporter-2 inhibitors (SGLT2is) in Veterans Affairs (VA) patients hospitalized with heart failure (HF) has not been reported previously.

METHODS

VA electronic health record data were used to identify patients hospitalized for HF (primary or secondary diagnosis) from 01/2019-11/2022. Patients with SGLT2i allergy, advanced/end-stage chronic kidney disease (CKD) or advanced HF therapies were excluded. We identified factors associated with discharge SGLT2i prescriptions for patients hospitalized due to HF in 2022. We also compared SGLT2i and angiotensin receptor-neprilysin inhibitor (ARNI) prescription rates. Hospital-level variations in SGLT2i prescriptions were assessed via the median odds ratio.

RESULTS

A total of 69,680 patients were hospitalized due to HF; 10.3% were prescribed SGLT2i at discharge (4.4% newly prescribed, 5.9% continued preadmission therapy). SGLT2i prescription increased over time and was higher in patients with HFrEF and primary HF. Among 15,762 patients hospitalized in 2022, SGLT2i prescription was more likely in patients with diabetes (adjusted odds ratio [aOR] 2.27; 95% confidence interval [CI]: 2.09-2.47) and ischemic heart disease (aOR 1.14; 95% CI: 1.03-1.26). Patients with increased age (aOR 0.77 per 10 years; 95% CI: 0.73-0.80) and lower systolic blood pressure (aOR 0.94 per 10 mmHg; 95% CI: 0.92-0.96) were less likely to be prescribed SGLT2i, and SGLT2i prescription was not more likely in patients with CKD (aOR 1.07; 95% CI 0.98-1.16). The adjusted median odds ratio suggested a 1.8-fold variation in the likelihood that similar patients at 2 random VA sites were prescribed SGLT2i (range 0-21.0%). In patients with EF ≤ 40%, 30.9% were prescribed SGLT2i while 26.9% were prescribed ARNI (P < 0.01).

CONCLUSION

One-tenth of VA patients hospitalized for HF were prescribed SGLT2i at discharge. Opportunities exist to reduce variation in SGLT2i prescription rates across hospitals and to promote its use in patients with CKD and older age.

The value of using left ventricular pressure-strain loops to evaluate myocardial work in predicting heart failure with improved ejection fraction

BACKGROUND

The ultrasound left ventricular pressure-strain loop (LV PSL) was applied to evaluate myocardial work in heart failure with improved ejection fraction (HFimpEF) versus patients with persistent heart failure with reduced ejection fraction (HFrEF) to investigate the value of myocardial work parameters in predicting HFimpEF.

METHODS

We collected 120 patients with HFrEF and recorded clinical characteristics and echocardiographic parameters (PSL technique) of patients. Patients were divided into HFimpEF group or persistent HFrEF group according to the outcome of follow-up. Furthermore, differential clinical and echocardiographic parameters were determined by Student's t-test. We recognized the important echocardiographic parameters to predict whether patients would recover to HFimpEF using the univariate logistic regression analysis and ROC curves. In addition, the multivariate logistic regression models were constructed and evaluated using Delong test and decision curve analysis.

RESULTS

Firstly, the HFimpEF group had a higher prevalence of hypertension and higher systolic blood pressure (P-values <0.05). In terms of echocardiographic parameters, HFimpEF group also had higher LVEF, LV GLS, GCW, GWE, and GWI and lower LVEDD (P-values <0.01). In particular, LVEF, LVEDD, GLS, GWI, and GCW were robust predictors of the conversion of HFrEF patients to HFimpEF (AUC >0.70, P-values <0.05). Finally, we determined that the predictive Model 4 (LVEF, LVEDD, GLS, and GCW) had the optimal diagnostic power.

CONCLUSION

The model constructed by GCW with LVEF, LVEDD, and GLS has important predictive value for HFimpEF, which is an effective clinical decision-making tool for providing disease assessment.

Cholinesterase inhibitors associated with lower rate of mortality in dementia patients with heart failure: a nationwide propensity weighting study

PURPOSE

This study investigates the potential impact of cholinesterase inhibitors (ChEIs) on patients with heart failure (HF) and dementia. ChEIs are known to boost acetylcholine levels and benefit cognition in patients with dementia; however, their effect on patients with HF is uncertain. This study aimed to assess whether cardiovascular events and mortality among patients with HF and dementia are altered by ChEI therapy.

METHODS

Data from the National Health Insurance Research Database in Taiwan were retrospectively analyzed. Dementia patients diagnosed with HF were followed for 5 years until all-cause mortality, cardiovascular mortality, hospitalization for worsening HF, or the end of the study. Multivariable Cox models and inverse probability of treatment weighting (IPTW) were employed.

RESULTS

Out of 20,848 patients with dementia, 5138 had HF. Among them, 726 were ChEI users and 4412 were non-users. Based on IPTW, the ChEI users had significantly lower estimated risks of all-cause mortality [hazard ratio (HR) 0.43; 95% confidence interval (CI) 0.38-0.49, p < 0.001] and cardiovascular mortality (HR 0.41; 95% CI 0.33-0.53, p < 0.001) compared with the non-users, but there was no significant difference in hospitalization for worsening HF (HR 0.73; 95% CI 0.51-1.05, p = 0.091) after 5 years. The survival benefits of ChEIs were consistent across subgroups.

CONCLUSIONS

The results of this retrospective cohort study suggest that ChEIs may be beneficial in reducing all-cause and cardiovascular mortality in patients with dementia with HF. Further research is needed to validate these findings and explore the potential benefits of ChEIs in all patients with HF, including those without dementia.

Association Between Participation in a Heart Failure Telemonitoring Program and Health Care Utilization and Death Within an Integrated Health Care Delivery System

BACKGROUND

The clinical usefulness of remote telemonitoring to reduce postdischarge health care use and death in adults with heart failure (HF) remains controversial.

METHODS AND RESULTS

Within a large integrated health care delivery system, we matched patients enrolled in a postdischarge telemonitoring intervention from 2015 to 2019 to patients not receiving telemonitoring at up to a 1:4 ratio on age, sex, and calipers of a propensity score. Primary outcomes were readmissions for worsening HF and all-cause death within 30, 90, and 365 days of the index discharge; secondary outcomes were all-cause readmissions and any outpatient diuretic dose adjustments. We matched 726 patients receiving telemonitoring to 1985 controls not receiving telemonitoring, with a mean age of 75 ± 11 years and 45% female. Patients receiving telemonitoring did not have a significant reduction in worsening HF hospitalizations (adjusted rate ratio [aRR] 0.95, 95% confidence interval [CI] 0.68-1.33), all-cause death (adjusted hazard ratio 0.60, 95% CI 0.33-1.08), or all-cause hospitalization (aRR 0.82, 95% CI 0.65-1.05) at 30 days, but did have an increase in outpatient diuretic dose adjustments (aRR 1.84, 95% CI 1.44-2.36). All associations were similar at 90 and 365 days postdischarge.

CONCLUSIONS

A postdischarge HF telemonitoring intervention was associated with more diuretic dose adjustments but was not significantly associated with HF-related morbidity and mortality.

Evolution of economic burden of heart failure by ejection fraction in newly diagnosed patients in Spain

OBJECTIVE

To describe healthcare resource utilization (HCRU) and costs, in patients with newly diagnosed heart failure (HF) according to ejection fraction (EF) in Spain.

METHODS

Retrospective cohort study that analyzed anonymized, integrated and computerised medical records in Spain. Patients with ≥ 1 new HF diagnosis between January 2013 and September 2019 were included and followed-up during a 4-year period. Rates per 100 person-years of HCRU and costs were estimated.

RESULTS

Nineteen thousand nine hundred sixty-one patients were included, of whom 43.5%, 26.3%, 5.1% and 25.1% had HF with reduced, preserved, mildly reduced and unknown EF, respectively. From year 1 to 4, HF rates of outpatient visits decreased from 1149.5 (95% CI 1140.8-1159.3) to 765.5 (95% CI 745.9-784.5) and hospitalizations from 61.7 (95% CI 60.9-62.7) to 15.7(14.7-16.7) per 100 person-years. The majority of HF-related healthcare resource costs per patient were due to hospitalizations (year 1-4: 63.3-38.2%), followed by indirect costs (year 1-4: 12.2-29.0%), pharmacy (year 1-4: 11.9-19.9%), and outpatient care (year 1-4: 12.6-12.9%). Mean (SD) per patient HF-related costs decreased from 2509.6 (3518.5) to 1234.6 (1534.1) Euros (50% cost reduction). At baseline, 70.1% were taking beta-blockers, 56.3% renin-angiotensin system inhibitors, 11.8% mineralocorticoid receptor antagonists and 8.9% SGLT2 inhibitors. At 12 months, these numbers were 72.3%, 65.4%, 18.9% and 9.8%, respectively.

CONCLUSIONS

Although the economic burden of HF decreased over time since diagnosis, it is still substantial. This reduction could be partially related to a survival bias (sick patients died early), but also to a better HF management. Despite that, there is still much room for improvement.

Developing Clinical Risk Prediction Models for Worsening Heart Failure Events and Death by Left Ventricular Ejection Fraction

Background There is a need to develop electronic health record-based predictive models for worsening heart failure (WHF) events across clinical settings and across the spectrum of left ventricular ejection fraction (LVEF). Methods and Results We studied adults with heart failure (HF) from 2011 to 2019 within an integrated health care delivery system. WHF encounters were ascertained using natural language processing and structured data. We conducted boosted decision tree ensemble models to predict 1-year hospitalizations, emergency department visits/observation stays, and outpatient encounters for WHF and all-cause death within each LVEF category: HF with reduced ejection fraction (EF) (LVEF <40%), HF with mildly reduced EF (LVEF 40%-49%), and HF with preserved EF (LVEF ≥50%). Model discrimination was evaluated using area under the curve and calibration using mean squared error. We identified 338 426 adults with HF: 61 045 (18.0%) had HF with reduced EF, 49 618 (14.7%) had HF with mildly reduced EF, and 227 763 (67.3%) had HF with preserved EF. The 1-year risks of any WHF event and death were, respectively, 22.3% and 13.0% for HF with reduced EF, 17.0% and 10.1% for HF with mildly reduced EF, and 16.3% and 10.3% for HF with preserved EF. The WHF model displayed an area under the curve of 0.76 and mean squared error of 0.13, whereas the model for death displayed an area under the curve of 0.83 and mean squared error of 0.076. Performance and predictors were similar across WHF encounter types and LVEF categories. Conclusions We developed risk prediction models for 1-year WHF events and death across the LVEF spectrum using structured and unstructured electronic health record data and observed no substantial differences in model performance or predictors except for death, despite differences in underlying HF cause.

Virtual Care Team Guided Management of Patients With Heart Failure During Hospitalization

BACKGROUND

Scalable and safe approaches for heart failure guideline-directed medical therapy (GDMT) optimization are needed.

OBJECTIVES

The authors assessed the safety and effectiveness of a virtual care team guided strategy on GDMT optimization in hospitalized patients with heart failure with reduced ejection fraction (HFrEF).

METHODS

In a multicenter implementation trial, we allocated 252 hospital encounters in patients with left ventricular ejection fraction ≤40% to a virtual care team guided strategy (107 encounters among 83 patients) or usual care (145 encounters among 115 patients) across 3 centers in an integrated health system. In the virtual care team group, clinicians received up to 1 daily GDMT optimization suggestion from a physician-pharmacist team. The primary effectiveness outcome was in-hospital change in GDMT optimization score (+2 initiations, +1 dose up-titrations, -1 dose down-titrations, -2 discontinuations summed across classes). In-hospital safety outcomes were adjudicated by an independent clinical events committee.

RESULTS

Among 252 encounters, the mean age was 69 ± 14 years, 85 (34%) were women, 35 (14%) were Black, and 43 (17%) were Hispanic. The virtual care team strategy significantly improved GDMT optimization scores vs usual care (adjusted difference: +1.2; 95% CI: 0.7-1.8; P < 0.001). New initiations (44% vs 23%; absolute difference: +21%; P = 0.001) and net intensifications (44% vs 24%; absolute difference: +20%; P = 0.002) during hospitalization were higher in the virtual care team group, translating to a number needed to intervene of 5 encounters. Overall, 23 (21%) in the virtual care team group and 40 (28%) in usual care experienced 1 or more adverse events (P = 0.30). Acute kidney injury, bradycardia, hypotension, hyperkalemia, and hospital length of stay were similar between groups.

CONCLUSIONS

Among patients hospitalized with HFrEF, a virtual care team guided strategy for GDMT optimization was safe and improved GDMT across multiple hospitals in an integrated health system. Virtual teams represent a centralized and scalable approach to optimize GDMT.

Novel Strategies to Improve Prescription of Guideline-Directed Medical Therapy in Heart Failure

PURPOSE OF REVIEW

To examine the emerging data for novel strategies being studied to improve use and dose titration of guideline-directed medical therapy (GDMT) for patients with heart failure (HF).

RECENT FINDINGS

There is mounting evidence to employ novel multi-pronged strategies to address HF implementation gaps.

SUMMARY

Despite high-level randomized evidence and clear national society recommendations, a large gap persists in use and dose titration of guideline-directed medical therapy (GDMT) in patients with heart failure (HF). Accelerating the safe implementation of GDMT has proven to reduce the morbidity and mortality associated with HF but remains an ongoing challenge for patients, clinicians, and health systems. In this review, we examine the emerging data for novel strategies to improve the use of GDMT including the use of multidisciplinary team-based approaches, nontraditional patient encounters, patient messaging/engagement, remote patient monitoring, and electronic health record (EHR)-based clinical alerts. While societal guidelines and implementation studies have focused on heart failure with reduced ejection fraction (HFrEF), expanding indications and evidence for the use of sodium glucose cotransporter2 (SGLT2i) will necessitate implementation efforts across the LVEF spectrum.

Worsening Heart Failure: Nomenclature, Epidemiology, and Future Directions: JACC Review Topic of the Week

Heart failure (HF) is a progressive disease characterized by variable durations of symptomatic stability often punctuated by episodes of worsening despite continued therapy. These periods of clinical worsening are increasingly recognized as a distinct phase in the history of HF, termed worsening HF (WHF). The definition of WHF continues to evolve from a historical focus solely on hospitalization to now include nonhospitalization events (eg, need for intravenous diuretic therapy in the emergency or outpatient setting). Most HF clinical trials to date have had HF hospitalization and death as primary endpoints, and only recently, some studies have included other WHF events regardless of location of care. This article reviews the evolution of the WHF definition, highlights the importance of considering the onset of WHF as an event that marks a new phase of HF, summarizes the latest clinical trials investigating novel therapies, and outlines unmet needs regarding identification and treatment of WHF.

A prediction model for major adverse cardiovascular events in patients with heart failure based on high-throughput echocardiographic data

Background

Heart failure (HF) is a serious end-stage condition of various heart diseases with increasing frequency. Few studies have combined clinical features with high-throughput echocardiographic data to assess the risk of major cardiovascular events (MACE) in patients with heart failure. In this study, we assessed the relationship between these factors and heart failure to develop a practical and accurate prognostic dynamic nomogram model to identify high-risk groups of heart failure and ultimately provide tailored treatment options.

Materials and methods

We conducted a prospective study of 468 patients with heart failure and established a clinical predictive model. Modeling to predict risk of MACE in heart failure patients within 6 months after discharge obtained 320 features including general clinical data, laboratory examination, 2-dimensional and Doppler measurements, left ventricular (LV) and left atrial (LA) speckle tracking echocardiography (STE), and left ventricular vector flow mapping (VFM) data, were obtained by building a model to predict the risk of MACE within 6 months of discharge for patients with heart failure. In addition, the addition of machine learning models also confirmed the necessity of increasing the STE and VFM parameters.

Results

Through regular follow-up 6 months after discharge, MACE occurred in 156 patients (33.3%). The prediction model showed good discrimination C-statistic value, 0.876 (p < 0.05), which indicated good identical calibration and clinical efficacy. In multiple datasets, through machine learning multi-model comparison, we found that the area under curve (AUC) of the model with VFM and STE parameters was higher, which was more significant with the XGboost model.

Conclusion

In this study, we developed a prediction model and nomogram to estimate the risk of MACE within 6 months of discharge among patients with heart failure. The results of this study can provide a reference for clinical physicians for detection of the risk of MACE in terms of clinical characteristics, cardiac structure and function, hemodynamics, and enable its prompt management, which is a convenient, practical and effective clinical decision-making tool for providing accurate prognosis.