Factors influencing the predictive power of models for predicting mortality and/or heart failure hospitalization in patients with heart failure

Cognitive impairment in young and middle-aged patients with acute heart failure

AIMS

This study aimed to investigate the prevalence, risk factors and prognostic implications of cognitive impairment in young and middle-aged patients with acute heart failure (HF).

METHODS

In a prospective cohort of patients with acute HF, we assessed cognitive function by the Mini-Cog, predictors of the cognitive impairment and its associations with 30 day and 1 year cardiovascular death or HF rehospitalization among young and middle-aged patients (<65 years old).

RESULTS

Among 1958 young and middle-aged patients, the prevalence of cognitive impairment was 19.6%. Predictors of cognitive impairment included older age, females, lower education levels and prior strokes. Compared with patients having normal cognitive function, cognitive impairment was associated with a higher risk of 30 day cardiovascular death or HF rehospitalization [hazard ratio (HR), 1.52, 95% confidence interval (CI), 1.07-2.17, P = 0.02], but not for 1 year cardiovascular death or HF rehospitalization (HR, 1.06, 95% CI, 0.87-1.30, P = 0.55).

CONCLUSIONS

Cognitive impairment is present in a notable proportion of young and middle-aged patients with acute HF and is associated with an increased risk of short-term adverse outcomes. Strategies for screening and intervention for cognitive impairment at a younger age are necessary, particularly for those at high risk.

Machine learning-based model for worsening heart failure risk in Chinese chronic heart failure patients

AIMS

This study aims to develop and validate an optimal model for predicting worsening heart failure (WHF). Multiple machine learning (ML) algorithms were compared, and the results were interpreted using SHapley Additive exPlanations (SHAP). A clinical risk calculation tool was subsequently developed based on these findings.

METHODS AND RESULTS

This nested case-control study included 200 patients with chronic heart failure (CHF) from the China-Japan Friendship Hospital (September 2019 to December 2022). Sixty-five variables were collected, including basic information, physical and chemical examinations, and quality of life assessments. WHF occurrence within a 3-month follow-up was the outcome event. Variables were screened using LASSO regression, univariate analysis, and comparison of key variables in multiple ML models. Eighty per cent of the data was used for training and 20% for testing. The best models were identified by integrating nine ML algorithms and interpreted using SHAP, and to develop a final risk calculation tool. Among participants, 68 (34.0%) were female, with a mean age (standard deviation, SD) of 68.57 (12.80) years. During the follow-up, 60 participants (30%) developed WHF. N-terminal pro-brain natriuretic peptide (NT-proBNP), creatinine (Cr), uric acid (UA), haemoglobin (Hb), and emotional area score on the Minnesota Heart Failure Quality of Life Questionnaire were critical predictors of WHF occurrence. The random forest (RF) model was the best model to predict WHF with an area under the curve (AUC) (95% confidence interval, CI) of 0.842 (0.675-1.000), accuracy of 0.775, sensitivity of 0.900, specificity of 0.833, negative predictive value of 0.800, and positive predictive value of 0.600 for the test set. SHAP analysis highlighted NT-proBNP, UA, and Cr as significant predictors. An online risk predictor based on the RF model was developed for personalized WHF risk assessment.

CONCLUSIONS

This study identifies NT-proBNP, Cr, UA, Hb, and emotional area scores as crucial predictors of WHF in CHF patients. Among the nine ML algorithms assessed, the RF model showed the highest predictive accuracy. SHAP analysis further emphasized NT-proBNP, UA, and Cr as the most significant predictors. An online risk prediction tool based on the RF model was subsequently developed to enhance early and personalized WHF risk assessment in clinical settings.

[Prognostic value of electrical bioimpedance measured with a portable and wireless device in acute heart failure]

INTRODUCTION AND OBJECTIVES

The current evaluation of acute heart failure (HF) does not allow an adequate prediction of its evolution. The electrical bioimpedance (BI) allows knowing the state of blood volume, until now only with fixed equipment. We have developed and validated a portable and wireless device to measure BI at the ankle (IVOL). The objective of the study is to know the long-term prognostic value of the point measurement of BI with IVOL in patients with acute HF.

METHODS

A prospective cohort study of unselected patients admitted for acute HF in a tertiary hospital. The association between BI and different clinical, analytical and echocardiographic variables on admission and clinical evolution were analyzed.

RESULTS

76 patients were included (mean age 66.1 years, 71.1% men, 68.4% hypertensive, 34.2% diabetic, mean NT-ProBNP: 7,103 pg / ml). Of these, 52.6% with non-preserved left ventricular ejection fraction (LVEF) (<50%) and 56.6% with right ventricular (RV) dysfunction. 26.3% died during a mean follow-up of 35.8 months. Survival in patients with BI≤21,8Ω was lower, globally and in the subgroups of patients without preserved LVEF and with RV dysfunction, P<.008). In the multivariate analysis, a BI≥21.8Ω was an independent survival factor (HR: 0.242; 95% CI: 0.86-0.681; P=.007).

CONCLUSIONS

BI values measured with IVOL may be an independent predictor of long-term mortality in patients hospitalized for acute HF. This prognostic value is maintained in patients without preserved LVEF function and with RV dysfunction.

Prognostic impact of frailty based on a comprehensive frailty assessment in patients with heart failure

AIMS

This study aimed to evaluate the impact of frailty and living function domains based on the Kihon Checklist (KCL), a questionnaire for a comprehensive frailty assessment, on prognosis in patients with acute heart failure (AHF).

METHODS AND RESULTS

The Kochi Registry of Subjects with Acute Decompensated Heart Failure (Kochi YOSACOI) study was a prospective multicentre cohort study enrolling 1061 patients hospitalized for AHF from May 2017 to December 2019 in Japan. We divided patients into three groups according to the severity of frailty using the KCL and compared clinical outcomes after discharge. The primary endpoint was all-cause death, and the secondary outcomes were cardiovascular death, heart failure (HF) rehospitalization, and the composite event of cardiovascular death and HF rehospitalization. Of 936 patients (median age, 81 years; 48.9% women) who could be assessed for frailty, we identified frailty in 501 patients (53.5%), prefrailty in 290 patients (31.0%), and non-frailty in 145 patients (15.5%). Compared with prefrail and non-frail patients, frail patients were older (83 vs. 79 and 72 years, P < 0.001), were more likely to be women (53.9% vs. 43.1% and 43.4%, P = 0.005), and were more likely to have a history of previous HF hospitalization (35.4% vs. 25.3% and 19.6%, P < 0.001) and multimorbidity (90.8% vs. 81.0% and 73.8%, P < 0.001). Frail patients had a lower rate of discharge to home (79.7% vs. 94.8% and 96.5%, P < 0.001). During the 2 year follow-up period, frail patients had a higher incidence rate of all-cause death, cardiovascular death, and HF rehospitalization (log-rank P < 0.001, P < 0.001, and P = 0.003, respectively). After adjusting for other prognostic factors, multivariate analysis showed that frailty was associated with all-cause death [adjusted hazard ratio (HR): 2.917, 95% confidence interval (CI): 1.326-6.417, P = 0.008] and cardiovascular death (adjusted HR: 7.026, 95% CI: 1.700-29.030, P = 0.007). Among all domains of the KCL, the cognitive function domain was associated with a higher risk of all-cause death (P = 0.004) and cardiovascular death (P < 0.001). The depression domain remained associated with a higher risk of HF rehospitalization (P = 0.045). The risk for all-cause death increased with an increase in total KCL score (adjusted HR: 1.819, 95% CI: 1.300-2.547, P < 0.001).

CONCLUSIONS

The KCL is a useful tool for risk stratification of adverse outcomes in patients with AHF. Functional declines in psycho-emotional domains including cognitive function and depressed mood contribute to adverse outcomes.

Risk Factors for All-Cause Mortality in Patients Diagnosed with Advanced Heart Failure: A Scoping Review

Introduction: Identifying the evolving needs of patients with advanced heart failure (AdHF) and triaging those at high risk of death can facilitate timely referrals to palliative care and advance patient-centered individualized care. There are limited models specific for patients with end-stage HF. We aim to identify risk factors associated with up to three-year all-cause mortality (ACM) and describe prognostic models developed or validated in AdHF populations. Methods: Frameworks proposed by Arksey, O'Malley, and Levac were adopted for this scoping review. We searched the Medline, EMBASE, PubMed, CINAHL, Cochrane library, Web of Science and gray literature databases for articles published between January 2010 and September 2020. Primary studies that included adults aged ≥ 18 years, diagnosed with AdHF defined as New York Heart Association class III/IV, American Heart Association/American College of Cardiology Stage D, end-stage HF, and assessed for risk factors associated with up to three-year ACM using multivariate analysis were included. Studies were appraised using the Quality of Prognostic Studies tool. Data were analyzed using a narrative synthesis approach. Results: We reviewed 167 risk factors that were associated with up to three-year ACM and prognostic models specific to AdHF patients across 65 articles with low-to-moderate bias. Studies were mostly based in Western and/or European cohorts (n = 60), in the acute care setting (n = 56), and derived from clinical trials (n = 40). Risk factors were grouped into six domains. Variables related to cardiovascular and overall health were frequently assessed. Ten prognostic models developed/validated on AdHF patients displayed acceptable model performance [area under the curve (AUC) range: 0.71-0.81]. Among the ten models, the model for end-stage-liver disease (MELD-XI) and acute decompensated HF with N-terminal pro b-type natriuretic peptide (ADHF/proBNP) model attained the highest discriminatory performance against short-term ACM (AUC: 0.81). Conclusions: To enable timely referrals to palliative care interventions, further research is required to develop or validate prognostic models that consider the evolving landscape of AdHF management.

Functional limitation predicts mortality in heart failure with preserved ejection fraction

BACKGROUND

While the prognostic value of six-minute walking test (6MWT) in patients with heart failure (HF) and reduced ejection fraction has been firmly established, there are few or no data correlating the distance walked during 6MWT (6MWD) with mortality in patients with HF with preserved ejection fraction (HFpEF) METHODS: We studied 482 patients with HFpEF who had been admitted to inpatients cardiac rehabilitation. The primary outcome was 3-year all-cause mortality. The association between 6MWD and the primary outcome was assessed using multivariable models. Established risk markers were incorporated into the models.

RESULTS

174 patients died during the 3-year follow-up. Taking the highest tertile of 6MWD (≥360 m) as reference, the adjusted hazard ratio (HR) of the primary outcome was 2.23 (95 % CI 1.31-3.78; p = .003) for the patients in the intermediate tertile (241-359 m) and 4.94 (95 % CI 2.90-8.39; p < .001) for those in the lowest tertile (≤240 m). The annual mortality rate was 25.0 % in the lowest tertile, 10.9 % in the intermediate tertile, and 5.3 % in the highest tertile. When the distance walked was normalized for age, sex, and body mass index and expressed as percent-of-predicted walking distance, the adjusted HR was 1.30 (95 % CI 0.76-2.22; p = .331) for the patients in the intermediate tertile (58.2 % to 77.6 %) and 3.52 (95 % CI 2.12-5.85; p < .001) for those in the lowest tertile (≤58.1 %).

CONCLUSIONS

Our findings suggest that measuring functional capacity by evaluating the distance that a patient can walk over a period of 6 min provides important prognostic information in HFpEF.

Symptoms and signs in patients with heart failure: association with 3-month hospitalisation and mortality

OBJECTIVES

To determine the association between symptoms and signs reported in primary care consultations following a new diagnosis of heart failure (HF), and 3-month hospitalisation and mortality.

DESIGN

Nested case-control study with density-based sampling.

SETTING

Clinical Practice Research Datalink, linked to hospitalisation and mortality (1998-2020).

PARTICIPANTS

Database cohort of 86 882 patients with a new HF diagnosis. In two separate analyses for (1) first hospitalisation and (2) death, we compared the 3-month history of symptoms and signs in cases (patients with HF with the event), with their respective controls (patients with HF without the respective event, matched on diagnosis date (±1 month) and follow-up time). Controls could be included more than once and later become a case.

MAIN OUTCOME MEASURES

All-cause, HF and non-cardiovascular disease (non-CVD) hospitalisation and mortality.

RESULTS

During a median follow-up of 3.22 years (IQR: 0.59-8.18), 56 677 (65%) experienced first hospitalisation and 48 146 (55%) died. These cases were matched to 356 714 and 316 810 HF controls, respectively. For HF hospitalisation, the strongest adjusted associations were for symptoms and signs of fluid overload: pulmonary oedema (adjusted OR 3.08; 95% CI 2.52, 3.64), shortness of breath (2.94; 2.77, 3.11) and peripheral oedema (2.16; 2.00, 2.32). Generic symptoms also showed significant associations: depression (1.50; 1.18, 1.82), anxiety (1.35; 1.06, 1.64) and pain (1.19; 1.10, 1.28). Non-CVD hospitalisation had the strongest associations with chest pain (2.93; 2.77, 3.09), fatigue (1.87; 1.73, 2.01), general pain (1.87; 1.81, 1.93) and depression (1.59; 1.44, 1.74).

CONCLUSIONS

In the primary care HF population, routinely recorded cardiac and non-specific symptoms showed differential risk associations with hospitalisation and mortality.

The role and application of current pharmacological management in patients with advanced heart failure

In the last decades, several classifications and definitions have been proposed for advanced heart failure (ADVHF) patients, including clinical, functional, hemodynamic, imaging, and electrocardiographic features. Despite different inclusion criteria, ADVHF is characterized by some common items, such as drug intolerance, low arterial pressure, multiple organ dysfunction, chronic kidney disease, and diuretic use dependency. Additional features include fatigue, hypotension, hyponatremia, and unintentional weight loss associated with a specific laboratory profile reflecting systemic multiorgan dysfunction. Notably, studies evaluating guideline-directed medical therapy recently endorsed by guidelines in stable HF, including the 4 drug classes all together (i.e., betablocker, mineral corticoid antagonist, renin angiotensin inhibitors/neprilysin inhibitors, and sodium glucose transporter inhibitors), remain scarcely analyzed in ADVHF and New York Heart Association (NYHA) Class IV. Additionally, due to the common conditions associated with advanced stages, the balance between drug tolerance and potential benefits of the contemporary use of all agents is questioned. Therefore, less hard endpoints, such as exercise tolerance, quality of life (QoL) and self-competency, are not clearly demonstrated. Specific analyses evaluating outcome and rehospitalization of each drug provided conflicting results and are often limited to subjects with stable conditions and less advanced NYHA class. Current European Society of Cardiology/American Heart Association (ESC/AHA) Guidelines do not indicate the type of treatment, dosage, and administration modalities, and they do not suggest specific indications for ADVHF patients. Due to these concerns, there is an impelling need to understand what drugs may be used as the first line, what management leads to the better outcome, and what is the best treatment algorithm in this setting. In this paper, we summarize the most common pitfalls and limitations for the use of the traditional agents, and we propose a personalized approach aiming at preserve drug tolerance and maintaining adverse event protection and satisfactory QoL.

Growth differentiation factor-15 in patients with or at risk of heart failure but before first hospitalisation

OBJECTIVE

Identification of patients at risk of adverse outcome from heart failure (HF) at an early stage is a priority. Growth differentiation factor (GDF)-15 has emerged as a potentially useful biomarker. This study sought to identify determinants of circulating GDF-15 and evaluate its prognostic value, in patients at risk of HF or with HF but before first hospitalisation.

METHODS

Prospective, longitudinal cohort study of 2166 consecutive patients in stage A-C HF undergoing cardiovascular magnetic resonance and measurement of GDF-15. Multivariable linear regression investigated determinants of GDF-15. Cox proportional hazards modelling, Net Reclassification Improvement and decision curve analysis examined its incremental prognostic value. Primary outcome was a composite of first hospitalisation for HF or all-cause mortality. Median follow-up was 1093 (939-1231) days.

RESULTS

Major determinants of GDF-15 were age, diabetes and N-terminal pro-B-type natriuretic peptide, although despite extensive phenotyping, only around half of the variability of GDF-15 could be explained (R2 0.51). Log-transformed GDF-15 was the strongest predictor of outcome (HR 2.12, 95% CI 1.71 to 2.63) and resulted in a risk prediction model with higher predictive accuracy (continuous Net Reclassification Improvement 0.26; 95% CI 0.13 to 0.39) and with greater clinical net benefit across the entire range of threshold probabilities.

CONCLUSION

In patients at risk of HF, or with HF but before first hospitalisation, GDF-15 provides unique information and is highly predictive of hospitalisation for HF or all-cause mortality, leading to more accurate risk stratification that can improve clinical decision making.

TRIAL REGISTRATION NUMBER

NCT02326324.

Predictors of a Good Diuretic Response and Administration Methods for Carperitide in Patients With Acute Heart Failure

PURPOSE

In Japan, carperitide has been recommended for the treatment of pulmonary congestion in patients with acute heart failure. Identifying useful indicators to support the decision to administer carperitide and the optimal timing of administration may lead to better improvement of pulmonary congestion. Therefore, we investigated the factors associated with good diuretic response to carperitide in patients with acute heart failure and the optimal timing of carperitide administration.

METHODS

This retrospective cohort study investigated 293 hospitalized patients who were diagnosed with acute heart failure and treated with carperitide at the Department of Cardiology, Showa University Fujigaoka Hospital. The primary endpoint was the diuretic response to carperitide. Patients with urine output ≥100 mL/h were defined as the good diuretic response group, and those with a urine output <100 mL/h during the first 6 hours of carperitide administration were defined as the poor diuretic response group. Multivariate analysis was used to examine the predictors of good diuretic response. The relationship between the time from intravenous furosemide to carperitide administration and urine output was also investigated.

FINDINGS

The patients' median age was 77 (range: 28-99) years, and 75.5% had New York Heart Association stage IV acute heart failure. The median urine output within 6 hours of carperitide administration was 104.5 (range: 6.6-1571.3) mL/h, and 118 patients (53.6%) showed a good diuretic response. Significant predictors of good diuretic response were age < 75 years [odds ratio (OR) 4.186; 95% confidence interval (CI), 2.129-8.230; P < 0.001], no prior use of loop diuretics (OR 2.155; 95% CI, 1.104-4.207; P = 0.024), blood urea nitrogen <20 mg/dL (OR 2.637; 95% CI, 1.340-5.190; P = 0.005), and white blood cell count <8.6 × 109/L (OR 3.162; 95% CI, 1.628-6.140; P = 0.001). The median urine output in the group with <2 hours between intravenous furosemide and carperitide administration was significantly higher than that in the group with an interval >6 hours [127.3; interquartile range (IQR), 77.6-216.2 mL/h vs. 66.2; IQR. 51.8-114.8 mL/h; P = 0.012).

IMPLICATIONS

The 4 predictors (age, no prior use of loop diuretics, blood urea nitrogen, and white blood cell count) of good diuretic response are useful indicators to support decision-making for carperitide administration. Additionally, the administration of carperitide within 2 hours of intravenous furosemide may lead to the improvement of pulmonary congestion.

Analysis and prediction of readmissions for heart failure in the first year after discharge with INCA score

To determine the readmissions trends and the comorbidities of patients with heart failure that most influence hospital readmission rates. Heart failure (HF) is one of the most prevalent health problems as it causes loss of quality of life and increased health-care costs. Its prevalence increases with age and is a major cause of re-hospitalisation within 30 days after discharge. INCA study had observational and ambispective design, including 4,959 patients from 2000 to 2019, with main diagnosis of HF in Extremadura (Spain). The variables examined were collected from discharge reports. To develop the readmission index, capable of discriminating the population with higher probability of re-hospitalisation, a Competing-risk model was generated. Readmission rate have increased over the period under investigation. The main predictors of readmission were: age, diabetes mellitus, presence of neoplasia, HF without previous hospitalisation, atrial fibrillation, anaemia, previous myocardial infarction, obstructive pulmonary disease (COPD) and chronic kidney disease (CKD). These variables were assigned values with balanced weights, our INCA index showed that the population with values greater than 2 for men and women were more likely to be re-admitted. Previous HF without hospital admission, CKD, and COPD appear to have the greatest effect on readmission. Our index allowed us to identify patients with different risks of readmission.

Analysis of the Larissa Heart Failure Risk Score: Predictive Value in 9207 Patients Hospitalized for Heart Failure from a Single Center

Early risk stratification is of outmost clinical importance in hospitalized patients with heart failure (HHF). We examined the predictive value of the Larissa Heart Failure Risk Score (LHFRS) in a large population of HHF patients from the Cleveland Clinic. A total of 13,309 admissions for heart failure (HF) from 9207 unique patients were extracted from the Cleveland Clinic's electronic health record system. For each admission, components of the 3-variable simple LHFRS were obtained, including hypertension history, myocardial infarction history, and red blood cell distribution width (RDW) ≥ 15%. The primary outcome was a HF readmission and/or all-cause mortality at one year, and the secondary outcome was all-cause mortality at one year of discharge. For both outcomes, all variables were statistically significant, and the Kaplan-Meier curves were well-separated and in a consistent order (Log-rank test p-value < 0.001). Higher LHFRS values were found to be strongly related to patients experiencing an event, showing a clear association of LHFRS with this study outcomes. The bootstrapped-validated area under the curve (AUC) for the logistic regression model for each outcome revealed a C-index of 0.64 both for the primary and secondary outcomes, respectively. LHFRS is a simple risk model and can be utilized as a basis for risk stratification in patients hospitalized for HF.

Comprehensive vasodilatation in women with acute heart failure: Novel insights from the GALACTIC randomized controlled trial

AIMS

Sex-specific differences in acute heart failure (AHF) are both relevant and underappreciated. Therefore, it is crucial to evaluate the risk/benefit ratio and the implementation of novel AHF therapies in women and men separately.

METHODS AND RESULTS

We performed a pre-defined sex-specific analysis in AHF patients randomized to a strategy of early intensive and sustained vasodilatation versus usual care in an international, multicentre, open-label, blinded endpoint trial. Inclusion criteria were AHF with increased plasma concentrations of natriuretic peptides, systolic blood pressure ≥100 mmHg, and plan for treatment in a general ward. Among 781 eligible patients, 288 (37%) were women. Women were older (median 83 vs. 76 years), had a lower body weight (median 64.5 vs. 77.6 kg) and lower estimated glomerular filtration rate (median 48 vs. 54 ml/min/1.73 m2 ). The primary endpoint, a composite of all-cause mortality or rehospitalization for AHF at 180 days, showed a significant interaction of treatment strategy and sex (p for interaction = 0.03; hazard ratio adjusted for female sex 1.62, 95% confidence interval 1.05-2.50; p = 0.03). The combined endpoint occurred in 53 women (38%) in the intervention group and in 35 (24%) in the usual care group. The implementation of rapid up-titration of renin-angiotensin-aldosterone system (RAAS) inhibitors was less successful in women versus men in the overall cohort and in patients with heart failure with reduced ejection fraction (median discharge % target dose in patients randomized to intervention: 50% in women vs. 75% in men).

CONCLUSION

Rapid up-titration of RAAS inhibitors was less successfully implemented in women possibly explaining their higher rate of all-cause mortality and rehospitalization for AHF.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov, unique identifier NCT00512759.

Predictive Model of All-Cause Death in Patients with Heart Failure using Heart Rate Variability

BACKGROUND

Central Illustration : Predictive Model of All-Cause Death in Patients with Heart Failure using Heart Rate Variability.

BACKGROUND

Short and long-duration heart rate variability (HRV) data from Holter monitoring could identify predictors of all-cause death in heart failure (HF) patients.

OBJECTIVES

To build a predictive model of all-cause death in patients with HF using HRV.

METHODS

Retrospective study including patients with suspected or confirmed HF who were admitted for decompensated HF or syncope that underwent Holter monitoring. In analysis of augmented sympathetic tonus, we evaluated the lowest HRV in nonoverlapping 10-minutes periods throughout 24h continuous electrocardiographic signal recording (short HRV variables). Variables with p<0.01 were included in a multivariate Cox regression model to determine the occurrence of the all-cause death. Variables with statistical significance in Cox regression were chosen to build the predictive model. P<0.05 was considered significant.

RESULTS

A total of 116 patients were included, mean age of 71.9±16.3 years, 45.7% men, mean follow-up of 2.83±1.27 years. Thirty-nine deaths occurred (33.6%). By comparing survivors vs. non-survivors, the variables that showed statistical significance were lowest SDNN, lowest rMSSD, age and left ventricular ejection fraction (LVEF). In Cox regression, independent predictors of all-cause death were: age>69 years (HR 3.95, 95%CI 1.64-9.52); LVEF≤57% (HR 4.70, 95%CI 2.38-9.28) and lowest rMSSD≤12ms (HR 5.54, 95%CI 2.04-15.08). An integer value was assigned to each variable. Score<3 showed AUC=0.802 (95%CI 0.72-0.87).

CONCLUSION

In HF patients hospitalized for decompensated HF or syncope, independent long-term predictors of all-cause death were age, LVEF, and 10-minutes rMSSD. These findings indicate that even brief moments of high sympathetic tone can impact survival, specifically in the elderly and patients with HF with reduced ejection fraction.

Examining predictors for 6-month mortality and healthcare utilization for patients admitted for heart failure in the acute care setting

BACKGROUND

Acute heart failure (AHF) is a leading cause of mortality and hospitalization. Past studies reported increased healthcare spending in the last year of life in high-income countries, and this has been characterized as inappropriate healthcare resource utilization. The study aimed to examine potentially (in)appropriate healthcare utilization by comparing healthcare utilization patterns across predicted and observed 6-month mortality among patients admitted for HF.

METHODS

We conducted a retrospective cohort study among patients presenting at the emergency department (ED) of a tertiary hospital with HF as primary diagnosis and admitted after their ED discharge. We used LASSO Cox proportional hazards models to predict 6-month mortality, and estimated healthcare utilization patterns of predicted and observed mortality across inpatient healthcare services.

RESULTS

3946 patients were admitted into the emergency department with a primary diagnosis of HF. From 57 candidate variables, 17 were retained in the final 6- month mortality model (C-statistic 0.66). Patients who died within 6-months of ED admission had longer length of stay (LOS) and less inpatient surgeries than those who survived. Patients with a greater predicted mortality risk were admitted to the ICU more often and had a longer LOS than those with a lower predicted mortality risk.

CONCLUSIONS

There were significant differences in healthcare resource utilization in patients admitted for AHF across predicted versus actual mortality. Lack of information on patients' preferences prevents the estimation of (in)appropriateness. Future studies should account for these considerations to estimate inappropriate healthcare utilization among these patients.

Personalized lifetime prediction of survival and treatment benefit in patients with heart failure with reduced ejection fraction: The LIFE-HF model

AIMS

Although trials have proven the group-level effectiveness of various therapies for heart failure with reduced ejection fraction (HFrEF), important differences in absolute effectiveness exist between individuals. We developed and validated the LIFEtime-perspective for Heart Failure (LIFE-HF) model for the prediction of individual (lifetime) risk and treatment benefit in patients with HFrEF.

METHODS AND RESULTS

Cox proportional hazards functions with age as the time scale were developed in the PARADIGM-HF and ATMOSPHERE trials (n = 15 415). Outcomes were cardiovascular death, heart failure (HF) hospitalization or cardiovascular death, and non-cardiovascular mortality. Predictors were age, sex, New York Heart Association class, prior HF hospitalization, diabetes mellitus, extracardiac vascular disease, systolic blood pressure, left ventricular ejection fraction, N-terminal pro-B-type natriuretic peptide, and glomerular filtration rate. The functions were combined in life-tables to predict individual overall and HF hospitalization-free survival. External validation was performed in the SwedeHF registry, ASIAN-HF registry, and DAPA-HF trial (n = 51 286). Calibration of 2- to 10-year risk was adequate, and c-statistics were 0.65-0.74. An interactive tool was developed combining the model with hazard ratios from trials to allow estimation of an individual's (lifetime) risk and treatment benefit in clinical practice. Applying the tool to the development cohort, combined treatment with a mineralocorticoid receptor antagonist, sodium-glucose cotransporter 2 inhibitor, and angiotensin receptor-neprilysin inhibitor was estimated to afford a median of 2.5 (interquartile range [IQR] 1.7-3.7) and 3.7 (IQR 2.4-5.5) additional years of overall and HF hospitalization-free survival, respectively.

CONCLUSION

The LIFE-HF model enables estimation of lifelong overall and HF hospitalization-free survival, and (lifetime) treatment benefit for individual patients with HFrEF. It could serve as a tool to improve the management of HFrEF by facilitating personalized medicine and shared decision-making.

Development and validation of a prediction model for in-hospital death in patients with heart failure and atrial fibrillation

BACKGROUND

To develop a prediction model for in-hospital mortality of patients with heart failure (HF) and atrial fibrillation (AF).

METHODS

This cohort study extracted the data of 10,236 patients with HF and AF upon intensive care unit (ICU) from the Medical Information Mart for Intensive Care (MIMIC). The subjects from MIMIC-IV were divided into the training set to construct the prediction model, and the testing set to verify the performance of the model. The samples from MIMIC-III database and eICU-CRD were included as the internal and external validation set to further validate the predictive value of the model, respectively. Univariate and multivariable Logistic regression analyses were used to explore predictors for in-hospital death in patients with HF and AF. The receiver operator characteristic (ROC), calibration curves and the decision curve analysis (DCA) curves were plotted to evaluate the predictive values of the model.

RESULTS

The mean survival time of participants from MIMIC-III was 11.29 ± 10.05 days and the mean survival time of participants from MIMIC-IV was 10.56 ± 9.19 days. Simplified acute physiology score (SAPSII), red blood cell distribution width (RDW), beta-blocker, race, respiratory rate, urine output, coronary artery bypass grafting (CABG), Charlson comorbidity index, renal replacement therapies (RRT), antiarrhythmic, age, and anticoagulation were predictors finally included in the prediction model. The AUC of our prediction model was 0.810 (95%CI: 0.791-0.828) in the training set, 0.757 (95%CI: 0.729-0.786) in the testing set, 0.792 (95%CI: 0.774-0.810) in the internal validation set, and 0.724 (95%CI: 0.687-0.762) in the external validation set. The calibration curves of revealed that the predictive probabilities of our model for the in-hospital death in patients with HF and AF deviated slightly from the ideal model. The DCA curves revealed that the use of our prediction model increased the net benefit than use no model.

CONCLUSION

The prediction model had good discriminative ability, and might provide a tool to timely identify patients with HF complicated with AF who were at high risk of in-hospital mortality.

Increased circulating phenylacetylglutamine concentration elevates the predictive value of cardiovascular event risk in heart failure patients

BACKGROUND

Phenylacetylglutamine (PAGln)-a newly discovered microbial metabolite produced by phenylalanine metabolism-is reportedly associated with cardiovascular events via adrenergic receptors. Nonetheless, its association with cardiovascular outcomes in heart failure (HF) patients remains unknown.

OBJECTIVES

This study aimed to prospectively investigate the prognostic value of PAGln for HF.

METHODS

Plasma PAGln levels were quantified by liquid chromatography-tandem mass spectrometry. We first assessed the association between plasma PAGln levels and the incidence of adverse cardiovascular events in 3152 HF patients (including HF with preserved and reduced ejection fraction) over a median follow-up period of 2 years. The primary endpoint was the composite of cardiovascular death or heart transplantation. We then assessed the prognostic role of PAGln in addition to the classic biomarker N-terminal pro-B-type natriuretic peptide (NT-proBNP). The correlation between PAGln levels and β-blocker use was also investigated.

RESULTS

In total, 520 cardiovascular deaths or heart transplantations occurred in the HF cohort. Elevated PAGln levels were independently associated with a higher risk of the primary endpoint in a dose-response manner, regardless of HF subtype. Concurrent assessment of PAGln and NT-proBNP levels enhanced risk stratification among HF patients. PAGln further showed prognostic value at low NT-proBNP levels. Additionally, the interaction effects between PAGln and β-blocker use were not significant.

CONCLUSIONS

Plasma PAGln levels are an independent predictor of an increased risk of adverse cardiovascular events in HF. Our work could provide joint and complementary prognostic value to NT-proBNP levels in HF patients.

Hospitalization for acute heart failure during non-working hours impacts on long-term mortality: the REPORT-HF registry

AIMS

Hospital admission during nighttime and off hours may affect the outcome of patients with various cardiovascular conditions due to suboptimal resources and personnel availability, but data for acute heart failure remain controversial. Therefore, we studied outcomes of acute heart failure patients according to their time of admission from the global International Registry to assess medical practice with lOngitudinal obseRvation for Treatment of Heart Failure.

METHODS AND RESULTS

Overall, 18 553 acute heart failure patients were divided according to time of admission into 'morning' (7:00-14:59), 'evening' (15:00-22:59), and 'night' (23:00-06:59) shift groups. Patients were also dichotomized to admission during 'working hours' (9:00-16:59 during standard working days) and 'non-working hours' (any other time). Clinical characteristics, treatments, and outcomes were compared across groups. The hospital length of stay was longer for morning (odds ratio: 1.08; 95% confidence interval: 1.06-1.10, P < 0.001) and evening shift (odds ratio: 1.10; 95% confidence interval: 1.07-1.12, P < 0.001) as compared with night shift. The length of stay was also longer for working vs. non-working hours (odds ratio: 1.03; 95% confidence interval: 1.02-1.05, P < 0.001). There were no significant differences in in-hospital mortality among the groups. Admission during working hours, compared with non-working hours, was associated with significantly lower mortality at 1 year (hazard ratio: 0.88; 95% confidence interval: 0.80-0.96, P = 0.003).

CONCLUSIONS

Acute heart failure patients admitted during the night shift and non-working hours had shorter length of stay but similar in-hospital mortality. However, patients admitted during non-working hours were at a higher risk for 1 year mortality. These findings may have implications for the health policies and heart failure trials.

Development and validation of a multivariate model for predicting heart failure hospitalization and mortality in patients receiving maintenance hemodialysis

BACKGROUND

Heart failure (HF) in patients undergoing maintenance hemodialysis (MHD) increases their hospitalization rates, mortality, and economic burden significantly. We aimed to develop and validate a predictive model utilizing contemporary deep phenotyping for individual risk assessment of all-cause mortality or HF hospitalization in patients on MHD.

MATERIALS AND METHODS

A retrospective review was conducted from January 2017 to October 2022, including 348 patients receiving MHD from four centers. The variables were adjusted by Cox regression analysis, and the clinical prediction model was constructed and verified.

RESULTS

The median follow-up durations were 14 months (interquartile range [IQR] 9-21) for the modeling set and 14 months (9-20) for the validation set. The composite outcome occurred in 72 (29.63%) of 243 patients in the modeling set and 39 (37.14%) of 105 patients in the validation set. The model predictors included age, albumin, history of cerebral hemorrhage, use of angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers/"sacubitril/valsartan", left ventricular ejection fraction, urea reduction ratio, N-terminal prohormone of brain natriuretic peptide, and right atrial size. The C-index was 0.834 (95% CI 0.784-0.883) for the modeling set and 0.853 (0.798, 0.908) for the validation set. The model exhibited excellent calibration across the complete risk profile, and the decision curve analysis (DCA) suggested its ability to maximize patient benefits.

CONCLUSION

The developed prediction model offered an accurate and personalized assessment of HF hospitalization risk and all-cause mortality in patients with MHD. It can be employed to identify high-risk patients and guide treatment and follow-up.

Impact of Social Support on Cardiovascular Risk Prediction Models: A Systematic Review

Cardiovascular diseases (CVD) stand as the primary causes of both mortality and morbidity on a global scale. Social factors such as low social support can increase the risk of developing heart diseases and have shown poor prognosis in cardiac patients. Resources such as PubMed and Google Scholar were searched using a boolean algorithm for articles published between 2003 and 2023. Eligible articles showed an association between social support and cardiovascular risks. A systematic review was conducted using the guidance published in the Cochrane Prognosis Method Group and the PRISMA checklist, for reviews of selected articles. A total of five studies were included in our final analysis. Overall, we found that participants with low social support developed cardiovascular events, and providing a good support system can decrease the risk of readmission in patients with a history of CVD. We also found that integrating social determinants in the cardiovascular risk prediction model showed improvement in accessing the risk. Population with good social support showed low mortality and decreased rate of readmission. There are various prediction models, but the social determinants are not primarily included while calculating the algorithms. Although it has been proven in multiple studies that including the social determinants of health (SDOH) improves the accuracy of cardiovascular risk prediction models. Hence, the inclusion of SDOH should be highly encouraged.

Exercise Oscillatory Ventilation Improves Heart Failure Prognostic Scores

BACKGROUND

Several heart failure (HF) prognostic risk scores are available to guide the ideal time for listing candidates for a heart transplant (HTx). The detection of exercise oscillatory ventilation (EOV) during cardiopulmonary exercise testing (CPET) is associated with advanced HF and a worse prognosis, and yet it is not accounted for in these risk scores. Therefore, this study aimed to assess whether EOV further adds prognostic value to HF scores.

METHODS

A single-centre retrospective cohort study was undertaken of consecutive HF patients with reduced ejection fraction (HFrEF) who underwent CPET from 1996 to 2018. The Heart Failure Survival Score (HFSS), Seattle Heart Failure Model (SHFM), Meta-analysis Global Group In Chronic Heart Failure (MAGGIC), and Metabolic Exercise Cardiac Kidney Index (MECKI) were calculated. The added value of EOV on top of those scores was assessed using a Cox proportional hazard model. The added discriminative power was also assessed by receiver operating characteristic curve comparison.

RESULTS

A total of 390 HF patients with a median age of 58 (IQR 50-65) years were investigated, of whom 78% were male and 54% had ischaemic heart disease. The median peak oxygen consumption was 15.7 mL/kg/min (IQR 12.8-20.1). Exercise oscillatory ventilation was detected in 153 (39.2%) patients. Over a median follow-up of 2 years, 61 patients died (49 due to a cardiovascular reason) and 54 had a HTx. Exercise oscillatory ventilation independently predicted the composite outcome of all-cause death and HTx. Furthermore, the presence of this ventilatory pattern significantly improved the prognostic performance of both HFSS and MAGGIC scores.

CONCLUSION

Exercise oscillatory ventilation was often found in a cohort of HF patients with reduced LVEF who underwent CPET. It was found that EOV added further prognostic value to contemporary HF scores, suggesting that this easily obtained parameter should be included in future modified HF scores.

Electronic Health Record Embedded Strategies for Improving Care of Patients With Heart Failure

PURPOSE

A majority of clinical decisions use the electronic health record (EHR) and there is an unmet need to use its capability to help providers to make evidence-based decisions that improve care for heart failure patients. These electronic nudges are rooted in the human psychology of decision-making and often target specific cognitive biases. This review outlines the development of novel EHR nudges and specific lessons learned from each experience to inform the development of future interventions.

RECENT FINDINGS

There have been several randomized clinical trials examining the impact of EHR alerts on quality of care for heart failure patients. These interventions have targeted both clinicians and patients. There are features of each trial that inform best practices and future directions for EHR nudges. Recent clinical trials have demonstrated that some EHR alerts can improve care for heart failure patients. These trials utilized default options, involved clinicians in the alert design process, provided actionable recommendations, and aimed to minimize disruptions to typical workflow. Alerts aimed at improving care should be examined in a randomized fashion in order to evaluate their impact on clinician satisfaction and patient care.

Prognostic Value of Liver Fibrotic Markers in Patients With Heart Failure

Several liver fibrotic markers are associated with prognosis in patients with heart failure (HF). However, the optimal markers for outcome prediction remain unclear. This study aimed to simultaneously investigate the prognostic value of liver fibrotic markers and the associations between these markers and clinical parameters in patients with HF without organic liver disease. We prospectively examined 211 consecutive patients with chronic HF between April 2018 and August 2021, excluding those with organic liver disease, using liver magnetic resonance imaging and ultrasound. A total of 7 representative liver fibrotic markers were measured in all patients. The primary outcome of interest was the composite of all-cause death and hospitalization for worsening HF. During a median follow-up period of 747 (interquartile range 465 to 1,042) days, the primary outcome occurred in 45 patients. Patients with higher hyaluronic acid and type III procollagen N-terminal peptide (P-III-P) levels showed a significantly higher incidence of the primary outcome than those without (p <0.001 and p = 0.005, respectively). The multivariable Cox regression analysis revealed that hyaluronic acid and P-III-P levels were independently associated with the risk of adverse events (hazard ratio 1.84, 95% confidence interval 1.18 to 2.87 and hazard ratio 2.89, 95% confidence interval 1.32 to 6.34, respectively) even after adjustment for a mortality prediction model, whereas the other 5 markers were not associated with the primary outcome. In conclusion, among the representative liver fibrotic markers, hyaluronic acid and P-III-P might be the optimal markers for outcome prediction in patients with HF.

Risk prediction models for mortality and readmission in patients with acute heart failure: A protocol for systematic review, critical appraisal, and meta-analysis

INTRODUCTION

A considerable number of risk models, which predict outcomes in mortality and readmission rates, have been developed for patients with acute heart failure (AHF) to help stratify patients by risk level, improve decision making, and save medical resources. However, some models exist in a clinically useful manner such as risk scores or online calculators, while others are not, providing only limited information that prevents clinicians and patients from using them. The reported performance of some models varied greatly when predicting at multiple time points and being validated in different cohorts, which causes model users uncertainty about the predictive accuracy of these models. The foregoing leads to users facing difficulties in the selection of prediction models, and even sometimes being reluctant to utilize models. Therefore, a systematic review to assess the performance at multiple time points, applicability, and clinical impact of extant prediction models for mortality and readmission in AHF patients is essential. It may facilitate the selection of models for clinical implementation.

METHOD AND ANALYSIS

Four databases will be searched from their inception onwards. Multivariable prognostic models for mortality and/or readmission in AHF patients will be eligible for review. Characteristics and the clinical impact of included models will be summarized qualitatively and quantitatively, and models with clinical utility will be compared with those without. Predictive performance measures of included models with an analogous clinical outcome appraised repeatedly, will be compared and synthesized by a meta-analysis. Meta-analysis of validation studies for a common prediction model at the same time point will also be performed. We will also provide an overview of critical appraisal of the risk of bias, applicability, and reporting transparency of included studies using the PROBAST tool and TRIPOD statement.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration number CRD42021256416.

Heart Failure Emergency Readmission Prediction Using Stacking Machine Learning Model

Heart failure is a devastating disease that has high mortality rates and a negative impact on quality of life. Heart failure patients often experience emergency readmission after an initial episode, often due to inadequate management. A timely diagnosis and treatment of underlying issues can significantly reduce the risk of emergency readmissions. The purpose of this project was to predict emergency readmissions of discharged heart failure patients using classical machine learning (ML) models based on Electronic Health Record (EHR) data. The dataset used for this study consisted of 166 clinical biomarkers from 2008 patient records. Three feature selection techniques were studied along with 13 classical ML models using five-fold cross-validation. A stacking ML model was trained using the predictions of the three best-performing models for final classification. The stacking ML model provided an accuracy, precision, recall, specificity, F1-score, and area under the curve (AUC) of 89.41%, 90.10%, 89.41%, 87.83%, 89.28%, and 0.881, respectively. This indicates the effectiveness of the proposed model in predicting emergency readmissions. The healthcare providers can intervene pro-actively to reduce emergency hospital readmission risk and improve patient outcomes and decrease healthcare costs using the proposed model.

Auricular Vagal Neuromodulation and its Application in Patients with Heart Failure and Reduced Ejection Fraction

BACKGROUND

The autonomic nervous system (ANS) imbalance in heart failure (HF) creates a vicious cycle, excess sympathetic activity, and decreased vagal activity contributing to the worsening of HF. Low-intensity transcutaneous electrical stimulation of the auricular branch of the vagus nerve (taVNS) is well tolerated and opens new therapeutic possibilities.

OBJECTIVES

To hypothesize the applicability and benefit of taVNS in HF through intergroup comparison of echocardiography parameters, 6-minute walk test, Holter heart rate variability (SDNN and rMSSD), Minnesota quality of life questionnaire, and functional class by the New York Heart Association. In comparisons, p values <0.05 were considered significant.

METHODS

Prospective, double-blind, randomized clinical study with sham methodology, unicentric. Forty-three patients were evaluated and divided into 2 groups: Group 1 received taVNS (frequencies 2/15 Hz), and Group 2 received sham. In comparisons, p values <0.05 were considered significant.

RESULTS

In the post-intervention phase, it was observed that Group 1 had better rMSSD (31 x 21; p = 0.046) and achieved better SDNN (110 vs. 84, p = 0.033). When comparing intragroup parameters before and after the intervention, it was observed that all of them improved significantly in group 1, and there were no differences in group 2.

CONCLUSION

taVNS is a safe to perform and easy intervention and suggests a probable benefit in HF by improving heart rate variability, which indicates better autonomic balance. New studies with more patients are needed to answer the questions raised by this study.

The impact of commercial health datasets on medical research and health-care algorithms

As the health-care industry emerges into a new era of digital health driven by cloud data storage, distributed computing, and machine learning, health-care data have become a premium commodity with value for private and public entities. Current frameworks of health data collection and distribution, whether from industry, academia, or government institutions, are imperfect and do not allow researchers to leverage the full potential of downstream analytical efforts. In this Health Policy paper, we review the current landscape of commercial health data vendors, with special emphasis on the sources of their data, challenges associated with data reproducibility and generalisability, and ethical considerations for data vending. We argue for sustainable approaches to curating open-source health data to enable global populations to be included in the biomedical research community. However, to fully implement these approaches, key stakeholders should come together to make health-care datasets increasingly accessible, inclusive, and representative, while balancing the privacy and rights of individuals whose data are being collected.

Comparison of Machine Learning Algorithms for Predicting Hospital Readmissions and Worsening Heart Failure Events in Patients With Heart Failure With Reduced Ejection Fraction: Modeling Study

BACKGROUND

Heart failure (HF) is highly prevalent in the United States. Approximately one-third to one-half of HF cases are categorized as HF with reduced ejection fraction (HFrEF). Patients with HFrEF are at risk of worsening HF, have a high risk of adverse outcomes, and experience higher health care use and costs. Therefore, it is crucial to identify patients with HFrEF who are at high risk of subsequent events after HF hospitalization.

OBJECTIVE

Machine learning (ML) has been used to predict HF-related outcomes. The objective of this study was to compare different ML prediction models and feature construction methods to predict 30-, 90-, and 365-day hospital readmissions and worsening HF events (WHFEs).

METHODS

We used the Veradigm PINNACLE outpatient registry linked to Symphony Health's Integrated Dataverse data from July 1, 2013, to September 30, 2017. Adults with a confirmed diagnosis of HFrEF and HF-related hospitalization were included. WHFEs were defined as HF-related hospitalizations or outpatient intravenous diuretic use within 1 year of the first HF hospitalization. We used different approaches to construct ML features from clinical codes, including frequencies of clinical classification software (CCS) categories, Bidirectional Encoder Representations From Transformers (BERT) trained with CCS sequences (BERT + CCS), BERT trained on raw clinical codes (BERT + raw), and prespecified features based on clinical knowledge. A multilayer perceptron neural network, extreme gradient boosting (XGBoost), random forest, and logistic regression prediction models were applied and compared.

RESULTS

A total of 30,687 adult patients with HFrEF were included in the analysis; 11.41% (3184/27,917) of adults experienced a hospital readmission within 30 days of their first HF hospitalization, and nearly half (9231/21,562, 42.81%) of the patients experienced at least 1 WHFE within 1 year after HF hospitalization. The prediction models and feature combinations with the best area under the receiver operating characteristic curve (AUC) for each outcome were XGBoost with CCS frequency (AUC=0.595) for 30-day readmission, random forest with CCS frequency (AUC=0.630) for 90-day readmission, XGBoost with CCS frequency (AUC=0.649) for 365-day readmission, and XGBoost with CCS frequency (AUC=0.640) for WHFEs. Our ML models could discriminate between readmission and WHFE among patients with HFrEF. Our model performance was mediocre, especially for the 30-day readmission events, most likely owing to limitations of the data, including an imbalance between positive and negative cases and high missing rates of many clinical variables and outcome definitions.

CONCLUSIONS

We predicted readmissions and WHFEs after HF hospitalizations in patients with HFrEF. Features identified by data-driven approaches may be comparable with those identified by clinical domain knowledge. Future work may be warranted to validate and improve the models using more longitudinal electronic health records that are complete, are comprehensive, and have a longer follow-up time.

Functional outcome after cardiac rehabilitation and its association with survival in heart failure across the spectrum of ejection fraction

BACKGROUND

There is limited evidence regarding the effects of cardiac rehabilitation (CR) in patients with heart failure and preserved ejection fraction (HFpEF).

METHODS

We studied 1784 patients admitted to inpatient CR. The patients were grouped into HFpEF (EF≥0.50), HF with mildly reduced EF (HFmrEF; EF 41-49), and HF with reduced EF (HFrEF; EF≤0.40). A standardized 6-min walking test was performed at admission and discharge. Measures of functional outcome were: (1) absolute increase in 6-min walking distance (6MWD) from admission to discharge >50 m and (2) increase in 6MWD to ≥300 among the patients who walked <300 m at admission.

RESULTS

After adjustment, the patients with HFpEF or HFmrEF were as likely as those with HFrEF to achieve an increase in 6MWD >50 m (odds ratio 0.95 [95%CI 0.71-1.24; p=0.648] and 1.04 [95%CI 0.77-1.41; p=0.769], respectively) or an increase in 6MWD to ≥300 m (odds ratio 0.79 [95%CI 0.51-1.23; p=0.299] and 0.65 [95%CI 0.38-1.12; p=0.118], respectively). The adjusted hazard ratio of 5-year mortality for patients who achieved an increase in 6MWD >50 m was 0.60 (95%CI 0.51-0.71; p<0.001) and that for patients who achieved an increase in 6MWD at discharge to ≥300 m 0.61 (95%CI 0.48-0.79; p<0.001). In each EF group, both outcomes remained independently associated with improved survival.

CONCLUSIONS

Our data suggest that patients with HFpEF or HFmrEF are as likely as those with HFrEF to benefit from CR in terms of functional improvement. Functional improvement was independently associated with improved long-term survival, regardless of EF.

A Prognostic Model Based on Clinical Biomarkers for Heart Failure in Adult Patients Following Allogeneic Hematopoietic Stem Cell Transplantation

Heart failure (HF) is an uncommon but serious cardiovascular complication after allogeneic hematopoietic stem cell transplantation (allo-HSCT). Unfortunately, knowledge about early mortality prognostic factors in patients with HF after allo-HSCT is limited, and an easy-to-use prognostic model is not available. This study aimed to develop and validate a clinical-biomarker prognostic model capable of predicting HF mortality following allo-HSCT that uses a combination of variables readily available in clinical practice. To investigate this issue, we conducted a retrospective analysis at our center with 154 HF patients who underwent allo-HSCT between 2008 and 2021. The patients were separated according to the time of transplantation, with 100 patients composing the derivation cohort and the other 54 patients composing the external validation cohort. We first calculated the univariable association for each variable with 2-month mortality in the derivation cohort. We then included the variables with a P value <.1 in univariate analysis as candidate predictors in the multivariate analysis using a backward stepwise logistic regression model. Variables remaining in the final model were identified as independent prognostic factors. To predict the prognosis of HF, a scoring system was established, and scores were assigned to the prognostic factors based on the regression coefficient. Finally, 4 strongly significant independent prognostic factors for 2-month mortality from HF were identified using multivariable logistic regression methods with stepwise variable selection: pulmonary infection (P = .005), grade III to IV acute graft-versus-host disease (severe aGVHD; P = .033), lactate dehydrogenase (LDH) >426 U/L (P = .049), and brain natriuretic peptide (BNP) >1799 pg/mL (P = .026). A risk grading model termed the BLIPS score (for BNP, LDH, cardiac troponin I, pulmonary infection, and severe aGVHD) was constructed according to the regression coefficients. The validated internal C-statistic was .870 (95% confidence interval [CI], .798 to .942), and the external C-statistic was .882 (95% CI, .791-.973). According to the calibration plots, the model-predicted probability correlated well with the actual observed frequencies. The clinical use of the prognostic model, according to decision curve analysis, could benefit HF patients. The BLIPS model in our study can serve to identify HF patients at higher risk for mortality early, which might aid designing timely targeted therapies and eventually improving patients' survival and prognosis.

The importance of re-evaluating the risk score in heart failure patients: An analysis from the Metabolic Exercise Cardiac Kidney Indexes (MECKI) score database

BACKGROUND

The role of risk scores in heart failure (HF) management has been highlighted by international guidelines. In contrast with HF, which is intrinsically a dynamic and unstable syndrome, all its prognostic studies have been based on a single evaluation. We investigated whether time-related changes of a well-recognized risk score, the MECKI score, added prognostic value. MECKI score is based on peak VO₂, VE/VCO₂ slope, Na⁺, LVEF, MDRD and Hb.

METHODS

A multi-centre retrospective study was conducted involving 660 patients who performed MECKI re-evaluation at least 6 months apart. Based on the difference between II and I evaluation of MECKI values (MECKI II - MECKI I = ∆ MECKI) the study population was divided in 2 groups: those presenting a score reduction (∆ MECKI <0, i.e. clinical improvement), vs. patients presenting an increase (∆ MECKI >0, clinical deterioration).

RESULTS

The prognostic value of MECKI score is confirmed also when re-assessed during follow-up. The group with improved MECKI (366 patients) showed a better prognosis compared to patients with worsened MECKI (294 patients) (p < 0.0001). At 1st evaluation, the two groups differentiated by LVEF, V_E/VCO₂ slope and blood Na⁺ concentration, while at 2nd evaluation they differentiated in all 6 parameters considered in the score. The patients who improved MECKI score, improved in all components of the score but hemoglobin, while patients who worsened the score, worsened all parameters.

CONCLUSIONS

This study shows that re-assessment of MECKI score identifies HF subjects at higher risk and that score improvement or deterioration regards several MECKI score generating parameters confirming the holistic background of HF.

Applicability of new proposed criteria for iron deficiency in Japanese patients with heart failure

AIMS

Iron deficiency (ID) is a common co-morbidity in patients with heart failure (HF). A recent study showed that ID defined by the current guideline criteria was not associated with worse clinical outcomes, and new ID criteria was proposed in patients with HF. However, the external applicability of the new proposed criteria is unclear. We sought to investigate the applicability of the proposed ID criteria in Japanese patients with HF.

METHODS AND RESULTS

We prospectively examined 763 patients with chronic HF from a Japanese multicentre registry. The proposed ID criteria were transferrin saturation (TSAT) < 20% and serum iron ≤13 mmol/L and the guideline ID criteria were serum ferritin <100 ng/mL or, when ferritin was 100-299 ng/mL, TSAT <20%. Among all patients (456 male, mean age 71 ± 13 years), 213 (28%) and 444 (58%) met the proposed and guideline ID criteria, respectively. During a median follow-up period of 436 days (interquartile range 297-565), the primary outcome of all-cause mortality occurred in 56 (7%) patients. There was no significant difference in the primary outcome between the patients with and without guideline ID criteria (P = 0.32), whereas patients with serum iron ≤10 μmol/L showed higher mortality (P = 0.002). In multivariable Cox regressions, the proposed ID criteria, but not guideline ID criteria, were independently associated with the risk of all-cause mortality (HR 2.01, 95% CI 1.16-3.51 and HR 1.32, 95% CI 0.76-2.28, respectively), even after adjustment for covariates.

CONCLUSIONS

When defined by the proposed criteria and not the guideline criteria, ID was associated with higher mortality in patients with chronic HF, suggesting that the proposed ID criteria is applicable to the Japanese population.

Determinants of ejection fraction improvement in heart failure patients with reduced ejection fraction

AIMS

This study aimed to investigate the prognostic value of dynamic changes in left ventricular ejection fraction (EF) for cardiovascular (CV) outcomes in an all-comer heart failure (HF) population with reduced EF (HFrEF, EF < 40%). We sought to identify independent factors related to improvement in EF and to identify risk factors for increased risk of CV events in the subgroups of improved EF (iEF) and non-improved EF (niEF), respecively.

METHODS AND RESULTS

This is a retrospective sub-analysis from the REDEAL HF trial, which included consecutive patients with chronic HF who were hospitalized from July 2009 to December 2017. Baseline and follow-up echocardiography data (interval ≥12 months) of 573 consecutive patients with HFrEF were analysed. iEF was defined as absolute improvement in EF ≥ 10% and follow-up EF over 40%. The primary endpoint was defined as a composite endpoint of cardiovascular (CV) death, CV hospitalization, or appropriate implantable cardioverter-defibrillator (ICD) therapy for ventricular arrhythmia. EF improved in 37.2% of patients with HFrEF during follow-up (median period of 17 months). iEF was independently associated with shorter HF duration (>4 vs. ≤4 years, odd ratio [OR] = 0.477, 95% CI 0.305-0.745), no coronary artery disease (CAD vs. no CAD, OR = 0.583, 95% CI 0.396-0.858), and no ICD implantation (ICD vs. no ICD, OR = 0.341, 95% CI 0.228-0.511). Compared with niEF, iEF was significantly and independently associated with lower all-cause mortality (22.1% vs. 31.1%, P = 0.019; hazard ratio [HR] = 0.674, 95% CI 0.469-0.968), lower CV mortality (8.9% vs. 16.1%, P = 0.015; HR = 0.539, 95% CI 0.317-0.916), and lower CV events risk (27.2% vs. 49.2%, P < 0.001; HR 0.519, 95% CI 0.381-0.708), after adjustment for age, sex, duration of HF, and other clinical risk factors. Hypertension (HR = 2.452, P = 0.032) and elevated N-terminal prohormone of brain natriuretic peptide (NT-proBNP >1153 pg/mL, HR = 4.372, P < 0.001) were identified as independent risk factors for CV events in the iEF subgroup. ICD implantation (HR = 1.533, P = 0.011), elevated NT-proBNP (HR = 1.626, P = 0.018), increased left atrial volume index (HR = 1.461, P = 0.021), reduced lateral mitral annular plane systolic excursion (HR = 1.478, P = 0.025), and reduced tricuspid plane systolic excursion (HR = 1.491, P = 0.039) were identified as risk factors for CV events in the niEF subgroup.

CONCLUSIONS

Improvement in EF is independently related to the longer survival and lower CV related mortality and hospitalization rate of HFrEF. Elevated baseline NT-proBNP is identified as the strongest prognostic factor associated with increased CV events risk in HFrEF patients both with and without improved EF, regardless of age, sex, duration of HF, and other clinical risk factors.

One-year rehospitalisation and mortality after acute heart failure hospitalisation: a competing risk analysis

OBJECTIVE

To identify factors that independently predict the risk of rehospitalisation and death after acute heart failure (AHF) hospital discharge in a real-world setting, considering death without rehospitalisation as a competing event.

METHODS

Single-centre, retrospective, observational study enrolling 394 patients discharged from an index AHF hospitalisation. Overall survival was evaluated using Kaplan-Meier and Cox regression models. For the risk of rehospitalisation, survival analysis considering competing risks was performed: rehospitalisation was the event of interest, and death without rehospitalisation was the competing event.

RESULTS

During the first year after discharge, 131 (33.3%) patients were rehospitalised for AHF and 67 (17.0%) died without being readmitted; the remaining 196 patients (49.7%) lived without further hospitalisations. The 1-year overall survival estimate was 0.71 (SE=0.02). After adjusting for gender, age and left ventricle ejection fraction, the results showed that the risk of death was higher in patients with dementia, higher levels of plasma creatinine (PCr), lower levels of platelet distribution width (PDW) and at Q4 of red cell distribution width (RDW). Multivariable models showed that the risk of rehospitalisation was increased in patients with atrial fibrillation, higher PCr or taking beta-blockers at discharge. Furthermore, the risk of death without AHF rehospitalisation was higher in males, those aged ≥80 years, patients with dementia or RDW at Q4 on admission (compared with Q1). Taking beta-blockers at discharge and having a higher PDW on admission reduced the risk of death without rehospitalisation.

CONCLUSION

When assessing rehospitalisation as a study endpoint, death without rehospitalisation should be considered a competing event in the analyses. Data from this study reveal that patients with atrial fibrillation, renal dysfunction or taking beta-blockers are more likely to be rehospitalised for AHF, while older men with dementia or high RDW are more prone to die without hospital readmission.

Influence of Meteorological Temperature and Pressure on the Severity of Heart Failure Decompensations

OBJECTIVE

To investigate the relationship between ambient temperature and atmospheric pressure (AP) and the severity of heart failure (HF) decompensations.

METHODS

We analysed patients coming from the Epidemioloy Acute Heart Failure Emergency (EAHFE) Registry, a multicentre prospective cohort study enrolling patients diagnosed with decompensated HF in 26 emergency departments (EDs) of 16 Spanish cities. We recorded patient and demographic data and maximum temperature (Tmax) and AP (APmax) the day before ED consultation. Associations between temperature and AP and severity endpoints were explored by logistic regression. We used restricted cubic splines to model continuous non-linear associations of temperature and AP with each endpoint.

RESULTS

We analysed 16,545 patients. Daily Tmax and APmax (anomaly) of the day before patient ED arrival ranged from 0.8 to 41.6° and from - 61.7 to 69.9 hPa, respectively. A total of 12,352 patients (75.2%) were hospitalised, with in-hospital mortality in 1171 (7.1%). The probability of hospitalisation by HF decompensation showed a U-shaped curve versus Tmax and an increasing trend versus APmax. Regarding temperature, hospitalisation significantly increased from 20 °C (reference) upwards (25 °C: OR = 1.12, 95% CI = 1.04-1.21; 40 °C: 1.65, 1.13-2.40) and below 5.4 °C (5 °C: 1.21, 1.01-1.46). Concerning the mean AP of the city (anomaly = 0 hPa), hospitalisation increased when APmax (anomaly) was above + 7.0 hPa (atmospheric anticyclone; + 10 hPa: 1.14, 1.05-1.24; + 30 hPa: 2.02. 1.35-3.03). The lowest probability of mortality also corresponded to cold-mild temperatures and low AP, with a significant increased risk only found for Tmax above 24.3 °C (25 °C: 1.13, 1.01-1.27; 40 °C: 2.05, 1.15-3.64) and APmax (anomaly) above + 3.4 hPa (+ 10 hPa: 1.21, 1.07-1.36; + 30 hPa: 1.73, 1.06-2.81). Sensitivity analysis confirmed the main analysis results.

CONCLUSION

Temperature and AP are independently associated with the severity of HF decompensations, with possible different effects on the need for hospitalisation and in-hospital mortality.

Long-Term Clinical Outcomes in Patients With Severe Tricuspid Regurgitation

Background The natural history and optimal interventional timing in patients with isolated severe tricuspid regurgitation (TR) have not been well studied. This study aimed to investigate long-term clinical outcomes and risk factors associated with poor prognosis in patients with isolated severe TR. Methods and Results Consecutive transthoracic echocardiographic examinations in 2877 patients with isolated severe TR were retrospectively reviewed. Patients with significant left-sided valve disease or repeated examinations were excluded. Primary outcome was defined as a composite of all-cause death and hospitalization for heart failure. Among the 613 enrolled patients (mean age, 74±13 years; men, 38%), 141 died, and 62 were hospitalized for heart failure during the median follow-up period of 26.5 (interquartile range, 6.0-57.9) months. The 5-year event-free rate was 60.1%. TR pressure gradient (adjusted hazard ratio [HR], 1.03 [95% CI, 1.01-1.04]), blood urea nitrogen (adjusted HR, 1.02 [95% CI, 1.01-1.04]), left atrial volume index (adjusted HR, 1.01 [95% CI, 1.002-1.02]), and serum albumin (adjusted HR, 0.56 [95% CI, 0.36-0.95]) were identified as independent predictors of adverse events. A risk model based on the 4 clinical factors that included pulmonary hypertension (TR pressure gradient >40 mm Hg), elevated blood urea nitrogen levels (>25 mg/dL), decreased albumin levels (<3.7 g/dL), and left atrial enlargement (left atrial volume index <34 mL/m²) revealed a graded increase in the risk of adverse events (P<0.001). Conclusions The prognosis of isolated severe TR is not always favorable. Careful attention should be paid to patients with concomitant risk factors, such as pulmonary hypertension, elevated blood urea nitrogen levels, decreased albumin levels, and left atrial enlargement.

Cardiac Rehabilitation for Older Women with Heart Failure

Background: the role that sex plays in impacting cardiac rehabilitation (CR) outcomes remains an important gap in knowledge. Methods: we assessed sex differences in clinical and functional outcomes in 2345 older patients with heart failure (HF) admitted to inpatient CR. Three outcomes were considered: (1) the composite outcome of death during the index admission to CR or transfer to acute care; (2) three-year mortality; (3) change in six-minute walking distance (6MWD) from admission to discharge. Sex differences in outcomes were assessed using multivariable Cox or logistic regression models. Results: the hazard ratios of the composite outcome and of three-year mortality for females vs. males were 0.71 (95%CI:0.50−1.00; p = 0.049) and 0.68 (95%CI:0.59−0.79; p < 0.001), respectively. The standardized mean difference in 6MWD increase from admission to discharge between males and females was 0.10. The odds ratio of achieving an increase in 6MWD at discharge to values higher than the optimal sex-specific thresholds for predicting mortality for females vs. males was 2.21 (95%CI:1.53−3.20; p < 0.001). Conclusion: our findings suggest that older females with HF undergoing CR have better prognosis and garner similar improvement in 6MWD compared with their male counterparts. Nonetheless, females were more likely to achieve levels of functional capacity predictive of improved survival.

Ambient temperature and atmospheric pressure at discharge as precipitating factors in immediate adverse events in patients treated for decompensated heart failure

To investigate the relationship of ambient temperature and atmospheric pressure (AP) at patient discharge after an episode of acute heart failure (AHF) with very early post-discharge adverse outcomes. We analyzed 14,656 patients discharged after an AHF episode from 26 hospitals in 16 Spanish cities. The primary outcome was the 7-day post-discharge combined adverse event (emergency department -ED- revisit or hospitalization due to AHF, or all-cause death), and secondary outcomes were these three adverse events considered individually. Associations (adjusted for patient and demographic conditions, and length of stay -LOS- during the AHF index episode) of temperature and AP with the primary and secondary outcomes were investigated. We used restricted cubic splines to model the continuous non-linear association of temperature and AP with each endpoint. Some sensitivity analyses were performed. Patients were discharged after a median LOS of 5 days (IQR = 1-10). The highest temperature at discharge ranged from - 2 to 41.6 °C, and AP was from 892 to 1037 hPa. The 7-day post-discharge combined event occurred in 1242 patients (8.4%), with percentages of 7-day ED-revisit, hospitalization and death of 7.8%, 5.1% and 0.9%, respectively. We found no association between the maximal temperature and AP on the day of discharge and the primary or secondary outcomes. Similarly, there were no significant associations when the analyses were restricted to hospitalized patients (median LOS = 7 days, IQR = 4-11) during the index event, or when lag-1, lag-2 or the mean of the 3 post-discharge days (instead of point estimation) of ambient temperature and AP were considered. Temperature and AP on the day of patient discharge are not independently associated with the risk of very early adverse events during the vulnerable post-discharge period in patients discharged after an AHF episode.

Mortality prediction upon hospital admission - the value of clinical assessment: A retrospective, matched cohort study

Accurate prediction of mortality upon hospital admission is of great value, both for the sake of patients and appropriate resources' allocation. A myriad of assessment tools exists for this purpose. The evidence relating to the comparative value of clinical assessment versus established indexes are scarce. We analyzed the accuracy of a senior physician's clinical assessment in a retrospective cohort of patients in a crude, general patients' population and later on a propensity matched patients' population. In one department of internal medicine in a tertiary hospital, of 9891 admitted patients, 973 (10%) were categorized as prone to death in a 6-months' duration by a senior physician. The risk of death was significantly higher for these patients [73.1% vs 14.1% mortality within 180 days; hazard ratio (HR) = 7.58; confidence intervals (CI) 7.02-8.19, P < .001]. After accounting for multiple, other patients' variables associated with increased risk of mortality, the correlation remained significant (HR = 3.25; CI 2.85-3.71, P < .001). We further performed a propensity matching analysis (a subgroup of 710 patients, subdivided to two groups with 355 patients each): survival rates were as low as 45% for patients categorized as prone to death compared to 78% in patients who weren't categorized as such (P < .001). Reliance on clinical evaluation, done by an experienced senior physician, is an appropriate tool for mortality prediction upon hospital admission, achieving high accuracy rates.

Prognostic Value of Left Atrial Strain in Heart Failure: A Systematic Review and Meta-Analysis

Background

Heart failure (HF) is a global health problem with high morbidity and mortality. Recently, the association between peak atrial longitudinal strain (PALS) and clinical outcomes of HF has gained increasing attention. Our aim was to systematically assess the prognostic value of PALS for adverse events in HF.

Methods

PubMed, Embase, and Scopus databases were systematically searched from inception to 30 April 2022. Studies in which PALS was assessed to predict adverse outcomes in adult patients with HF were included. Study selection, quality assessment, and data extraction were performed independently by two authors. The primary endpoints were all-cause death and cardiac hospitalization.

Results

Among 7,787 patients in 17 included studies, 3,029 (38.9%) experienced the primary endpoint. Patients with events had lower PALS than those without events [weighted mean difference (WMD) 6.17, 95% confidence interval (CI) 3.09–9.26, p < 0.001]. Each unit increment of PALS was independently associated with decreased risk for the primary endpoint [hazard ratio (HR) 0.96, 95% CI 0.94–0.98, p < 0.001]. The addition of PALS significantly improved the predictive power of conventional risk models [net reclassification index (NRI) 0.22, 95% CI 0.06–0.39, p = 0.008].

Conclusion

Peak atrial longitudinal strain was an independent predictor for all-cause mortality and cardiac hospitalization in patients with HF, highlighting the clinical importance of left atrial (LA) deformation in the prognosis of HF.

Systematic Review Registration

[www.crd.york.ac.uk/prospero/], identifier [CRD42020185034].

Prognostic value of RDW alone and in combination with NT-proBNP in patients with heart failure

BACKGROUND

Red blood cell distribution width (RDW) and N-terminal pro brain natriuretic peptide (NT-proBNP) may predict the prognosis of heart failure (HF). However, the impact of combined RDW and NT-proBNP levels as a prognostic marker of HF remains unclear and the significance of this combination at various time-points has not been sufficiently studied.

HYPOTHESIS

RDW can predict prognosis in HF at various time-points and combination with NT-proBNP improves the prognostic value.

METHODS

Patients admitted to HF care unit of Fuwai Hospital CAMS&PUMC (Beijing, China) with a diagnosis of HF from November 2008 to November 2018 were analyzed retrospectively.

RESULTS

In total, 3231 patients with available RDW data at admission were evaluated (median age 58 years, 71.9% males, 39.7% coronary heart disease, 68.6% New York Heart Association [NYHA] III or IV). Median RDW and NT-proBNP at admission were 13.4% (interquartile range [IQR]: 12.7%-14.5%), and 1723.00 pg/ml (IQR: 754.00-4006.25 pg/ml), respectively. During 2.9-year median follow-up, all-cause death occurred in 1075 (33.27%) patients. Kaplan-Meier survival curve and Cox proportional-hazard models, showed patients in the top quarter RDW had a 32.0% increased mortality compared to the bottom quarter (hazard ratio: 4.39, 95% confidence interval: 3.59-5.38; p <.001). The top quarter RDW retained independent prognostic value across HF with reduced ejection fraction [HFrEF], HF with mid-range ejection fraction [HFmrEF], and HF with preserved ejection fraction [HFpEF] subgroups. Patients were subsequently divided into four groups by median RDW and NT-proBNP. Comparison of Kaplan-Meier survival curves for various groups showed good risk stratification (p < .001).

CONCLUSIONS

RDW is an independent predictor of mortality among patients with HF in the short-, medium-, and long-term. Combination of RDW and NT-proBNP improves the prognostic value. This is true across all clinical subtypes of heart failure (HFrEF, HFmrEF, HFpEF), and among most subgroups of patients with various comorbidities (infection, diabetes, hypertension).

Machine Learning Patient-Specific Prediction of Heart Failure Hospitalization Using Cardiac MRI-Based Phenotype and Electronic Health Information

Background

Heart failure (HF) hospitalization is a dominant contributor of morbidity and healthcare expenditures in patients with systolic HF. Cardiovascular magnetic resonance (CMR) imaging is increasingly employed for the evaluation of HF given capacity to provide highly reproducible phenotypic markers of disease. The combined value of CMR phenotypic markers and patient health information to deliver predictions of future HF events has not been explored. We sought to develop and validate a novel risk model for the patient-specific prediction of time to HF hospitalization using routinely reported CMR variables, patient-reported health status, and electronic health information.

Methods

Standardized data capture was performed for 1,775 consecutive patients with chronic systolic HF referred for CMR imaging. Patient demographics, symptoms, Health-related Quality of Life, pharmacy, and routinely reported CMR features were provided to both machine learning (ML) and competing risk Fine-Gray-based models (FGM) for the prediction of time to HF hospitalization.

Results

The mean age was 59 years with a mean LVEF of 36 ± 11%. The population was evenly distributed between ischemic (52%) and idiopathic non-ischemic cardiomyopathy (48%). Over a median follow-up of 2.79 years (IQR: 1.59–4.04) 333 patients (19%) experienced HF related hospitalization. Both ML and competing risk FGM based models achieved robust performance for the prediction of time to HF hospitalization. Respective 90-day, 1 and 2-year AUC values were 0.87, 0.83, and 0.80 for the ML model, and 0.89, 0.84, and 0.80 for the competing risk FGM-based model in a holdout validation cohort. Patients classified as high-risk by the ML model experienced a 34-fold higher occurrence of HF hospitalization at 90 days vs. the low-risk group.

Conclusion

In this study we demonstrated capacity for routinely reported CMR phenotypic markers and patient health information to be combined for the delivery of patient-specific predictions of time to HF hospitalization. This work supports an evolving migration toward multi-domain data collection for the delivery of personalized risk prediction at time of diagnostic imaging.

Prognostic value of functional capacity after transitional rehabilitation in older patients hospitalized for heart failure

BACKGROUND

Poor functional status is highly prevalent among older patients hospitalized for HF and marks a downward inflection point in functional and prognostic trajectories. We assessed the prognostic value of 6-min walk test after transitional cardiac rehabilitation in older patients hospitalized for heart failure (HF).

METHODS

We studied 759 patients aged ≥60 years who had been transferred to six inpatient rehabilitation facilities (IRF) from acute care hospitals after a hospitalization for acute HF. The primary outcome was 3-year all-cause mortality. We used multivariable Cox analysis to determine the association between 6-min walk distance (6MWD) at discharge from the IRFs and the primary outcome, adjusting for established predictors of death. The optimal cutoff for 6MWD was considered as the one that maximized the chi-square statistic.

RESULTS

Mean age was 75 ± 8 years. 6MWD significantly increased from admission to discharge (145 to 210 m; p < 0.001). The optimal cutoff for 6MWD was 198 m. After full adjustment, the hazard ratio for each 50 m-increase in discharge 6MWD was 0.90 (0.87-0.94; p < 0.001) and that for discharge 6MWD dichotomized at the optimal cutoff 0.48 (0.38-0.60; p < 0.001). The incidence rate of death/100 person-years for the patients who walked >198 m was 13.0 (10.0-15.5) compared with 30.8 (26.9-35.4) for those who walked <198 m. A statistically significant interaction of discharge 6MWD with left ventricular ejection fraction (EF) on the risk of death was observed (p value for interaction 0.047).

CONCLUSIONS

A rehabilitation intervention provided in the critical hospital-to-home transition period to older patients hospitalized for HF resulted in improved functional capacity. Increasing levels of functional capacity following rehabilitation were closely associated with decreasing risk of death; this association was significantly stronger for the subgroup with preserved EF.

Clinical Prediction of Heart Failure in Hemodialysis Patients: Based on the Extreme Gradient Boosting Method

Background: Heart failure (HF) is the main cause of mortality in hemodialysis (HD) patients. However, it is still a challenge for the prediction of HF in HD patients. Therefore, we aimed to establish and validate a prediction model to predict HF events in HD patients.

Methods: A total of 355 maintenance HD patients from two hospitals were included in this retrospective study. A total of 21 variables, including traditional demographic characteristics, medical history, and blood biochemical indicators, were used. Two classification models were established based on the extreme gradient boosting (XGBoost) algorithm and traditional linear logistic regression. The performance of the two models was evaluated based on calibration curves and area under the receiver operating characteristic curves (AUCs). Feature importance and SHapley Additive exPlanation (SHAP) were used to recognize risk factors from the variables. The Kaplan–Meier curve of each risk factor was constructed and compared with the log-rank test.

Results: Compared with the traditional linear logistic regression, the XGBoost model had better performance in accuracy (78.5 vs. 74.8%), sensitivity (79.6 vs. 75.6%), specificity (78.1 vs. 74.4%), and AUC (0.814 vs. 0.722). The feature importance and SHAP value of XGBoost indicated that age, hypertension, platelet count (PLT), C-reactive protein (CRP), and white blood cell count (WBC) were risk factors of HF. These results were further confirmed by Kaplan–Meier curves.

Conclusions: The HF prediction model based on XGBoost had a satisfactory performance in predicting HF events, which could prove to be a useful tool for the early prediction of HF in HD.

Development and Validation of a Risk Score in Chinese Patients With Chronic Heart Failure

Background

Acute exacerbation of chronic heart failure contributes to substantial increases in major adverse cardiovascular events (MACE). The study developed a risk score to evaluate the severity of heart failure which was related to the risk of MACE.

Methods

This single-center retrospective observational study included 5,777 patients with heart failure. A credible random split-sample method was used to divide data into training and validation dataset (split ratio = 0.7:0.3). Least absolute shrinkage and selection operator (Lasso) logistic regression was applied to select predictors and develop the risk score to predict the severity category of heart failure. Receiver operating characteristic (ROC) curves, and calibration curves were used to assess the model’s discrimination and accuracy.

Results

Body-mass index (BMI), ejection fraction (EF), serum creatinine, hemoglobin, C-reactive protein (CRP), and neutrophil lymphocyte ratio (NLR) were identified as predictors and assembled into the risk score (P &lt; 0.05), which showed good discrimination with AUC in the training dataset (0.770, 95% CI:0.746–0.794) and validation dataset (0.756, 95% CI:0.717–0.795) and was well calibrated in both datasets (all P &gt; 0.05). As the severity of heart failure worsened according to risk score, the incidence of MACE, length of hospital stay, and treatment cost increased (P &lt; 0.001).

Conclusion

A risk score incorporating BMI, EF, serum creatinine, hemoglobin, CRP, and NLR, was developed and validated. It effectively evaluated individuals’ severity classification of heart failure, closely related to MACE.

Serum Chloride Is Inversely Associated With 3 Months Outcomes in Chinese Patients With Heart Failure, a Retrospective Cohort Study

Background

Serum chloride was recently found to be associated with prognosis of heart failure in western countries. However, the evidence was scarce in Asia. We aimed to investigated the relationship between serum chloride and clinical outcomes in a Chinese cohort with hospitalized heart failure.

Methods

We retrospectively analyzed the data from PhysioNet, involving 1996 patients who were admitted with heart failure between December 2016 and June 2019. Outcome was a composite endpoint of all-cause death or rehospitalization at 3 months.

Results

The incidence of the composite endpoint was 26.8% (535/1,996); it was 32.2% (213/662), 25.0% (165/661), and 23.3% (157/673) by chloride tertiles (from the lowest to the highest), respectively. The serum chloride at admission was independently and inversely associated with the composite endpoint risk (hazard ratio: 0.967; 95% confidence interval: 0.939 to 0.996; p = 0.026) in contrast to sodium, which was no longer significant (p > 0.05) after multivariable adjustment. Pearson correlation between serum chloride and sodium was 0.747 (p < 0.001). However, an increased AUC was not observed by adding sodium to model composed of age, sex, NYHA class, diabetes, log BNP and chloride (0.620 vs. 0.612, p = 0.132). Subgroup analysis showed the presence or absence of hyponatremia did not affect the association between chloride and composite endpoint risk.

Conclusions

Low serum chloride at admission was associated with poor outcomes in Chinese hospitalized patients with heart failure. These findings warrant future studies for tackling the potential pathophysiological mechanisms and correction methods of hypochloremia in heart failure.

Ventricular longitudinal function by cardiovascular magnetic resonance predicts cardiovascular morbidity in HFrEF patients

Aims

Ventricular longitudinal function measured as basal‐apical atrioventricular plane displacement (AVPD) or global longitudinal strain (GLS) is a potent predictor of mortality and could potentially be a predictor of heart failure‐associated morbidity. We hypothesized that low AVPD and GLS are associated with the combined endpoint of cardiovascular mortality and heart failure‐associated morbidity.

Methods and results

Two hundred eighty‐seven patients (age 62 ± 12 years, 78% male) with heart failure with reduced (≤40%) ejection fraction (HFrEF) referred to a cardiovascular magnetic resonance exam were included. Ventricular longitudinal function, ventricular volume, and myocardial fibrosis or infarction were analysed from cine and late gadolinium enhancement images. National registries provided data on causes of cardiovascular hospitalizations and cardiovascular mortality for the combined endpoint. Time‐to‐event analysis capable of including reoccurring events was employed with a 5‐year follow‐up. HFrEF patients had EF 26.5 ± 8.0%, AVPD 7.8 ± 2.4 mm, and GLS −7.5 ± 3.0%. In contrast, ventricular longitudinal function was approximately twice as large in an age‐matched control group (AVPD 15.3 ± 1.6 mm; GLS −20.6 ± 2.0%; P < 0.001 for both). There were 578 events in total, and the majority were HF hospitalizations (n = 418). Other major events were revascularizations (n = 64), cardiovascular deaths (n = 40), and myocardial infarctions (n = 21). One hundred fifty‐five (54%) patients experienced at least one event (mean 2.0, range 0–64). Of these patients, 119 (71%) had three events or fewer, and the first three events comprised 51% of all events (295 events). Patients in the bottom AVPD or GLS tertile (<6.8 mm or >−6.1%) overall experienced more than 3 times as many events as the top tertile (>8.8 mm or <−8.4%; P < 0.001). Patients in this tertile also faced more cardiovascular deaths (P < 0.05), HF hospitalizations (P = 0.001), myocardial infarctions (only GLS: P = 0.032), and accumulated longer in‐hospital length‐of‐stay overall (AVPD 20.9 vs. 9.1 days; GLS 22.4 vs. 6.5 days; P = 0.001 for both), and from HF hospitalizations (AVPD 19.3 vs. 8.3 days; GLS 19.3 vs. 5.4 days; P = 0.001 for both). In multivariate analysis adjusted for significant covariates, AVPD and GLS remained independent predictors of events (hazard ratio 1.12 per‐mm‐decrease and 1.13 per‐%‐increase) alongside hyponatremia (<135 mmol/L), aetiology of HF, and LV end‐diastolic volume index.

Conclusions

Low ventricular longitudinal function is associated with an increase in number of events as well as longer in‐hospital stay from cardiovascular causes. In addition, AVPD and GLS have independent prognostic value for cardiovascular mortality and morbidity in HFrEF patients.