Performance of AHEAD Score in an Asian Cohort of Acute Heart Failure With Either Preserved or Reduced Left Ventricular Systolic Function

Prognostic impact of MitraScore in elderly Asian patients with heart failure: sub-analysis of FRAGILE-HF

AIMS

MitraScore is a novel, simple, and manually calculatable risk score developed as a prognostic model for patients undergoing transcatheter edge-to-edge repair (TEER) for mitral regurgitation. As its components are considered prognostic in heart failure (HF), we aimed to investigate the usefulness of the MitraScore in HF patients.

METHODS AND RESULTS

We calculated MitraScore for 1100 elderly patients (>65 years old) hospitalized for HF in the prospective multicentre FRAGILE-HF study and compared its prognostic ability with other simple risk scores. The primary endpoint was all-cause deaths, and the secondary endpoints were the composite of all-cause deaths and HF rehospitalization and cardiovascular deaths. Overall, the mean age of 1100 patients was 80 ± 8 years, and 58% were men. The mean MitraScore was 3.2 ± 1.4, with a median of 3 (interquartile range: 2-4). A total of 326 (29.6%), 571 (51.9%), and 203 (18.5%) patients were classified into low-, moderate-, and high-risk groups based on the MitraScore, respectively. During a follow-up of 2 years, 226 all-cause deaths, 478 composite endpoints, and 183 cardiovascular deaths were observed. MitraScore successfully stratified patients for all endpoints in the Kaplan-Meier analysis (P < 0.001 for all). In multivariate analyses, MitraScore was significantly associated with all endpoints after covariate adjustments [adjusted hazard ratio (HR) (95% confidence interval): 1.22 (1.10-1.36), P < 0.001 for all-cause deaths; adjusted HR 1.17 (1.09-1.26), P < 0.001 for combined endpoints; and adjusted HR 1.24 (1.10-1.39), P < 0.001 for cardiovascular deaths]. The Hosmer-Lemeshow plot showed good calibration for all endpoints. The net reclassification improvement (NRI) analyses revealed that the MitraScore performed significantly better than other manually calculatable risk scores of HF: the GWTG-HF risk score, the BIOSTAT compact model, the AHEAD score, the AHEAD-U score, and the HANBAH score for all-cause and cardiovascular deaths, with respective continuous NRIs of 0.20, 0.22, 0.39, 0.39, and 0.29 for all-cause mortality (all P-values < 0.01) and 0.20, 0.22, 0.42, 0.40, and 0.29 for cardiovascular mortality (all P-values < 0.02).

CONCLUSIONS

MitraScore developed for patients undergoing TEER also showed strong discriminative power in HF patients. MitraScore was superior to other manually calculable simple risk scores and might be a good choice for risk assessment in clinical practice for patients receiving TEER and those with HF.

The modified Rajan's heart failure risk score predicts all-cause mortality in patients hospitalized for heart failure with reduced ejection fraction: a retrospective cohort study

Background

The dimensionless Rajan's heart failure (R-hf) risk score was proposed to predict all-cause mortality in patients hospitalized with chronic heart failure (HF) and reduced ejection fraction (EF) (HFrEF).

Purpose

To examine the association between the modified R-hf risk score and all-cause mortality in patients with HFrEF.

Methods

Retrospective cohort study included adults hospitalized with HFrEF, as defined by clinical symptoms of HF with biplane EF less than 40% on transthoracic echocardiography, at a tertiary centre in Dalian, China, between 1 November 2015, and 31 October 2019. All patients were followed up until 31 October 2020. A modified R-hf risk score was calculated by substituting brain natriuretic peptide (BNP) for N-terminal prohormone of BNP (NT-proBNP) using EF× estimated glomerular filtration rate (eGFR)× haemoglobin (Hb))/BNP. The patients were stratified into tertiles according to the R-hf risk score. The measured outcome was all-cause mortality. The score performance was assessed using C-statistics.

Results

A total of 840 patients were analyzed (70.2% males; mean age, 64±14 years; median (interquartile range) follow-up 37.0 (27.8) months). A lower modified R-hf risk score predicted a higher risk of all-cause mortality, independent of sex and age [1st tertile vs. 3rd tertile: adjusted hazard ratio (aHR), 3.46; 95% CI: 2.11-5.67; P<0.001]. Multivariate Cox regression analysis indicated that a lower modified R-hf risk score was associated with increased cumulative all-cause mortality [univariate: (1st tertile vs. 3rd tertile: aHR, 3.45; 95% CI: 2.11-5.65; P<0.001) and multivariate: (1st tertile vs. 3rd tertile: aHR 2.21, 95% CI: 1.29-3.79; P=0.004)]. The performance of the model, as reported by C-statistic was 0.67 (95% CI: 0.62-0.72).

Conclusion

The modified R-hf risk score predicted all-cause mortality in patients hospitalized with HFrEF. Further validation of the modified R-hf risk score in other cohorts of patients with HFrEF is needed before clinical application.

Usefulness of HANBAH Score in Japanese Patients With Acute Heart Failure

The HANBAH score is a novel simple risk score consisting of hemoglobin level, age, sodium (N) level, blood urea nitrogen level, atrial fibrillation, and high-density lipoprotein. We aimed to validate this score in an external population. This retrospective study included 744 patients hospitalized for acute heart failure between 2015 and 2019. Each of the following criteria was scored as 1 point: hemoglobin level (<13.0 g/L for men and <12.0 g/L for women), atrial fibrillation, age (>70 years), serum blood urea nitrogen level (>26 mg/100 ml for men and >28 mg/100 ml for women), serum high-density lipoprotein level (<25 mg/100 ml), and serum sodium level (<135 mg/100 ml). HANBAH scores were available for 736 patients (age, 75 ± 13 years; 60% male; reduced [<40%] and preserved ejection fraction [≥50%]: 35% and 49%, respectively). All-cause death during follow-up, a composite of death and heart failure rehospitalization, and in-hospital death were observed in 173, 274, and 51 patients, respectively. The HANBAH score was significantly associated with these end points after adjustment for covariates (adjusted hazard ratio 1.38 [95% confidence interval 1.16 to 1.64], p <0.001; 1.27 [1.11 to 1.45], p <0.001; and 1.66 [1.18 to 2.33], p <0.001, respectively). Receiver operating characteristic and net reclassification improvement analyses showed that the HANBAH score performed significantly better than AHEAD (atrial fibrillation, hemoglobin [anemia], elderly, abnormal renal parameters, diabetes mellitus) and AHEAD-U (AHEAD with uric acid) scores and similar to the multi-domain ACUTE HF score for all end points. In conclusion, the HANBAH score showed powerful risk stratification in this external Japanese cohort. Despite its simplicity, it performed better than other simple risk scores and similar to a multidomain risk score.

Larissa Heart Failure Risk Score and Mode of Death in Acute Heart Failure: Insights from REALITY-AHF

Patients with heart failure (HF) patients may die either suddenly (sudden cardiac death/SCD) or progressively from pump failure. The heightened risk of SCD in patients with HF may expedite important decisions about medications or devices. We used the Larissa Heart Failure Risk Score (LHFRS), a validated risk model for all-cause mortality and HF rehospitalization, to investigate the mode of death in 1363 patients enrolled in the Registry Focused on Very Early Presentation and Treatment in Emergency Department of Acute Heart Failure (REALITY-AHF). Cumulative incidence curves were generated using a Fine-Gray competing risk regression, with deaths that were not due to the cause of death of interest as a competing risk. Likewise, the Fine-Gray competing risk regression analysis was used to evaluate the association between each variable and the incidence of each cause of death. The AHEAD score, a well-validated HF risk score ranging from 0 to 5 (atrial fibrillation, anemia, age, renal dysfunction, and diabetes mellitus), was used for the risk adjustment. Patients with LHFRS 2-4 exhibited a significantly higher risk of SCD (HR hazard ratio adjusted for AHEAD score 3.15, 95% confidence interval (CI) (1.30-7.65), p = 0.011) and HF death (adjusted HR for AHEAD score 1.48, 95% CI (1.04-2.09), p = 0.03), compared to those with LHFRS 0,1. Regarding cardiovascular death, patients with higher LHFRS had significantly increased risk compared to those with lower LHFRS (HR 1.44 adjusted for AHEAD score, 95% CI (1.09-1.91), p = 0.01). Lastly, patients with higher LHFRS exhibited a similar risk of non-cardiovascular death compared to those with lower LHFRS (HR 1.44 adjusted for AHEAD score, 95% CI (0.95-2.19), p = 0.087). In conclusion, LHFRS was associated independently with the mode of death in a prospective cohort of hospitalized HF patients.

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

AIMS

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

METHODS AND RESULTS

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

CONCLUSIONS

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

Relationship between instrumental activities of daily living decline during hospitalization and one-year mortality in elderly patients with heart failure: A multi-center prospective cohort study

BACKGROUND

It remains unclear whether instrumental activities of daily living (IADL) decline during hospitalization is related to mortality rates. This study examined the relationship between IADL decline during hospitalization and the one-year mortality rate in elderly heart failure (HF) patients.

METHODS

Five hundred seventy-six consecutive patients who were hospitalized for acute decompensated HF and underwent rehabilitation were divided into groups based on changes in IADL during hospitalization: IADL maintained and IADL decline. IADL was assessed by the National Center for Geriatrics and Gerontology-Activities of Daily Living Scale (NCGG-ADL). IADL decline was defined as Δ NCGG-ADL ≤ -1 point. The primary outcome was one-year all-cause mortality rate after discharge. Outcomes were examined using the Kaplan-Meier method with the log-rank test and Cox proportional hazards models using the existing prognostic risk factors for HF.

RESULTS

Of 576 patients, 20% (n = 113) had IADL decline during hospitalization, and 9.2% (n = 35) and 6.0% (n = 18) died of all-cause and cardiovascular disease within one year after discharge, respectively. The IADL-decline group had significantly higher one-year all-cause mortality rates after adjusting for risk factors (hazard ratio: 1.923, 95% confidence interval 1.085-3.409; P = 0.023). Among the IADL subcategories, outdoor activity items such as "go out by oneself," "take a bus or train," and "shop for necessities" were more likely to change from independent to dependent during hospitalization.

CONCLUSION

IADL decline during hospitalization was associated with an increased all-cause mortality rate at one-year after discharge in elderly HF patients.

Amino acid profiling to predict prognosis in patients with heart failure: an expert review

Heart failure is a complex disease with a poor prognosis. A number of widely used prognostic tools have limitations, so efforts to identify novel predictive markers and measures are important. As a metabolomics tool, amino acid profiling has shown promise in predicting heart failure prognosis; however, the evidence has not yet been sufficiently evaluated. We describe the utilization of amino acids in the healthy heart and in heart failure before reviewing the literature on amino acid profiling for prognostic prediction. We expertly interpret the findings and provide suggestions for future research to advance the understanding of the prognostic potential of amino acid profiling in heart failure. Our analysis revealed correlations between amino acid biomarkers and traditional prognostic factors, the additional prognostic value of amino acid biomarkers over traditional prognostic factors, and the successful use of amino acid biomarkers to distinguish heart failure aetiology. Although certain amino acid biomarkers have demonstrated additional prognostic value over traditional measures, such as New York Heart Association functional class, these measures are deeply rooted in clinical practice; thus, amino acid biomarkers may be best placed as additional prognostic tools to improve current risk stratification rather than as surrogate tools. Once the metabolic profiles of different heart failure aetiologies have been clearly delineated, the amino acid biomarkers with the most value in prognostic prediction should be determined. Amino acid profiling could be useful to evaluate the pathophysiology and metabolic status of different heart failure cohorts, distinguish heart failure aetiologies, and improve risk stratification and prognostic prediction.

Change in Nutritional Status during Hospitalization and Prognosis in Patients with Heart Failure with Preserved Ejection Fraction

The impact of changes in nutritional status during hospitalization on prognosis in patients with heart failure with preserved ejection fraction (HFpEF) remains unknown. We examined the association between changes in the Geriatric Nutritional Risk Index (GNRI) and prognosis during hospitalization in patients with HFpEF stratified by nutritional status on admission. Nutritional status did and did not worsen in 348 and 349 of 697 patients with high GNRI on admission, and in 142 and 143 of 285 patients with low GNRI on admission, respectively. Kaplan–Meier analysis revealed no difference in risk of the composite endpoint, all-cause death, or heart failure admission between patients with high GNRI on admission whose nutritional status did and did not worsen. In contrast, patients with low GNRI on admission whose nutritional status did not worsen had a significantly lower risk of the composite endpoint and all-cause death than those who did. Multivariable analysis revealed that worsening nutritional status was independently associated with a higher risk of the composite endpoint and all-cause mortality in patients with low GNRI on admission. Changes in nutritional status during hospitalization were thus associated with prognosis in patients with malnutrition on admission, but not in patients without malnutrition among those with HFpEF.

Validation of R-hf risk score for risk stratification in ischemic heart failure patients: A prospective cohort study

Background

The aim of this study was to validate R-heart failure (R-hf) risk score in ischemic heart failure patients.

Methods

We prospectively recruited a cohort of 179 ischemic and 107 non-ischemic heart failure patients. This study mainly focused on ischemic heart failure patients. Non-ischemic heart failure patients were included for the purpose of validation of the risk score in various heart failure groups. Patients were stratified in high risk, moderate risk and low risk groups according to R-hf risk score.

Results

A total of 179 participants with ischemic heart failure were included. Based on R-hf risk score, 82 had high risk, 50 had moderate risk and 47 had low risk heart failure scores. More than half of the patients having R-hf score of <5 had renal failure (n = 91, 50.8%) and anemia (n = 99, 55.3%). Notably, HFrEF was more prevalent in patients with high risk score (74, 90.2%). Patients with high risk score had significantly higher creatinine (2.63 ± 1.96, p < 0.001), Troponin-T HS (59.9 ± 38.0, p < 0.001) and PRO BNP (17842 ± 6684, p < 0.001) when compared to patients with low and moderate risk score. Patients with low risk score had significantly higher Hb (13.2 ± 1.85, p < 0.001), Albumin (3.69 ± 0.42, p < 0.001) and GFR (90.0 ± 8.04, p < 0.001). A R-hf score of <5 was a significant predictor of mortality in ischemic (OR = 50.34; 95% CI [16.94–194.00, p < 0.001) and non-ischemic (OR = 46.34; 95% CI [12.97–225.39], p < 0.001) heart failure patients.

Conclusions

Lower R-hf risk score is a significant predictor of mortality in ischemic and non-ischemic heart failure patients. Risk score can be accessed at https://www.hfriskcalc.in.

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R-hf risk score is a robust tool (a derivative of e-GFR, EF, Hb, and NT proBNP) to predict heart failure mortality.

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Lower R-hf risk score is a significant predictor of mortality.

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Rajan's-hf risk score calculator will be available at https://www.hfriskcalc.in/.

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

Purpose

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

Patients and Methods

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

Results

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

Conclusion

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

Associations between kidney function and outcomes of comprehensive cardiac rehabilitation in patients with heart failure

AIMS

To investigate the impact of baseline kidney function on outcomes following comprehensive cardiac rehabilitation (CR) in patients with heart failure (HF).

METHODS

We reviewed a total of 3,727 patients who were admitted for HF treatment. Estimated glomerular filtration rate (eGFR), quadriceps strength (QS), and 6-min walk distance (6MWD) were measured at hospital discharge as a baseline and 5 months thereafter in participants of outpatient comprehensive CR. The association between outpatient CR participation and all-cause events was evaluated using propensity score-matched analysis in subgroups across eGFR stages. The changes in QS and 6MWD following 5-month CR were compared between eGFR stages.

RESULTS

Out of the studied patients, 1585 (42.5%) participated in outpatient CR. After propensity matching for clinical confounders, 2680 patients were included for analysis (pairs of n = 1340 outpatient CR participants and nonparticipants). The participation in outpatient CR was significantly associated with low clinical events in subgroups of eGFR ≥ 60 [hazard ratio (HR): 0.65, 95% confidence interval (CI): 0.51-0.84] and eGFR 45-60 (HR: 0.71, 95% CI: 0.55-0.92), but not in eGFR 30-45 (HR: 0.83, 95% CI: 0.64-1.08) and eGFR < 30 (HR: 0.88, 95% CI: 0.69-1.12). QS and 6MWD were significantly higher after 5-month CR than those at baseline (P < 0.001, respectively), but lower baseline eGFR correlated with lower changes in QS and 6MWD (trend P < 0.001, respectively).

CONCLUSIONS

Although low baseline kidney function attenuates the outcomes of CR, outpatient CR seems to be associated with a better prognosis and positive change in physical function in HF patients with low kidney function.

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

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

The Comprehensive Machine Learning Analytics for Heart Failure

Background: Early detection of heart failure is the basis for better medical treatment and prognosis. Over the last decades, both prevalence and incidence rates of heart failure have increased worldwide, resulting in a significant global public health issue. However, an early diagnosis is not an easy task because symptoms of heart failure are usually non-specific. Therefore, this study aims to develop a risk prediction model for incident heart failure through a machine learning-based predictive model. Although African Americans have a higher risk of incident heart failure among all populations, few studies have developed a heart failure risk prediction model for African Americans. Methods: This research implemented the Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression, support vector machine, random forest, and Extreme Gradient Boosting (XGBoost) to establish the Jackson Heart Study's predictive model. In the analysis of real data, missing data are problematic when building a predictive model. Here, we evaluate predictors' inclusion with various missing rates and different missing imputation strategies to discover the optimal analytics. Results: According to hundreds of models that we examined, the best predictive model was the XGBoost that included variables with a missing rate of less than 30 percent, and we imputed missing values by non-parametric random forest imputation. The optimal XGBoost machine demonstrated an Area Under Curve (AUC) of 0.8409 to predict heart failure for the Jackson Heart Study. Conclusion: This research identifies variations of diabetes medication as the most crucial risk factor for heart failure compared to the complete cases approach that failed to discover this phenomenon.

A statistical predictive model consistent within a 5-year follow-up period for patients with acute heart failure

BACKGROUND

Acute heart failure (AHF) is a major and rapidly growing health problem responsible for millions of hospitalizations annually. Due to a high proportion of in-hospital mortality and postdischarge rehospitalization and mortality, a prompt strategy for risk stratification and subsequently tailored therapy is desirable to help improve clinical outcomes. The AHEAD (A: atrial fibrillation; H: hemoglobin; E: elderly; A: abnormal renal parameters; D: diabetes mellitus) and AHEAD-U (A: atrial fibrillation; H: hemoglobin; E: elderly; A: abnormal renal parameters; D: diabetes mellitus, U: uric acid) are popular prognostic scoring systems. However, only a specific follow-up period is considered in these systems, and whether their predictive capability is still accurate in a significantly shorter or longer follow-up period is not known.

METHODS

In this research, we adapted extensive statistical approaches based on the Cox model to explore consistent risk factors in various follow-up durations. Results showed that six factors, namely, hemoglobin level, age, sodium level, blood urea nitrogen level, atrial fibrillation, and high-density lipoprotein level could be used to establish a new prognostic model, which was referred to as HANBAH. For a simple clinical application, the HANBAH scoring system, with scores from 0 to 6, was developed using several statistical models.

RESULTS

Based on an evaluation using the conventional statistical approaches, such as the Akaike information criterion, concordance statistic, and Cox area under the curve, the HANBAH scoring system consistently outperformed other strategies in predicting short- and long-term mortality. Notably, an independent replication study also revealed similar results. In addition, a modern machine learning technique using the support vector machine confirmed its superior performance.

CONCLUSION

The use of the HANBAH scoring system, which is a clinically friendly tool, was proposed, and its efficacy in predicting the mortality rates of patients with AHF regardless of the follow-up duration was independently validated.

Risk stratification in patients hospitalized for acute heart failure in Asian population

BACKGROUND

The AHEAD (A: atrial fibrillation; H: hemoglobin; E: elderly; A: abnormal renal parameters; D: diabetes mellitus) score may be suboptimal in predicting long-term mortality in Asian patients with acute heart failure (AHF). We aimed to propose and validate a risk score incorporating easily available echocardiographic parameters to improve risk stratification in Asian patients with AHF.

METHODS

A total of 3537 patients hospitalized for AHF were enrolled and divided into generation and validation cohorts. Independent predictors of all-cause mortality were identified by Cox regression analysis and scored by hazard ratios to constitute the model. Model performance was validated and evaluated by receiver operating characteristic (ROC) curves and net reclassification improvement (NRI).

RESULTS

In the generation cohort of 1775 patients (74.3±13.0 years, 69.9% men), there were 870 deaths (49.0%) during a mean follow-up of 24.7±13.8 months. Age, anemia, estimated glomerular filtration rate <50 ml/min/1.73 m, hyperuricemia, left ventricular ejection fraction <50% and right ventricular systolic pressure (RVSP) >40 mmHg were independently related to mortality, which constituted "UR-HEARt" (U: uric acid, R: renal function, H: hemoglobin, E: ejection fraction of left ventricle, A: age, Rt: RVSP) score. Model performance was evaluated in the validation cohort (n = 1762), which outperformed AHEAD score by comparison of ROC curves in predicting all-cause mortality (area under curve [AUC] of UR-HEARt vs. AHEAD: 0.66 [95% CI 0.62-0.70] vs. 0.58 [95% CI 0.54-0.62]; p < 0.001), with NRI by 10.9% for all-cause mortality (p < 0.001) and 18.4% for cardiovascular death (p < 0.001).

CONCLUSION

UR-HEARt score, an easily accessible racial-specific risk score with integration of echocardiographic indices, improved risk stratification in Asian patients hospitalized for AHF.

Changes in Respiratory Muscle Strength Following Cardiac Rehabilitation for Prognosis in Patients with Heart Failure

Respiratory muscle weakness, frequently observed in patients with heart failure (HF), is reported as a predictor for poor prognosis. Although increased respiratory muscle strength ameliorates exercise tolerance and quality of life in HF patients, the relationship between changes in respiratory muscle strength and patient prognosis remains unclear. A total of 456 patients with HF who continued a 5-month cardiac rehabilitation (CR) were studied. We measured maximal inspiratory pressure (PI_max) at hospital discharge as the baseline and five months thereafter to assess the respiratory muscle strength. Changes in PI_max during the 5-month observation period (⊿PI_max) were examined. We investigated the composite multiple incidence of all-cause death or unplanned readmission after 5-month CR. The relationship between ⊿PI_max and the incidence of clinical events was analyzed. Over a median follow-up of 1.8 years, 221 deaths or readmissions occurred, and their rate of incidence was 4.3/100 person-years. The higher ⊿PI_max was significantly associated with lower incidence of clinical event. In multivariate Poisson regression model after adjustment for clinical confounding factors, ⊿PI_max remained a significant and independent predictor for all-cause death/readmission (adjusted incident rate ratio for ⊿PI_max increase of 10 cmH₂O: 0.77, 95% confidence interval: 0.70–0.86). In conclusion, the changes in respiratory muscle strength independently predict the incidence of clinical events in patients with HF.

Prognostic Significance of Serum Cholinesterase Level in Patients With Acute Decompensated Heart Failure With Preserved Ejection Fraction: Insights From the PURSUIT-HFpEF Registry

Background

Malnutrition is one of the most important comorbidities in patients with heart failure with preserved ejection fraction. We recently reported the prognostic significance of serum cholinesterase level and superior predictive power of cholinesterase level to other objective nutritional indices such as the controlling nutritional status score, prognostic nutritional index, and geriatric nutritional risk index in patients with acute decompensated heart failure. The aim of this study was to clarify the prognostic role of cholinesterase in patients with heart failure with preserved ejection fraction/acute decompensated heart failure and investigate incremental cholinesterase value.

Methods and Results

We prospectively studied 274 consecutive patients from the PURSUIT‐HFpEF (Prospective Multicenter Observational Study of Patients with Heart Failure With Preserved Ejection Fraction) study. During a follow‐up period of 1.2±0.6 years, 56 patients reached the composite end points (cardiovascular death and readmission for worsening heart failure). In the multivariable Cox analysis, cholinesterase level was significantly associated with the composite end points after adjustment for major confounders. A Kaplan–Meier analysis revealed that patients with low cholinesterase levels (stratified by tertile) had significantly greater risk of reaching the composite end points than those with middle or high cholinesterase levels (P=0.0025). Cholinesterase level showed the best C‐statistics (0.703) for prediction of the composite end points among the objective nutritional indices. C‐statistics of the Meta‐Analysis Global Group in Chronic Heart Failure (MAGGIC) risk score for prediction of the composite end points were improved when cholinesterase level was added (C‐statistics, from 0.601 to 0.705; P=0.0408).

Conclusions

Cholinesterase was a useful prognostic marker for prediction of adverse outcome in patients with heart failure with preserved ejection fraction/acute decompensated heart failure.

Prevalence and prognosis of respiratory muscle weakness in heart failure patients with preserved ejection fraction

BACKGROUND

Although respiratory muscle weakness (RMW) is known to predict prognosis in patients with heart failure with reduced ejection fraction (HFrEF), RMW prevalence and its prognosis in those with preserved ejection fraction (HFpEF) remain unknown. We aimed to investigate whether the RMW predicted mortality in HFpEF patients.

METHODS

We conducted a single-centre observational study with consecutive 1023 heart failure patients (445 in HFrEF and 578 in HFpEF). Maximal inspiratory pressure (PI_max) was measured to assess respiratory muscle strength at hospital discharge, and RMW was defined as PI_max <70% of predicted value. Endpoint was all-cause mortality after hospital discharge, and we examined the influence of RMW on the endpoint.

RESULTS

Over a median follow-up of 1.8 years, 134 patients (13.1%) died; of these 53 (11.9%) were in HFrEF and 81 (14.0%) in HFpEF. RMW was evident in 190 (42.7%) HFrEF and 226 (39.1%) HFpEF patients and was independently associated with all-cause mortality in both HFrEF (adjusted hazard ratio [HR]: 2.13, 95% confidence interval [CI]: 1.17-3.88) and HFpEF (adjusted HR: 2.85, 95% CI: 1.74-4.67) patients. Adding RMW to the multivariate logistic regression model significantly increased area under the receiver-operating characteristic curve (AUC) for all-cause mortality in HFpEF (AUC including RMW: 0.78, not including RMW: 0.74, P = 0.026) but not in HFrEF (AUC including RMW: 0.84, not including RMW: 0.82, P = 0.132).

CONCLUSIONS

RMW was observed in 39% of HFpEF patients, which was independently associated with poor prognosis. The additive effect of RMW on prognosis was detected only in HFpEF but not in HFrEF.

Prognostic significance of serum cholinesterase in patients with acute decompensated heart failure: a prospective comparative study with other nutritional indices

BACKGROUND

Nutritional status is associated with poor outcomes in patients with heart failure. Serum cholinesterase (CHE) concentration, a marker of malnutrition, was reported to be a prognostic factor in patients with chronic heart failure. The geriatric nutritional risk index (GNRI), the controlling nutritional status (CONUT) score, and the prognostic nutritional index (PNI) are established objective nutritional indices.

OBJECTIVE

The aim of this study was to clarify the prognostic significance of CHE concentration and to compare it with other well-established objective nutritional indices in patients with acute decompensated heart failure (ADHF).

METHODS

We prospectively enrolled 371 consecutive patients admitted for ADHF with survival discharge. Laboratory data including CHE and the objective nutritional indices were obtained at discharge. The primary endpoint of this study was all-cause mortality.

RESULTS

During a mean ± SD follow-up period of 2.5 ± 1.4 y, 112 patients died. CHE concentration was significantly associated with all-cause mortality independently of GNRI, CONUT score, or PNI, after adjustment for major confounders including other nutritional indices, such as age, sex, systolic blood pressure, BMI, left ventricular ejection fraction, history of hypertension, diabetes mellitus, dyslipidemia, prior heart failure hospitalization, angiotensin-converting enzyme inhibitor or angiotensin receptor blocker use, β-blocker use, statin use, hemoglobin, sodium, blood urea nitrogen, albumin, C-reactive protein, and brain natriuretic peptide concentrations via multivariable Cox analysis. Kaplan-Meier analysis revealed that the risk of all-cause mortality significantly increased in accordance with CHE stratum [lowest tertile: 53%, adjusted HR: 6.92; 95% CI: 3.87, 12.36, compared with middle tertile: 28%, adjusted HR: 2.72; 95% CI: 1.45, 5.11, compared with highest tertile: 11%, adjusted HR: 1.0 (reference), P < 0.0001]. CHE showed the best area under the curve value (0.745) for the prediction of all-cause mortality compared with the other objective nutritional indices. Net reclassification improvement afforded by adding CHE to the fully adjusted multivariable model was statistically significant for all-cause mortality (0.330; 95% CI: 0.112, 0.549, P = 0.0030).

CONCLUSION

CHE is a simple, strong prognostic marker for the prediction of all-cause mortality in patients with ADHF.

Short-Term Change in Gait Speed and Clinical Outcomes in Older Patients With Acute Heart Failure

BACKGROUND

Evidence for the prognostic value of gait speed is largely based on a single measure at baseline, so we investigated the prognostic significance of change in gait speed in hospitalized older acute heart failure (AHF) patients.Methods and Results:This retrospective study was performed in a cohort of 388 AHF patients ≥60 years old (mean age: 74.8±7.8 years, 228 men). Routine geriatric assessment included gait speed measurement at baseline and at discharge. The primary outcome of this study was all-cause death. Gait speed increased from 0.74±0.25 m/s to 0.98±0.27 m/s after 13.5±11.0 days. Older age, shorter height and lower hemoglobin level at admission, prior HF admission, and higher baseline gait speed were independently associated with lesser improvement in gait speed. A total of 80 patients died and 137 patients were readmitted for HF over a mean follow-up period of 2.1±1.9 years. In multivariate analyses, change in gait speed showed inverse associations with all-cause death (hazard ratio [HR] per 0.1 m/s increase: 0.83; 95% confidence interval [CI]: 0.73 to 0.95; P=0.006) and with risk of readmission for HF (HR: 0.91; 95% CI: 0.83 to 0.99; P=0.036).

CONCLUSIONS

Short-term improvement in gait speed during hospitalization was associated with reduced risks of death and readmission for HF in older patients with AHF.

Prediction of acute coronary syndrome, ischemic stroke, and mortality in patients with heart failure: a comparison of CHA2DS2-VASc and AHEAD scores

PURPOSE

To compare the predictive capacity of the CHA₂DS₂-VASc and AHEAD scores in predicting acute coronary syndrome (ACS), ischemic stroke (IS), and mortality in patients with heart failure (HF).

METHODS

A total of 404,635 patients hospitalized for HF between 2000 and 2011 were recruited from a large national database in Taiwan. The predictive value of both scores was evaluated by analysis of the area under the receiver operating characteristic curve (AUROC), and the difference in their discriminative capacity was assessed using the DeLong test.

RESULTS

The AUROC for the CHA₂DS₂-VASc score was significantly higher than that for the AHEAD score in predicting ACS and IS: 0.53 (95% CI = 0.53-0.54) versus 0.51 (95% CI = 0.51-0.52) for ACS, and 0.57 (95% CI = 0.56-0.57) versus 0.52 (95% CI = 0.51-0.52) for IS, respectively (all DeLong tests p < 0.001). By contrast, for mortality risk, the AUROC was significantly lower for the CHA₂DS₂-VASc score (0.56, 95% CI = 0.55-0.56) than the AHEAD score (0.60, 95% CI = 0.59-0.60; DeLong test p < 0.001).

CONCLUSIONS

The ability of the CHA₂DS₂-VASc score to predict macrovascular complications (ACS and IS) in HF patients was higher than that of AHEAD.

Gender Differences in Prognostic Markers of All-Cause Death in Patients with Acute Heart Failure: a Prospective 18-Month Follow-Up Study

Acute heart failure (AHF) is a life-threatening condition with poor prognosis. Gender differences have been increasingly recognized in diverse cardiovascular diseases. The present study aimed to evaluate gender-specific prognostic markers of all-cause death in AHF patients based on a prospective 18-month follow-up study. Data were collected from 419 patients with AHF hospitalization who were followed up for 18 months using all-cause death as primary endpoint. The mean age of all patients was 60.9 ± 15.7 years old, 277 were males, and 142 were females. Females had higher rate of valvular heart disease (37.3%) and atrial fibrillation (45.8%) but lower rate of cardiomyopathy (30.3%) than males in this cohort. Based on multiple COX stepwise regression and ROC curve analysis, diastolic blood pressure (DBP), serum sodium, serum creatinine, and pulmonary artery systolic pressure (PASP) were identified as independent predictors of all-cause death in male AHF patients, while systolic blood pressure (SBP), serum aspartate transaminase (AST), serum creatinine, and serum D-dimer as independent predictors in females. Kaplan-Meier analysis showed a higher probability of all-cause death over time in male AHF patients with DBP ≤ 77 mmHg, serum sodium ≤ 138.5 mM, serum creatinine ≥ 126.2 μM, or PASP ≥ 52 mmHg, and in female AHF patients with SBP ≤ 129 mmHg, serum AST > 29.3 U/L, serum creatinine ≥ 102.7 μM, or serum D-dimer ≥ 1.76 mg/L. In conclusion, these data provide novel insights into gender differences in prognostic markers of outcomes of AHF patients.

Comparison of CHA2DS2-VASc and AHEAD scores for the prediction of incident dementia in patients hospitalized for heart failure: a nationwide cohort study

This study explores the use of the CHA₂DS₂-VASc and the AHEAD scores to predict incident dementia in patients with heart failure (HF) who need hospitalization. We used a large national database to study 387,595 adult patients hospitalized for HF from Taiwan. This registration cohort was followed to document the cumulative incidence of dementia. The area under the curve of receiver operating characteristics (AUROC) was used to evaluate the discriminative ability of CHA₂DS₂-VASc and AHEAD scores in predicting dementia, whereas the DeLong test was used to examine the difference between the predictive capacity. A higher CHA₂DS₂-VASc and AHEAD scores appear to be more strongly associated with a higher incidence of dementia. The AUROC for CHA₂DS₂-VASc score in predicting dementia (0.61, 95% CI = 0.60-0.61) is significantly higher than the AHEAD score (0.55, 95% CI = 0.54-0.55) (DeLong test p < 0.001). A significantly higher ability, by AUROC, of CHA₂DS₂-VASc score to predict new-onset dementia in patients hospitalized for HF is found.

Clinical Significance of Get With the Guidelines-Heart Failure Risk Score in Patients With Chronic Heart Failure After Hospitalization

Background The Get With the Guidelines-Heart Failure ( GWTG - HF ) risk score was developed using American Heart Association GWTG - HF program data and predicts in-hospital mortality in patients with acute heart failure (HF). We aimed to clarify the prognostic impacts of the GWTG - HF risk score in patients with HF after discharge. Methods and Results We examined the GWTG - HF score in 1452 patients with HF, who were admitted to our hospital and discharged after treatment, by calculating 7 predetermined variables. We divided all subjects into 3 groups according to the GWTG - HF risk score (low, moderate, and high score groups). The plasma B-type natriuretic peptide level significantly increased with increasing GWTG - HF risk score severity (median values of B-type natriuretic peptide: 167.0 in low, 260.7 in moderate, and 418.2 pg/mL in high score groups). We followed up all subjects after discharge, and there were 347 (23.9%) all-cause deaths and 407 (28.0%) cardiac events in follow-up periods. A Kaplan-Meier survival curve demonstrated that event rates of all-cause death and cardiovascular events, including worsening HF and cardiac death, significantly increased with increasing GWTG - HF risk score severity in all subjects, and also in 749 patients with HF with preserved ejection fraction (ejection fraction ≥50%) and 703 patients with HF with reduced ejection fraction (ejection fraction <50%) patients. The multivariable Cox proportional hazard regression analysis demonstrated that the GWTG - HF risk score was one of the significant predictors of all-cause mortality and cardiac events (all-cause mortality: hazard ratio, 1.537, 95% confidence interval, 1.172-2.023; cardiac events: hazard ratio, 1.584, 95% confidence interval, 1.344-1.860, per 10-point increase of GWTG - HF score). Conclusions The GWTG - HF risk score is a useful multivariable score model for several years after hospitalization in patients with HF in a Japanese population.