A Model for the Prediction of Mortality and Hospitalization in Chinese Heart Failure Patients

Background: Although many risk prediction models have been released internationally, the application of these models in the Chinese population still has some limitations.Aims: The purpose of the study was to establish a heart failure (HF) prognosis model suitable for the Chinese population.Methods: According to the inclusion criteria, we included patients with chronic heart failure (CHF) who were admitted to the Department of Cardiac Rehabilitation of Tongji Hospital from March 2007 to December 2018, recorded each patient's condition and followed up on the patient's re-admission and death. All data sets were randomly divided into derivation and validation cohorts in a ratio of 7/3. Least absolute shrinkage and selection operator regression and Cox regression were used to screen independent predictors; a nomogram chart scoring model was constructed and validated.Results: A total of 547 patients were recruited in this cohort, and the median follow-up time was 519 days. The independent predictors screened out by the derivation cohort included age, atrial fibrillation (AF), percutaneous coronary intervention (PCI), diabetes mellitus (DM), peak oxygen uptake (peak VO2), heart rate at the 8th minute after the cardiopulmonary exercise peaked (HR8min), C-reaction protein(CRP), and uric acid (UA). The C indexes values of the derivation and the validation cohorts were 0.69 and 0.62, respectively, and the calibration curves indicate that the model's predictions were in good agreement with the actual observations.Conclusions: We have developed and validated a multiple Cox regression model to predict long-term mortality and readmission risk of Chinese patients with CHF.Registration Number: ChicTR-TRC-00000235.

Download Full-text

The association between serum selenium concentration and prognosis in patients with heart failure in a Chinese population

Scientific Reports ◽

10.1038/s41598-021-93873-7 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Zhiliang Zhang ◽

Chao Chang ◽

Yuxin Zhang ◽

Zhiyong Chai ◽

Jinbei Li ◽

...

Keyword(s):

Heart Failure ◽

Chinese Population ◽

Selenium Concentration ◽

Chinese Patients ◽

Serum Selenium ◽

Increased Risk ◽

Patients With Heart Failure ◽

All Cause Mortality ◽

Serum Selenium Concentration ◽

Baseline Information

AbstractWhether Selenium (Se) deficiency relates with adverse prognosis in Chinese patients with heart failure (HF) is still unknown. This study aimed to investigate the association of serum Se level and the outcomes of patients with HF in a Chinese population. Patients with HF and serum Se examination were retrospectively included. Baseline information were collected at patient’s first admission. The primary and secondary outcomes were all-cause mortality and rehospitalization for HF during follow-up, respectively. The study participants were divided into quartiles according to their serum Se concentrations. The Cox proportional hazard models were adopted to estimate the association of serum Se levels with observed outcomes. A total of 411 patients with HF with a mean age of 62.5 years were included. The mean serum level of Se was 68.3 ± 27.7 µg/L. There was nonsignificant difference of baseline characterizes between the four quartile groups. In comparison with patients in the highest quartile, those with the lowest quartile (17.40–44.35 µg/L) were associated with increased risk of all-cause mortality [adjusted hazard ratios (95% CI) 2.32 (1.43–3.77); Ptrend = 0.001]. Our study suggested that a lower serum Se level was significantly associated with increased risk of all-cause mortality in patients with HF.

Download Full-text

High N-Terminal proB-Type Natriuretic Peptide Indicates Elevated Risk of Death after Percutaneous Coronary Intervention Compared to Coronary Artery Bypass Surgery in Patients with Left Ventricular Dysfunction

Journal of Clinical Medicine ◽

10.3390/jcm8060898 ◽

2019 ◽

Vol 8 (6) ◽

pp. 898 ◽

Cited By ~ 2

Author(s):

Christian Roth ◽

Matthias Schneider ◽

Daniel Dalos ◽

Clemens Gangl ◽

Christian Toth ◽

...

Keyword(s):

Heart Failure ◽

Percutaneous Coronary Intervention ◽

Survival Benefit ◽

Cox Regression ◽

Artery Bypass ◽

Coronary Intervention ◽

Left Ventricular ◽

Revascularization Procedure ◽

Risk Of Death ◽

Percutaneous Coronary

Background: Reduced left ventricular function (LVF) is a predictor for stent-thrombosis. In advanced heart failure (characterized by high NT-proBNP) with an activated coagulation system, coronary events clinically perceived as sudden death or death from heart failure may be more common in patients treated by percutaneous coronary intervention (PCI) than in patients treated by coronary artery bypass grafting (CABG). Our study analyses (1) if patients with reduced LVF who require coronary revascularization will have a better survival benefit with CABG or PCI, and (2) if the survival benefit is predicted by NT-proBNP. Methods: This observational retrospective study included patients from the coronary catheter laboratory database of the Medical University of Vienna (CCLD-MUW). Multivariate Cox regression analyses were performed to test the hypothesis that there is an interaction in the risk of death between those with lower or elevated NT-proBNP levels and the revascularization procedure (PCI or CABG). The relative risk of PCI compared to CABG as reference was calculated for patients with low and elevated NT-proBNP levels. Results: In the entire study population with 398 patients (340 PCI and 58 CABG) the revascularization procedure had no predictive value. When the revascularization procedure*NTproBNP interaction was forced into the Cox regression model, this term was an independent predictor of death. The relative risk of PCI compared to CABG was similar in patients with lower NT-proBNP—1.01 (95% confidence interval (CI), 0.45–2.24), but was significantly increased in patients with elevated NT-proBNP—1.58 (95% CI, 1.07–2.33). Conclusion: Death is associated to the revascularization procedure, but only in those patients with elevated NT-proBNP levels. NT-proBNP is a predicting factor for the revascularization procedure: elevated levels showed an increased risk of death after PCI compared to CABG, whereas lower levels were associated with a similar risk after both revascularization procedures.

Download Full-text

Abstract 17185: Modest Performance of Heart Failure Clinical Prediction Models: A Systematic External Validation Study

Circulation ◽

10.1161/circ.138.suppl_1.17185 ◽

2018 ◽

Vol 138 (Suppl_1) ◽

Author(s):

Jenica N Upshaw ◽

Jason Nelson ◽

Benjamin Wessler ◽

Benjamin Koethe ◽

Christine Lundquist ◽

...

Keyword(s):

Heart Failure ◽

Prediction Models ◽

External Validation ◽

Significant Heterogeneity ◽

Clinical Prediction ◽

Clinical Prediction Models ◽

Derivation Cohort ◽

C Statistic ◽

Improved Model ◽

Relative Change

Introduction: Most heart failure (HF) clinical prediction models (CPMs] have not been independently externally validated. We sought to test the performance of HF models in a diverse population using a systematic approach. Methods: A systematic review identified CPMs predicting outcomes for patients with HF. Individual patient data from 5 large publicaly available clinical trials enrolling patients with chronic HF were matched to published CPMs based on similarity in populations and available outcome and predictor variables in the clinical trial databases. CPM performance was evaluated for discrimination (c-statistic, % relative change in c-statistic) and calibration (Harrell’s E and E 90 , the mean and the 90% quantile of the error distribution from the smoothed loess observed value) for the original and recalibrated models. Results: Out of 135 HF CPMs reviewed, we identified 45 CPM-trial pairs including 13 unique CPMs. The outcome was mortality for all of the models with a trial match. During external validations, median c-statistic was 0.595 (IQR 0.563 to 0.630) with a median relative decrease in the c-statistic of -57 % (IQR, -49% to -71%) compared to the c-statistic reported in the derivation cohort. Overall, the median Harrell’s E was 0.09 (IQR, 0.04 to 0.135) and E 90 was 0.11 (IQR, 0.07 to 0.21). Recalibration of the intercept and slope led to substantially improved calibration with median change in Harrell’s E of -35% [IQR 0 to -75%] for the intercept and -56% [IQR -17% to -75%] for the intercept and slope. Refitting model covariates improved the median c-statistic by 38% to 0.629 [IQR 0.613 to 0.649]. Conclusion: For HF CPMs, independent external validations demonstrate that CPMs perform significantly worse than originally presented; however with significant heterogeneity. Recalibration of the intercept and slope improved model calibration. These results underscore the need to carefully consider the derivation cohort characteristics when using published CPMs.

Download Full-text

Development and Validation of a Nomogram to Predict the 180-Day Readmission Risk for Chronic Heart Failure: A Multicenter Prospective Study

Frontiers in Cardiovascular Medicine ◽

10.3389/fcvm.2021.731730 ◽

2021 ◽

Vol 8 ◽

Author(s):

Shanshan Gao ◽

Gang Yin ◽

Qing Xia ◽

Guihai Wu ◽

Jinxiu Zhu ◽

...

Keyword(s):

Heart Failure ◽

Chronic Heart Failure ◽

Stepwise Regression ◽

Prediction Models ◽

Cox Regression ◽

Univariate Analysis ◽

External Validation ◽

Calibration Plot ◽

Lasso Regression ◽

Internal Validation

Background: The existing prediction models lack the generalized applicability for chronic heart failure (CHF) readmission. We aimed to develop and validate a widely applicable nomogram for the prediction of 180-day readmission to the patients.Methods: We prospectively enrolled 2,980 consecutive patients with CHF from two hospitals. A nomogram was created to predict 180-day readmission based on the selected variables. The patients were divided into three datasets for development, internal validation, and external validation (mean age: 74.2 ± 14.1, 73.8 ± 14.2, and 71.0 ± 11.7 years, respectively; sex: 50.2, 48.8, and 55.2% male, respectively). At baseline, 102 variables were submitted to the least absolute shrinkage and selection operator (Lasso) regression algorithm for variable selection. The selected variables were processed by the multivariable Cox proportional hazards regression modeling combined with univariate analysis and stepwise regression. The model was evaluated by the concordance index (C-index) and calibration plot. Finally, the nomogram was provided to visualize the results. The improvement in the regression model was calculated by the net reclassification index (NRI) (with tenfold cross-validation and 200 bootstraps).Results: Among the selected 2,980 patients, 1,696 (56.9%) were readmitted within 180 days, and 1,502 (50.4%) were men. A nomogram was established by the results of Lasso regression, univariate analysis, stepwise regression and multivariate Cox regression, as well as variables with clinical significance. The values of the C-index were 0.75 [95% confidence interval (CI): 0.72–0.79], 0.75 [95% CI: 0.69–0.81], and 0.73 [95% CI: 0.64–0.83] for the development, internal validation, and external validation datasets, respectively. Calibration plots were provided for both the internal and external validation sets. Five variables including history of acute heart failure, emergency department visit, age, blood urea nitrogen level, and beta blocker usage were considered in the final prediction model. When adding variables involving hospital discharge way, alcohol taken and left bundle branch block, the calculated values of NRI demonstrated no significant improvements.Conclusions: A nomogram for the prediction of 180-day readmission of patients with CHF was developed and validated based on five variables. The proposed methodology can improve the accurate prediction of patient readmission and have the wide applications for CHF.

Download Full-text

Abstract 036: Derivation and Validation of a Novel Risk Equation for 10-year Risk of Incident Heart Failure in the General US Population

Circulation ◽

10.1161/circ.137.suppl_1.036 ◽

2018 ◽

Vol 137 (suppl_1) ◽

Author(s):

Sadiya S Khan ◽

Hongyan Ning ◽

Sanjiv J Shah ◽

Clyde W Yancy ◽

John T Wilkins ◽

...

Keyword(s):

Heart Failure ◽

Cardiovascular Health ◽

Prediction Models ◽

Smoking Status ◽

Health Study ◽

Cardiovascular Health Study ◽

Targeted Prevention ◽

Prevention Strategies ◽

Chi Square ◽

Derivation Cohort

Background: Identification of individuals at risk for heart failure (HF) is necessary for implementation of primary prevention strategies. However, currently no validated prediction models exist for assessment of HF risk in a broad-based general population (ACC/AHA Stage 0 and Stage A individuals) based on routinely available clinical data. Methods: Estimation of 10-year risk equations for developing a HF event were derived from community-based cohorts representative of the U.S. population of Whites and Blacks. Participants were included from ARIC (Atherosclerosis Risk in Communities) study, Cardiovascular Health Study, the CARDIA (Coronary Artery Risk Development in Young Adults) study, Multi-Ethnic Study of Atherosclerosis, and Framingham Offspring Study cohorts who were recruited between 1985-2000, between the ages of 30 to 80 years, free of cardiovascular disease at baseline, and had 12-years of follow-up. Sex- and race-specific 10-year risk equations were derived in a random pre-specified subset of the pooled sample (n=11,771) and subsequently validated in the remaining participants (n=11,770). Harrell’s C-statistic and Greenwood-Nam-D'Agostino chi-square were used to determine discrimination and calibration of these models. Results: In the derivation cohort, 58% were women, 22% black, and mean age 52.7±11.9 years. HF occurred in 1,339 participants. Independent predictors of HF included in the model were age, blood pressure (treated or untreated), fasting glucose (treated or untreated), body mass index, cholesterol, smoking status, and QRS duration. The data-derived model had excellent discrimination in the 11,770 distinct participants in the validation cohort (C-statistics 0.71-0.85) and was well-calibrated ( Figure) . Conclusions: A 10-year HF risk score that incorporates readily available clinical parameters in the primary care setting can be used to identify individuals with higher likelihood of developing HF who may merit intensive screening and/or targeted prevention strategies.

Download Full-text

P6336Plasma proteomic profile predicts survival in heart failure with reduced ejection fraction

European Heart Journal ◽

10.1093/eurheartj/ehz746.0933 ◽

2019 ◽

Vol 40 (Supplement_1) ◽

Author(s):

H Gui ◽

R C She ◽

J Li ◽

H Sabbah ◽

L K Williams ◽

...

Keyword(s):

Heart Failure ◽

Ejection Fraction ◽

Risk Stratification ◽

Risk Score ◽

Cox Regression ◽

Validation Cohort ◽

Predictive Score ◽

Reduced Ejection Fraction ◽

Derivation Cohort ◽

C Statistic

Abstract Background Whether the plasma proteome can predict the course of heart failure (HF) and has incremental value to established predictors is uncertain. Methods Patients meeting Framingham HF criteria with history of reduced ejection fraction (n=1017) were prospectively enrolled in a registry and donated fasting blood samples. Plasma underwent analysis on the SOMAscan proteomic discovery platform, quantifying 4789 proteins using standard assay and quality controls. Patients were randomly divided into derivation (n=681) and validation (n=336) cohorts. We derived a proteomic risk score (PRS) in the derivation cohort using Lasso-penalized Cox regression and then tested it in the validation cohort. Both models were adjusted for an establish HF clinical risk score (MAGGIC) and NTproBNP. We assessed risk stratification improvement in the validation cohort by comparing models with and without PRS using the model C statistic, continuous net reclassification index (NRI), integrated discrimination index (IDI), and the median improvement in risk score (MIRS). Results Overall 47.5% of patients were African American, 35.2% were female, mean ejection fraction was 34.8%, and average age was 67.9 years. After median follow-up of 3.6 years, there were 296 deaths (194 in derivation and 102 in validation). Optimized modeling defined a 32 protein PRS (hazard ratio [HR] 2.33, p<2.00E-16) which was also statistically significant when tested in the validation cohort (PRS HR=1.19, p=4.87E-02) and showed some improvement in risk stratification (Table). Methods Variables Estimate 95% CI P Validation Testing MAGGIC 1.06 1.027, 1.092 2.84E-04 NTproBNP 1.84 1.430, 2.359 1.88E-06 PRS 1.19 1.001, 1.408 4.87E-02 Risk Stratification Assessment C-statistic improvement 0.012 −0.076, 0.101 8.30E-01 IDI 0.034 0.007, 0.095 <2.00E-16 Continuous-NRI 0.286 −0.062, 0.475 9.00E-02 Median Improvement in Risk Score 0.015 0.001, 0.078 2.00E-02 Conclusion A plasma multi-protein predictive score can improve risk stratification in HF patients on top of a validated clinical score and NTproBNP. Additional investigation is warranted to define mechanisms underlying individual proteins and explore proteomic clinical applications.

Download Full-text

N-terminal pro-brain natriuretic peptide and adverse outcomes in Chinese patients with hypertrophic cardiomyopathy

Bioscience Reports ◽

10.1042/bsr20212098 ◽

2021 ◽

Author(s):

Zeng-Lei Zhang ◽

Yan-Yan Xu ◽

Zhen Qin ◽

Yong-Zheng Lu ◽

Tian-Ding Liu ◽

...

Keyword(s):

Heart Failure ◽

Hypertrophic Cardiomyopathy ◽

Brain Natriuretic Peptide ◽

Natriuretic Peptide ◽

Cox Regression ◽

Early Recognition ◽

Adverse Outcomes ◽

Chinese Patients ◽

Risk Category ◽

Cox Regression Analysis

Background: Although numerous studies have suggested that elevated N-terminal pro-brain natriuretic peptide (NT-proBNP) is positively correlated with cardiovascular events, especially the heart failure and heart failure-related death (HFRD), evidence of the association between NT-proBNP and the adverse outcomes of hypertrophic cardiomyopathy (HCM) is still relatively limited. The present study was performed to evaluate the relationship between NT-proBNP and outcomes in patients with HCM. Methods: Observational cohort methodology was used in this study, and a total of 227 patients were included. And the patients were followed for 44.97 ± 16.37 months. Patients were categorized into three groups according to these NT-proBNP tertiles: first tertile (≤ 910 pg/mL, n=68), second tertile (913-2141 pg/mL, n=68), and third tertile (≥ 2151 pg/mL, n=69). The adverse outcomes of this study were all-cause death (ACD) and cardiac death (CD). Results: According to the risk category of NT-proBNP, the incidences of ACD (P=0.005) and CD (P=0.032) among the three groups showed significant differences. Multivariate Cox regression analysis suggested that the ACD and CD in the third tertile have 7.022 folds (hazard risk [HR] =7.022 [95% confidence interval [CI]: 1.397-35.282], P=0.018) and 7.129 folds ([HR] =7.129 [95% [CI]: 1.329-38.237], P=0.022) increased risks as compared with those in the first tertile. Kaplan-Meier survival analyses showed that the cumulative risks of ACD and CD in patients with HCM tended to increase. Conclusion: The present study indicated NT-proBNP was a novel biomarker suitable for predicting adverse prognosis in patients with HCM, which may be used for early recognition and risk stratification.

Download Full-text

Barthel Index score predicts mortality in elderly heart failure: a goal of comprehensive cardiac rehabilitation

European Heart Journal ◽

10.1093/eurheartj/ehab724.2809 ◽

2021 ◽

Vol 42 (Supplement_1) ◽

Author(s):

S Katano ◽

T Yano ◽

K Ohori ◽

H Kouzu ◽

R Nagaoka ◽

...

Keyword(s):

Heart Failure ◽

Cardiac Rehabilitation ◽

Functional Status ◽

Barthel Index ◽

Cox Regression ◽

Hazard Ratio ◽

National Budget ◽

Net Reclassification Improvement ◽

Prediction Of Mortality

Abstract Background Accurate prediction of mortality in heart failure (HF) patients is crucial for decision-making regarding HF therapies, but a strategy for the prediction of mortality in elderly HF patients has not been established. In addition, although favorable effects of comprehensive cardiac rehabilitation (CR) on clinical outcomes and functional status in HF patients have been demonstrated, a goal of comprehensive CR during hospitalization for reducing mortality remains unclear. Aims We examined whether assessment of basic activities of daily living (ADL) by the Barthel Index (BI), the most widely used tool for assessment of basic ADL, is useful for predicting all-cause mortality in elderly HF patients who received comprehensive CR. Methods This study was a single-center, retrospective and observational study. We retrospectively examined 413 HF patients aged ≥65 years (mean age, 78±7 years; 50% female) who were admitted to our institute for management of HF and received comprehensive CR during hospitalization. Functional status for performing basic ADL ability was assessed by the BI within 3 days before discharge. The clinical endpoint was all-cause death during the follow-up period. Results Of 413 HF patients, 116 patients (28%) died during a follow-up period of median 1.90-years (interquartile range, 1.20–3.23 years). Results of an adjusted dose-dependent association analysis showed that the hazard ratio (HR) of mortality increases in an almost linear fashion as the BI score decreases and that the BI score corresponding the hazard ratio of 1.0 is 85 (Figure A). To minimize the differences in potential confounding factors between patient with low BI (<85) and patients with high BI (≥85), inverse probability treatment weighting (IPTW) was calculated using propensity score. Kaplan-Meier survival curves, in which selection bias was minimized by use of IPTW for confounders, showed that patients with low BI (<85) had a higher mortality rate than did patients with high BI (≥85) (Figure B). In multivariate Cox regression analyses, low BI was independently associated with higher mortality after adjustment for predictors including brain natriuretic peptide and prior HF hospitalization (IPTW-adjusted HR, 1.75 [95% confidence interval, 1.03–2.98], p<0.001). Inclusion of the BI into the adjustment model improved the accuracy of prediction of mortality (continuous net reclassification improvement, 0.292, p=0.008; integrated discrimination improvement, 0.017, p=0.022). Conclusion A BI score of <85 at the time of discharge is associated with increased mortality independently of known prognostic markers, and achievement of functional status of a BI score ≥85 by comprehensive CR during hospitalization may contribute to a favorable outcome in elderly HF patients. FUNDunding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): the Japan Society for the Promotion of Science

Download Full-text

Prognostic Implication of Admission HbA1c for All-cause Mortality in Ischemic Heart Failure Among a Chinese Population: A Prospective Cohort Study

10.21203/rs.3.rs-728195/v1 ◽

2021 ◽

Author(s):

Weida Qiu ◽

Sicheng Chen ◽

Anping Cai ◽

Xiaoju Xiao ◽

Zhiping Gao ◽

...

Keyword(s):

Heart Failure ◽

Chinese Population ◽

Hba1c Level ◽

Cox Regression ◽

Glycosylated Hemoglobin ◽

Ischemic Heart ◽

Ischemic Heart Failure ◽

Cox Regression Analysis ◽

All Cause Mortality ◽

The Impact

Abstract Background: The impact of glycosylated hemoglobin A1c (HbA1c) on heart failure (HF) and ischemic heart disease (IHD) differs among studies, and IHD is a preponderant cause in HF. We investigated the link between admission HbA1c and all-cause mortality in a Chinese population with ischemic heart failure (IHF).Methods: Eligible patients with IHF at the Department of Cardiology, Guangdong Provincial People’s Hospital from December 2015 to June 2019 were enrolled to investigate the association between admission HbA1c and all-cause mortality of IHF with Kaplan-Meier survival analysis and Cox regression analysis.Results: Of 1413 participants, the median age was 63.2 ± 10.9 years, 85% were men and median admission HbA1c level was 6.82%. All-cause mortality was higher in HbA1c >7% group compared with HbA1c ≤7% group (hazard ratio (HR): 1.328, 95% confidence interval (CI): 1.016-1.735, p =0.037), and sensitivity analysis appeared the consistent result. The association between HbA1c and all-cause mortality was also statistically significant in the male and younger cohorts.Conclusions: Elevated admission HbA1c level (>7%) is an independent risk factor for all-cause mortality of IHF in the general population, and there is also a consistent trend among male and younger individuals. Further explorations are required to elucidate whether glycemic management plays a crucial role in the progression of IHF within female and elderly population.

Download Full-text