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

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.

The fibrosis-4 score is associated with long-term mortality in different phenotypes of acute heart failure

BACKGROUND

Fibrosis-4 score (FIB4) was a non-invasive surrogate to estimate the amount of liver scarring in chronic hepatitis. Considering the presence of increased central venous pressure and congestive hepatopathy in patients with decompensated heart failure, we therefore investigated the prognostic values of FIB4 in acute heart failure (AHF) patients.

METHOD

Patients hospitalised primarily for HF were drawn from an intramural registry. FIB4 was calculated according to age, aspartate aminotransferase, alanine aminotransferase and platelet count. All-cause mortality up to 5 years after discharge was obtained by linking to the national death registry.

RESULTS

Among a total of 1854 participants, 940 patients died during a mean follow-up of 28.3 ± 21.8 months. FIB4 score was related to mortality and the composite of cardiovascular death or HF rehospitalisation, independent of age, sex, left ventricular ejection fraction, left atrial dimension, sodium and haemoglobin levels, estimated glomerular filtration rate, comorbidities, and medications [hazard ratio and 95% confidence interval of mortality: 1.009 (1.002-1.015), and the composite of cardiovascular death or HF hospitalisation: 1.020 (1.010-1.031)]. The prognostic value of FIB4 was predominantly in the subjects with heart failure and preserved or mildly reduced ejection fraction (HFpEF and HFmrEF), or coronary artery disease (CAD) than the counterparts [interaction p-value <0.001, and 0.004, respectively].

CONCLUSIONS

FIB4 was an independent predictor of survival in AHF patients, irrespective of the phenotypes of HF. The higher predictive value of mortality of FIB4 was observed in the subjects with HFpEF, HFmrEF or CAD.