Dataset Information

Soluble ST2 in the prediction of heart failure and death in patients with atrial fibrillation.

ABSTRACT:

Background

Biomarkers may be a useful marker for predicting heart failure (HF) or death in patients with atrial fibrillation (AF).

Hypothesis

Soluble ST2 (sST2) may be a good biomarker for the prediction of HF or death in patients with AF.

Methods

This is a prospective study of patients with nonvalvular AF. Clinical outcomes were HF or death. Clinical and laboratory data were compared between those with and without clinical outcomes. Univariate and multivariate analysis was performed to determine whether sST2 is an independent predictor for heart failure or death in patients with nonvalvular AF.

Results

A total of 185 patients (mean age: 68.9 ± 11.0 years) were included, 116 (62.7%) were male. The average sST2 and N-terminal pro-brain natriuretic peptide (NT-proBNP) levels were 31.3 ± 19.7 ng/ml and 2399.5 ± 6853.0 pg/ml, respectively. Best receiver operating characteristic (ROC) cut off of sST2 for predicting HF or death was 30.14 ng/ml. Seventy-three (39.5%) patients had an sST2 level ≥30.14 ng/ml, and 112 (60.5%) had an sST2 level <30.14 ng/dl. The average follow-up was 33.1 ± 6.6 months. Twenty-nine (15.7%) patients died, and 33 (17.8%) developed HF during follow-up. Multivariate analysis revealed that high sST2 to be an independent risk factor for death or HF with a HR and 95% CI of 2.60 (1.41-4.78). The predictive value of sST2 is better than NT-proBNP, and it remained significant in AF patients irrespective of history of HF, and NT-proBNP levels.

Conclusions

sST2 is an independent predictor of death or HF in patients with AF irrespective of history of HF or NT-proBNP levels.

SUBMITTER: Krittayaphong R

PROVIDER: S-EPMC9019881 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Soluble ST2 in the prediction of heart failure and death in patients with atrial fibrillation.

Krittayaphong Rungroj R Pumprueg Satchana S Sairat Poom P

Clinical cardiology 20220221 4

<h4>Background</h4>Biomarkers may be a useful marker for predicting heart failure (HF) or death in patients with atrial fibrillation (AF).<h4>Hypothesis</h4>Soluble ST2 (sST2) may be a good biomarker for the prediction of HF or death in patients with AF.<h4>Methods</h4>This is a prospective study of patients with nonvalvular AF. Clinical outcomes were HF or death. Clinical and laboratory data were compared between those with and without clinical outcomes. Univariate and multivariate analysis was ...[more]

PMID: 35188278

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Project description:BackgroundTo develop a prediction model for in-hospital mortality of patients with heart failure (HF) and atrial fibrillation (AF).MethodsThis 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.ResultsThe 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.ConclusionThe 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.

Dataset Information

Soluble ST2 in the prediction of heart failure and death in patients with atrial fibrillation.

Background

Hypothesis

Methods

Results

Conclusions

Publications

Soluble ST2 in the prediction of heart failure and death in patients with atrial fibrillation.

Similar Datasets

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