External validation of the new REACT-HF score for heart failure prediction in patients with atrial fibrillation

Abstract Background Heart failure (HF) represents the main cause of hospital admissions and deaths among atrial fibrillation (AF) patients, but precise risk prediction tools are lacking. Recently, the REACT-HF score has been developed to predict incident HF hospitalizations or cardiovascular (CV) death within 2-years based on 12 variables (sex, age, height, creatinine clearance, diabetes, vascular disease, valvular heart disease, heart rate and rhythm, left ventricular hypertrophy and intraventricular conduction delay). Purpose The aim of the present study was to externally validate the REACT-HF score within the Swiss-AF and BEAT-AF cohorts, and to investigate whether this score model can be improved by adding biomarkers (hs-CRP, NT-proBNP, hs-TNT). Methods We included 2’599 AF patients from the Swiss- and BEAT-AF cohorts without prior history of HF, with at least one follow-up and with all baseline variables needed for the REACT-HF score. To validate the score, we estimated a Cox model with the original score as the only predictor. We further explored whether the predictive performance of the REACT-HF score model could be improved by adding any combination of the above listed biomarkers. The primary outcome was incident HF hospitalization or CV death. Secondary outcomes included the individual components of the primary outcome and all-cause mortality. Results Mean age was 70.2 years, 29.1% were female and 54.8% had paroxysmal AF. The mean CHA2DS2-VASc score was 2.7 (+/- 1.6). The most frequent comorbidities were hypertension (65%), diabetes (12%), vascular disease (23%) and coronary artery disease (36%). Most patients (1’883) presented a very low REACT-HF score below 0.05 (72.4%), 530 patients between 0.05 and below 0.1 (20.4%) and 186 had a risk score of 0.1 and above (7.2%). In the validation set, 380 (14.6%), 471 (18.1%), 511 (19.7%) 561 (21.6%) and 676 (26.0%) patients were categorized in the lowest to the highest quintiles based on the original score`s quintiles. Figure 1 shows the Kaplan-Meier survival curves for the primary endpoint of first HF hospitalization or CV death by quintiles of the REACT-HF score, applied in our pooled cohort. And Figure 2 shows the Kaplan-Meier curves for the 1st HF hospitalization. The incidence rates at 2-year follow-up per 100 patient-years of the primary outcome (0.39, 0.59, 1.58, 3.97, 7.53), HF hospitalization (0.39, 0.49, 1.38, 2.75, 6.26), CV death (0.0, 0.10, 0.20, 1.29, 2.12), and all cause-death (0.10, 0.49, 0.78, 2.29, 4.24) all increased gradually among the quintiles of risk score. The estimated c-statistic for the composite primary outcome was 0.764 (approximate 95% CI, 0.723-0.806). The best biomarker enhanced-model within our cohort was the model including hs-CRP and NT-proBNP (c-statistic 0.810). Conclusions The REACT-HF score discriminates well for prediction of HF hospitalization and CV death in a contemporary AF population and can be improved by including NT-pro-BNP and hs-CRP.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.