Related Experiment Video
Updated: May 11, 2026
Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure
Published on: June 10, 2025
Prealbumin improves death risk prediction of BNP-added Seattle Heart Failure Model: results from a pilot study in
Aderville Cabassi1, Jacques de Champlain, Umberto Maggiore
1Cardiorenal Research Unit, Department of Clinical and Experimental Medicine, University of Parma Medical School, Via Gramsci 14, 43126 Parma, Italy.
Background:
An accurate prognosis prediction represents a key element in chronic heart failure (CHF) management. Seattle Heart Failure Model (SHFM) prognostic power, a validated risk score for predicting mortality in CHF, is improved by adding B-type natriuretic peptide (BNP). We evaluated in a prospective study the incremental value of several biomarkers, linked to different biological domains, on death risk prediction of BNP-added SHFM.
Methods:
Troponin I (cTnI), norepinephrine, plasma renin activity, aldosterone, high sensitivity-C reactive protein (hs-CRP), tumor necrosis factor-α (TNF-α), interleukin 6 (IL-6), interleukin 2 soluble receptor, leptin, prealbumin, free malondialdehyde, and 15-F2t-isoprostane were measured in plasma from 142 consecutive ambulatory, non-diabetic stable CHF (mean NYHA-class 2.6) patients (mean age 75±8years). Calibration, discrimination, and risk reclassification of BNP-added SHFM were evaluated after individual biomarker addition.
Results:
Individual addition of biomarkers to BNP-added SHFM did not improve death prediction, except for prealbumin (HR 0.49 CI: (0.31-0.76) p=0.002) and cTnI (HR 2.03 CI: (1.20-3.45) p=0.009). In fact, with respect to BNP-added SHFM (Harrell's C-statistic 0.702), prealbumin emerged as a stronger predictor of death showing the highest improvement in model discrimination (+0.021, p=0.033) and only a trend was observed for cTn I (+0.023, p=0.063). These biomarkers showed also the best reclassification statistic (Integrated Discrimination Improvement-IDI) at 1-year (IDI: cTnI, p=0.002; prealbumin, p=0.020), 2-years (IDI: cTnI, p=0.018; prealbumin: p=0.006) and 3-years of follow-up (IDI: cTnI p=0.024; prealbumin: p=0.012).
Conclusions:
Individual addition of prealbumin allows a more accurate prediction of mortality of BNP enriched SHFM in ambulatory elderly CHF suggesting its potential use in identifying those at high-risk that need nutritional surveillance.
