Prealbumin improves death risk prediction of BNP-added Seattle Heart Failure Model: Results from a pilot study in elderly chronic heart failure patients

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-F_2t-isoprostane were measured in plasma from 142 consecutive ambulatory, non-diabetic stable CHF (mean NYHA-class 2.6) patients (mean age 75 ± 8 years). 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.