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.
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.
Authors: Omar F AbouEzzeddine; Benjamin French; Sultan A Mirzoyev; Allan S Jaffe; Wayne C Levy; James C Fang; Nancy K Sweitzer; Thomas P Cappola; Margaret M Redfield Journal: J Heart Lung Transplant Date: 2016-01-15 Impact factor: 10.247