Browsing by Author "Manintveld, Olivier C. (6507985572)"

Purpose: Multiple hormonal and metabolic alterations occur in chronic heart failure (CHF), but their proper monitoring during clinically silent progression of CHF remains challenging. Hence, our objective was to explore whether temporal patterns of six emerging cardiometabolic biomarkers predict future adverse clinical events in stable patients with CHF. Methods: In 263 patients with CHF, we determined the risk of a composite end point of heart failure hospitalization, cardiac death, left ventricular assist device implantation, and heart transplantation in relation to serially assessed blood biomarker levels and slopes (i.e., rate of biomarker change per year). During 2.2 years of follow-up, we repeatedly measured IGF binding proteins 1, 2, and 7 (IGFBP-1, IGFBP-2, IGFBP-7), adipose fatty acid binding protein 4 (FABP-4), resistin, and chemerin (567 samples in total). Results: Serially measured IGFBP-1, IGFBP-2, IGFBP-7, and FABP-4 levels predicted the end point [univariable hazard ratio (95% CI) per 1-SD increase: 3.34 (2.43 to 4.87), 2.86 (2.10 to 3.92), 2.45 (1.91 to 3.13), and 2.46 (1.88 to 3.24), respectively]. Independently of the biomarkers’ levels, their slopes were also strong clinical predictors [per 0.1-SD increase: 1.20 (1.11 to 1.31), 1.27 (1.14 to 1.45), 1.23 (1.11 to 1.37), and 1.27 (1.12 to 1.48)]. All associations persisted after multivariable adjustment for patient baseline characteristics, baseline N-terminal pro-hormone brain natriuretic peptide and cardiac troponin T, and pharmacological treatment during follow-up. Main Conclusions: The temporal patterns of IGFBP-1, IGFBP-2, IGFBP-7, and adipose FABP-4 predict adverse clinical outcomes during outpatient follow-up of patients with CHF and may be clinically relevant as they could help detect more aggressive CHF forms and assess patient prognosis, as well as ultimately aid in designing more effective biomarker-guided therapy. Copyright © 2018 Endocrine Society.

Purpose: Multiple hormonal and metabolic alterations occur in chronic heart failure (CHF), but their proper monitoring during clinically silent progression of CHF remains challenging. Hence, our objective was to explore whether temporal patterns of six emerging cardiometabolic biomarkers predict future adverse clinical events in stable patients with CHF. Methods: In 263 patients with CHF, we determined the risk of a composite end point of heart failure hospitalization, cardiac death, left ventricular assist device implantation, and heart transplantation in relation to serially assessed blood biomarker levels and slopes (i.e., rate of biomarker change per year). During 2.2 years of follow-up, we repeatedly measured IGF binding proteins 1, 2, and 7 (IGFBP-1, IGFBP-2, IGFBP-7), adipose fatty acid binding protein 4 (FABP-4), resistin, and chemerin (567 samples in total). Results: Serially measured IGFBP-1, IGFBP-2, IGFBP-7, and FABP-4 levels predicted the end point [univariable hazard ratio (95% CI) per 1-SD increase: 3.34 (2.43 to 4.87), 2.86 (2.10 to 3.92), 2.45 (1.91 to 3.13), and 2.46 (1.88 to 3.24), respectively]. Independently of the biomarkers’ levels, their slopes were also strong clinical predictors [per 0.1-SD increase: 1.20 (1.11 to 1.31), 1.27 (1.14 to 1.45), 1.23 (1.11 to 1.37), and 1.27 (1.12 to 1.48)]. All associations persisted after multivariable adjustment for patient baseline characteristics, baseline N-terminal pro-hormone brain natriuretic peptide and cardiac troponin T, and pharmacological treatment during follow-up. Main Conclusions: The temporal patterns of IGFBP-1, IGFBP-2, IGFBP-7, and adipose FABP-4 predict adverse clinical outcomes during outpatient follow-up of patients with CHF and may be clinically relevant as they could help detect more aggressive CHF forms and assess patient prognosis, as well as ultimately aid in designing more effective biomarker-guided therapy. Copyright © 2018 Endocrine Society.

Purpose: Acute kidney injury (AKI) frequently occurs after heart transplantation (HTx), but its relation to preoperative right heart hemodynamic (RHH) parameters remains unknown. Therefore, we aimed to determine their predictive properties for postoperative AKI severity within 30 days after HTx. Methods: From 1984 to 2016, all consecutive HTx recipients (n = 595) in our tertiary referral center were included and analyzed for the occurrence of postoperative AKI staged by the kidney disease improving global outcome criteria. The effects of preoperative RHH parameters on postoperative AKI were calculated using logistic regression, and predictive accuracy was assessed using integrated discrimination improvement (IDI), net reclassification improvement (NRI), and area under the receiver operating characteristic curves (AUC). Results: Postoperative AKI occurred in 430 (72%) patients including 278 (47%) stage 1, 66 (11%) stage 2, and 86 (14%) stage 3 cases. Renal replacement therapy (RRT) was administered in 41 (7%) patients. Patients with higher AKI stages had also higher baseline right atrial pressure (RAP; median 7, 7, 8, and in RRT 11 mmHg, p trend = 0.021), RAP-to-pulmonary capillary wedge pressure ratio (median 0.37, 0.36, 0.40, 0.47, p trend = 0.009), and lower pulmonary artery pulsatility index (PAPi) values (median 2.83, 3.17, 2.54, 2.31, p trend = 0.012). Higher RAP and lower PAPi values independently predicted AKI severity [adjusted odds ratio (OR) per doubling of RAP 1.16 (1.02–1.32), p = 0.029; of PAPi 0.85 (0.75–0.96), p = 0.008]. Based on IDI, NRI, and delta AUC, inclusion of these parameters improved the models’ predictive accuracy. Conclusions: Preoperative PAPi and RAP strongly predict the development of AKI early after HTx and can be used as early AKI predictors. © 2018, The Author(s).