Ferran Rueda1,2, Eva Borràs3,4, Cosme García-García1,2, Oriol Iborra-Egea1,2, Elena Revuelta-López1,2, Veli-Pekka Harjola5, Germán Cediel1,2, Johan Lassus6, Tuukka Tarvasmäki6, Alexandre Mebazaa7, Eduard Sabidó3,4, Antoni Bayés-Genís1,2. 1. Heart Institute, Hospital Universitari Germans Trias i Pujol, c/ Canyet SN, 08916 Badalona, Spain. 2. Department of Medicine, CIBERCV, Autonomous University of Barcelona, Barcelona, Spain. 3. Proteomics Unit, Centre de Regulació Genòmica (CRG), Barcelona Institute of Science and Technology (BIST), Dr Aiguader 88, Barcelona, Spain. 4. Universitat Pompeu Fabra (UPF), Dr Aiguader 88, Barcelona, Spain. 5. Emergency Medicine, Department of Emergency Medicine and Services, University of Helsinki, Helsinki University Hospital, Finland. 6. Cardiology, University of Helsinki, Heart and Lung Center, Helsinki University Hospital, Finland. 7. U942 Inserm, University Paris Diderot, APHP Hôpitaux Universitaires Saint-Louis-Lariboisière, INI-CRCT, Paris, France.
Abstract
AIMS: Cardiogenic shock (CS) is associated with high short-term mortality and a precise CS risk stratification could guide interventions to improve patient outcome. Here, we developed a circulating protein-based score to predict short-term mortality risk among patients with CS. METHODS AND RESULTS: Mass spectrometry analysis of 2654 proteins was used for screening in the Barcelona discovery cohort (n = 48). Targeted quantitative proteomics analyses (n = 51 proteins) were used in the independent CardShock cohort (n = 97) to derive and cross-validate the protein classifier. The combination of four circulating proteins (Cardiogenic Shock 4 proteins-CS4P), discriminated patients with low and high 90-day risk of mortality. CS4P comprises the abundances of liver-type fatty acid-binding protein, beta-2-microglobulin, fructose-bisphosphate aldolase B, and SerpinG1. Within the CardShock cohort used for internal validation, the C-statistic was 0.78 for the CardShock risk score, 0.83 for the CS4P model, and 0.84 (P = 0.033 vs. CardShock risk score) for the combination of CardShock risk score with the CS4P model. The CardShock risk score with the CS4P model showed a marked benefit in patient reclassification, with a net reclassification improvement (NRI) of 0.49 (P = 0.020) compared with CardShock risk score. Similar reclassification metrics were observed in the IABP-SHOCK II risk score combined with CS4P (NRI =0.57; P = 0.032). The CS4P patient classification power was confirmed by enzyme-linked immunosorbent assay (ELISA). CONCLUSION: A new protein-based CS patient classifier, the CS4P, was developed for short-term mortality risk stratification. CS4P improved predictive metrics in combination with contemporary risk scores, which may guide clinicians in selecting patients for advanced therapies. Published on behalf of the European Society of Cardiology. All rights reserved.
AIMS: Cardiogenic shock (CS) is associated with high short-term mortality and a precise CS risk stratification could guide interventions to improve patient outcome. Here, we developed a circulating protein-based score to predict short-term mortality risk among patients with CS. METHODS AND RESULTS: Mass spectrometry analysis of 2654 proteins was used for screening in the Barcelona discovery cohort (n = 48). Targeted quantitative proteomics analyses (n = 51 proteins) were used in the independent CardShock cohort (n = 97) to derive and cross-validate the protein classifier. The combination of four circulating proteins (Cardiogenic Shock 4 proteins-CS4P), discriminated patients with low and high 90-day risk of mortality. CS4P comprises the abundances of liver-type fatty acid-binding protein, beta-2-microglobulin, fructose-bisphosphate aldolase B, and SerpinG1. Within the CardShock cohort used for internal validation, the C-statistic was 0.78 for the CardShock risk score, 0.83 for the CS4P model, and 0.84 (P = 0.033 vs. CardShock risk score) for the combination of CardShock risk score with the CS4P model. The CardShock risk score with the CS4P model showed a marked benefit in patient reclassification, with a net reclassification improvement (NRI) of 0.49 (P = 0.020) compared with CardShock risk score. Similar reclassification metrics were observed in the IABP-SHOCK II risk score combined with CS4P (NRI =0.57; P = 0.032). The CS4P patient classification power was confirmed by enzyme-linked immunosorbent assay (ELISA). CONCLUSION: A new protein-based CS patient classifier, the CS4P, was developed for short-term mortality risk stratification. CS4P improved predictive metrics in combination with contemporary risk scores, which may guide clinicians in selecting patients for advanced therapies. Published on behalf of the European Society of Cardiology. All rights reserved.
Authors: Cosme García-García; Teresa Oliveras; Nabil El Ouaddi; Ferran Rueda; Jordi Serra; Carlos Labata; Marc Ferrer; German Cediel; Santiago Montero; Maria Jose Martínez; Helena Resta; Oriol de Diego; Joan Vila; Irene R Dégano; Roberto Elosua; Josep Lupón; Antoni Bayes-Genis Journal: J Clin Med Date: 2020-07-27 Impact factor: 4.241