Protein-based cardiogenic shock patient classifier

• Published in: European heart journal 2019-08, Vol.40 (32), p.2684-2694
• Main Authors: Rueda, Ferran, Borràs, Eva, García-García, Cosme, Iborra-Egea, Oriol, Revuelta-López, Elena, Harjola, Veli-Pekka, Cediel, Germán, Lassus, Johan, Tarvasmäki, Tuukka, Mebazaa, Alexandre, Sabidó, Eduard, Bayés-Genís, Antoni
• Format: Article
• Language: English
• ISSN: 0195-668X; 1522-9645
• DOI: 10.1093/eurheartj/ehz294

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.