Identifying biomarker-driven subphenotypes of cardiogenic shock: analysis of prospective cohorts and randomized controlled trials.

Summary

Across two prospective cohorts, unsupervised clustering of plasma biomarkers revealed four reproducible cardiogenic shock subphenotypes. The inflammatory and cardiopathic classes had the highest 28-day mortality and improved risk stratification beyond SCAI stages. Applying a simplified classifier to three RCTs suggested potential heterogeneity of treatment effect by subphenotype.

Key Findings

• Unsupervised clustering in two cohorts identified four biomarker-defined CS subphenotypes (adaptive, non-inflammatory, cardiopathic, inflammatory).
• Inflammatory and cardiopathic subphenotypes had significantly higher 28-day mortality; adding subphenotype improved Harrell’s C-index beyond SCAI staging.
• A simplified classifier assigned subphenotypes in three RCTs, enabling exploration of heterogeneity of treatment effect on 28-day mortality.

Clinical Implications

Subphenotype assignment could refine prognostication, guide trial stratification/enrichment, and eventually inform phenotype-targeted therapies for cardiogenic shock.

Limitations

• Biomarker panels and sampling times may differ between cohorts and trials
• Observational nature of associations; not a randomized phenotype-guided intervention

Future Directions

Prospective, phenotype-guided trials to test tailored therapies; standardization of biomarker panels; integration with hemodynamics and imaging.