Unsupervised Classification of the Host Response Identifies Dominant Pathobiological Signatures of Sepsis in Sub-Saharan Africa
Authors' conclusion
We identified prognostically enriched pathobiological signatures among patients with sepsis with diverse infections and high HIV prevalence in Uganda.
Study context
- Population
- Adults hospitalised with sepsis (severe infection with qSOFA score ⩾1) in Ugandatwo prospective cohorts
- Participants
- 242 vs 253
- Exposure
- USS-2 vs USS-1 pathobiological signatures
- Discoveryn = 242
- Validationn = 253
- Outcome
- Pathobiological signatures of the host response (173 soluble proteins)
Methodological detailsunsupervised clustering, discovery and validation cohorts, random forest-derived classifier
- Unsupervised clustering
- Discovery and validation cohorts
- Random forest-derived classifier
Main finding
As reported in the abstract
Five-protein classifier reproduced two signatures with similar biological profiles in the validation cohort (AUC)
0.97
Observational data: associations, not effects.
Further findings
- Substantial biological overlap between USS-2 and hyperinflammatory and reactive sepsis phenotypes identified in high-income countries (HICs)
Original publication
Unsupervised Classification of the Host Response Identifies Dominant Pathobiological Signatures of Sepsis in Sub-Saharan Africa. Am J Respir Crit Care Med. Published 1 March 2025. doi:10.
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