败血症
医学
四分位间距
免疫学
背景(考古学)
降钙素原
促炎细胞因子
队列
前瞻性队列研究
危险分层
免疫系统
内科学
生物
炎症
古生物学
作者
Matthew J Cummings,Barnabas Bakamutumaho,Komal Jain,Adam H. Price,Nicholas Owor,John Kayiwa,Joyce Namulondo,Timothy Byaruhanga,Moses Muwanga,Christopher Nsereko,Stephen Sameroff,W Ian Lipkin,Julius J. Lutwama,Max R O'Donnell
出处
期刊:American Journal of Tropical Medicine and Hygiene
[American Society of Tropical Medicine and Hygiene]
日期:2023-03-01
卷期号:108 (3): 619-626
标识
DOI:10.4269/ajtmh.22-0483
摘要
ABSTRACT. The global burden of sepsis is concentrated in sub-Saharan Africa (SSA), where epidemic HIV and unique pathogen diversity challenge the effective management of severe infections. In this context, patient stratification based on biomarkers of a dysregulated host response may identify subgroups more likely to respond to targeted immunomodulatory therapeutics. In a prospective cohort of adults hospitalized with suspected sepsis in Uganda, we applied machine learning methods to develop a prediction model for 30-day mortality that integrates physiology-based risk scores with soluble biomarkers reflective of key domains of sepsis immunopathology. After model evaluation and internal validation, whole-blood RNA sequencing data were analyzed to compare biological pathway enrichment and inferred immune cell profiles between patients assigned differential model-based risks of mortality. Of 260 eligible adults (median age, 32 years; interquartile range, 26–43 years; 59.2% female, 53.9% living with HIV), 62 (23.8%) died by 30 days after hospital discharge. Among 14 biomarkers, soluble tumor necrosis factor receptor 1 (sTNFR1) and angiopoietin 2 (Ang-2) demonstrated the greatest importance for mortality prediction in machine learning models. A clinicomolecular model integrating sTNFR1 and Ang-2 with the Universal Vital Assessment (UVA) risk score optimized 30-day mortality prediction across multiple performance metrics. Patients assigned to the high-risk, UVA-based clinicomolecular subgroup exhibited a transcriptional profile defined by proinflammatory innate immune and necroptotic pathway activation, T-cell exhaustion, and expansion of key immune cell subsets including regulatory and gamma-delta T cells. Clinicomolecular stratification of adults with suspected sepsis in Uganda enhanced 30-day mortality prediction and identified a high-risk subgroup with a therapeutically targetable immunological profile. Further studies are needed to advance pathobiologically informed sepsis management in SSA.
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