Related Experiment Video
Updated: May 5, 2026
Rat Burn Model to Study Full-Thickness Cutaneous Thermal Burn and Infection
Published on: August 23, 2022
Dynamic biomarker profiling and phenotyping in burn sepsis: a retrospective cohort study using growth mixture
Pei Xu1, Jiaqi Lou1, Hong Kong2
1Burn Department, Ningbo No. 2 Hospital, Wenzhou Medical University, Ningbo, Zhejiang, China.
Objective:
To assess the dynamic prognostic value of multicategory biomarkers in burn sepsis and identify patient phenotypes based on their longitudinal trajectories.
Methods:
This retrospective cohort study included 712 adult patients with burn sepsis (Sepsis-3) admitted to a regional burn ICU (2022-2025). Seventeen biomarkers covering nutrition (albumin, ALB; prealbumin, PA; transferrin, TRF; nitrogen balance), immunity (immunoglobulins A/G/M; CD3+/CD4+/CD8+ T cells, CD4+/CD8+ ratio; natural killer, NK cells), and inflammation (interleukin-6, IL-6; C-reactive protein, CRP; procalcitonin, PCT; platelet count, lactate) were measured at five time points (days 1, 3, 7, 14, and 21). We compared survivor/non-survivor trajectories using linear mixed-effects models, assessed baseline biomarker associations with 21-day mortality via Cox regression, and evaluated predictive performance with Harrell's C-index. Growth mixture modeling (GMM) identified phenotypes from integrated ALB, IL-6, and immunoglobulin G (IgG) trajectories.
Results:
The 21-day mortality was 17.9% (81 deaths). Survivor and non-survivor trajectories differed significantly for multiple biomarkers (P < 0.05). Growth mixture modeling identified two distinct patient phenotypes: a high-risk phenotype (n = 267, mortality 15.7%) characterized by persistently lower ALB and IgG and sustained IL-6 elevation over 21 days and a low-risk phenotype (n = 445, mortality 8.8%) with favorable biomarker trajectories (P = 0.005). Univariable analysis associated several baseline markers with mortality (e.g., ALB: HR = 0.97, P = 0.013; IL-6: HR = 1.004, P = 0.004). However, no biomarker retained independent significance in multivariable analysis, likely due to multicollinearity among nutritional markers [variance inflation factor (VIF) up to 8.4]. Harrell's C-indices for baseline ALB, PA, and IgG were modest (0.604, 0.583, and 0.585, respectively).
Conclusions:
Longitudinal multicategory biomarker trajectories predict 21-day survival in burn sepsis. Trajectory-based phenotyping identifies patient subgroups with markedly different outcomes, offering superior prognostic stratification over static measurements. The integrated phenotype, reflecting the dynamic interplay of catabolism, immune paralysis, and inflammation, emerges as a robust prognostic marker, supporting personalized management approaches.
