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Sarcopenia Index trajectories predict long-term mortality in super-elderly patients with sepsis: a retrospective
Jieyu Chen1, Min Ma1, Xiaoling Zhou1
1Department of Geriatrics, The General Hospital of Western Theater Command, Chengdu, China.
Background:
The dynamic trajectory of muscle mass during sepsis may hold superior prognostic value over static assessments, particularly in vulnerable super-elderly patients. This study aimed to identify distinct dynamic trajectories of the Sarcopenia Index (SI) using Group-Based Trajectory Modeling (GBTM) and investigate their association with 180-day mortality.
Methods:
This retrospective cohort study enrolled 210 super-elderly patients (aged >85 years) with sepsis. GBTM was employed to delineate SI trajectories over 60 days. The primary outcome was 180-day mortality. Kaplan-Meier analysis and multivariable Cox proportional hazards regression were used to assess the association between SI trajectories and mortality. The incremental predictive value of trajectory data was evaluated using C-index, Net Reclassification Improvement (NRI), and Integrated Discrimination Improvement (IDI).
Results:
Two distinct SI trajectories were identified: a "High-Level Group" (n = 88) and a "Low-Level Group" (n = 122). The Low-Level Group was characterized by lower baseline SI, poorer functional status, and higher prevalence of long-term bedridden status. The 180-day mortality rate was higher in the Low-Level Group (62.3% vs. 48.9%); however, this difference did not reach statistical significance in the unadjusted analysis (p = 0.072). After multivariable adjustment, assignment to the Low-Level trajectory remained an independent predictor of mortality (Adjusted HR = 1.64, 95% CI: 1.08-2.48, p = 0.020). Adding the SI trajectory to a clinical risk model led to a small but statistically significant improvement in risk reclassification (NRI = 0.020, p < 0.05), while discrimination gains were modest (IDI = 0.150, p = 0.078).
Conclusion:
A low and declining SI trajectory is an independent predictor of long-term mortality in super-elderly sepsis patients. Dynamic monitoring of SI provides incremental prognostic value over static assessments, offering a novel tool for early risk stratification and targeted interventions.
