To evaluate the diagnostic performance of blood biomarkers for early diagnosis of sepsis in ICU patients with acute moderate to severe stroke.
Approach:
Study Design: A prospective cohort study was conducted involving 157 patients with severe cerebrovascular disease admitted to the NICU.
Biomarker Assessment: Blood biomarkers IL-10, MIP-1β, TNF-α, nNOS, iNOS, MMP-9, S-100β, and ET-1 were detected using Enzyme-Linked Immunosorbent Assay (ELISA) within 48 hours after symptom onset.
Statistical Analysis: Multi-factorial logistic regression was used to construct a prediction model for sepsis, with internal validation via bootstrap validation.
Key Findings:
The prevalence of sepsis in acute moderate-to-severe stroke patients was 12.1%.
Patients with sepsis had lower GCS scores and higher NIHSS scores compared to those without sepsis.
Four significant variables identified for the prediction model were Hyperlipidaemia, IL-10, NIHSS, and Blood creatinine.
The prediction model achieved an AUC of 0.816 (95% CI: 0.721 ~ 0.911).
Interpretation:
The study successfully established a prediction model for sepsis in acute moderate-to-severe stroke patients using specific blood biomarkers and clinical parameters.
Limitations:
The study was conducted in a single center, which may limit generalizability.
The sample size may not be sufficient to fully validate the prediction model.
Conclusion:
The prediction model developed in this study shows promise for early identification of sepsis in patients with acute severe stroke.
