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Related Concept Videos

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Related Experiment Video

Updated: Sep 11, 2025

Evaluation of a Reliable Biomarker in a Cecal Ligation and Puncture-Induced Mouse Model of Sepsis
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Sepsis Prediction: Biomarkers Combined in a Bayesian Approach.

João V B Cabral1,2, Maria M B M da Silveira3, Wilma T F Vasconcelos2

  • 1Postgraduate Program in Therapeutic Innovation, Federal University of Pernambuco-UFPE, Professor Moraes Rego Avenue, SN, University City, Recife 50670-420, Brazil.

International Journal of Molecular Sciences
|August 14, 2025
PubMed
Summary
This summary is machine-generated.

Sepsis prediction in children is improved by combining soluble triggering receptor expressed on myeloid cells-1 (sTREM-1), C-reactive protein (CRP), and leukogram. This Bayesian model offers a promising diagnostic tool for early sepsis detection.

Keywords:
Bayes theorembiomarkerscardiac surgerysTREM-1sepsis

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Area of Science:

  • Biomedical research
  • Clinical diagnostics
  • Pediatric critical care

Background:

  • Sepsis poses a significant public health challenge, necessitating improved diagnostic tools.
  • Soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) shows potential as a biomarker for inflammatory and infectious processes.
  • Early and accurate sepsis prediction is crucial for patient outcomes, especially in vulnerable pediatric populations.

Purpose of the Study:

  • To develop and evaluate a predictive model for sepsis in children undergoing surgical correction for congenital heart disease.
  • To assess the utility of sTREM-1, C-reactive protein (CRP), and leukogram in predicting sepsis postoperatively.
  • To integrate these biomarkers using a Bayesian network for enhanced diagnostic accuracy.

Main Methods:

  • A translational study involving 32 pediatric patients with congenital heart disease post-surgical correction.
  • Measurement of sTREM-1, CRP, and leukocyte counts in the postoperative period.
  • Construction of a predictive sepsis model utilizing a Bayesian network approach.

Main Results:

  • Postoperative sTREM-1 levels were significantly higher in septic patients compared to non-septic patients (394.58 pg/mL vs. 239.93 pg/mL, p < 0.001).
  • The ROC curve analysis for sTREM-1 demonstrated an area under the curve of 0.761 (p = 0.013).
  • The Bayesian model indicated a 100% probability of sepsis with CRP > 71 mg/dL, leukogram > 14,000 cells/μL, and sTREM-1 > 283.53 pg/mL.

Conclusions:

  • The combination of sTREM-1, CRP, and leukogram, integrated via a Bayesian network, shows significant promise for the diagnosis of sepsis in pediatric patients.
  • This multi-biomarker approach offers a potentially valuable tool for improving early sepsis detection and management in this high-risk group.
  • Further validation in larger cohorts is warranted to solidify its clinical utility.