Which biomarkers reveal neonatal sepsis?

PLoS One. 2013 Dec 18;8(12):e82700. doi: 10.1371/journal.pone.0082700. eCollection 2013.

Abstract

We address the identification of optimal biomarkers for the rapid diagnosis of neonatal sepsis. We employ both canonical correlation analysis (CCA) and sparse support vector machine (SSVM) classifiers to select the best subset of biomarkers from a large hematological data set collected from infants with suspected sepsis from Yale-New Haven Hospital's Neonatal Intensive Care Unit (NICU). CCA is used to select sets of biomarkers of increasing size that are most highly correlated with infection. The effectiveness of these biomarkers is then validated by constructing a sparse support vector machine diagnostic classifier. We find that the following set of five biomarkers capture the essential diagnostic information (in order of importance): Bands, Platelets, neutrophil CD64, White Blood Cells, and Segs. Further, the diagnostic performance of the optimal set of biomarkers is significantly higher than that of isolated individual biomarkers. These results suggest an enhanced sepsis scoring system for neonatal sepsis that includes these five biomarkers. We demonstrate the robustness of our analysis by comparing CCA with the Forward Selection method and SSVM with LASSO Logistic Regression.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Biomarkers / metabolism*
  • Humans
  • Logistic Models
  • Sepsis / diagnosis*
  • Sepsis / metabolism
  • Support Vector Machine

Substances

  • Biomarkers

Grants and funding

This material is based on work partially supported by DARPA (Space and Naval Warfare Systems Center Pacic) under Award No. N66001-11-1-4184 http://www.darpa.mil/. Additional support for this work was provided by Infectious Disease Supercluster, Colorado State University, 2012 seed grant http://infectiousdisease.colostate.edu/. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.