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Neutrophil volume, conductivity and scatter parameters with effective modeling of molecular activity statistical program gives better results in neonatal sepsis
Author(s) -
Celik I. H.,
Demirel G.,
Sukhachev D.,
Erdeve O.,
Dilmen U.
Publication year - 2013
Publication title -
international journal of laboratory hematology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.705
H-Index - 55
eISSN - 1751-553X
pISSN - 1751-5521
DOI - 10.1111/ijlh.12002
Subject(s) - sepsis , medicine , procalcitonin , neonatal sepsis , stepwise regression , intensive care medicine
Summary Introduction Neonatal sepsis remains an important clinical syndrome despite advances in neonatology. Current hematology analyzers can determine cell volume ( V ), conductivity for internal composition of cell ( C ) and light scatter for cytoplasmic granularity and nuclear structure ( S ), and standard deviations which are effective in the diagnosis of sepsis. Statistical models can be used to strengthen the diagnosis. Effective modeling of molecular activity ( EMMA ) uses combinatorial algorithm of the selection parameters for regression equation based on modified stepwise procedure. It allows obtaining different regression models with different combinations of parameters. Methods We investigated these parameters in screening of neonatal sepsis. We used LH 780 hematological analyzer (Beckman Coulter, Fullerton, CA, USA). We combined these parameters with interleukin‐6 ( IL ‐6) and C‐reactive protein ( CRP ) and developed models by EMMA . Results A total of 304 newborns, 76 proven sepsis, 130 clinical sepsis and 98 controls, were enrolled in the study. Mean neutrophil volume ( MNV ) and volume distribution width ( VDW ) were higher in both proven and clinical sepsis groups. We developed three models using MNV , VDW , IL ‐6, and CRP . These models gave more sensitivity and specificity than the usage of each marker alone. Conclusions We suggest to use the combination of MNV and VDW with markers such as CRP and IL ‐6, and use diagnostic models created by EMMA .