Sysmex Cell Population Data for Diagnosing Infection in Patients With Suspected Sepsis in the Emergency Department.

Objectives: Early diagnosis of suspected sepsis is crucial to improve patient survival. Cell population (CP) data, a set of leucocyte research parameters from hematology instruments, has a potential as markers for infection. The aim of this study was to investigate the diagnostic accuracy for infection of CP variables from Sysmex XN instruments in patients with suspected sepsis in the emergency department (ED).

Methods: Adult patients with suspected sepsis in the ED were included. CP variables, C-reactive protein (CRP), and post hoc assessments of infection were recorded. Logistic regression and machine learning methods were used to develop multivariable models, which were evaluated by area under the receiver operating curve (AUC) and calibration plots.

Results: The development cohort and the validation cohort consisted of 600 and 656 patients, respectively. Univariate analyses revealed that complexity in monocytes (MO-X); AUC of 0.78 (0.74, 0.82), reactivity intensity of neutrophils (NEUT-RI); 0.72 (0.67, 0.76), and CRP 0.87 (0.84, 0.90) had the highest diagnostic accuracy for infection. A final multivariable model (the optimal model) using Multilayer perceptron (MLP), including MO-X, NEUT-RI, monocyte size (MO-Z), and neutrophil size (NE-FSC), had an AUC of 0.86 (0.85, 0.87) in the development cohort and 0.78 (0.74, 0.82) in the validation cohort with reasonable calibration. Including CRP in this model further improved accuracy and calibration.

Conclusions: Sysmex CP variables may help diagnose infections in the ED. However, the lack of well-described calibration procedures and quality assurance for non-IVD approved CP variables is an impediment to clinical implementation.