Delta-neutrophil index: a potential predictor of coronary artery involvement in Kawasaki disease by retrospective analys
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Rheumatology International https://doi.org/10.1007/s00296-019-04448-9
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Delta‑neutrophil index: a potential predictor of coronary artery involvement in Kawasaki disease by retrospective analysis Sang Hun Lee1 · Kyung Ok Ko1 · Jae Woo Lim1 · Jung Min Yoon1 · Young Hwa Song1 · Jong Wook Lee2 · Eun Jung Cheon1 Received: 3 July 2019 / Accepted: 16 September 2019 © Springer-Verlag GmbH Germany, part of Springer Nature 2019
Abstract DNI is the immature granulocyte fraction provided by a blood cell analyzer, which is determined by subtracting the fraction of mature polymorphonuclear leukocytes from the sum of myeloperoxidase-reactive cells. We aimed to evaluate the role of Delta-neutrophil index (DNI) in cardiac prognosis prediction in children with Kawasaki disease (KD). Medical records of 193 patients were retrospectively reviewed. The values of DNI, white blood cells, erythrocyte sedimentation rate, the percent of polymorphonuclear leucocytes, C-reactive protein, aspartate transaminase, alanine aminotransferase, total bilirubin data of children with KD were analyzed. Also, sex and age of children were compared. The value of DNI was higher in children with cardiac complications [median 0.8 (0–0.26) vs 5.3 (3.55–8.95); P 5 years old), or 1.5 × larger of internal diameter than the adjacent segment [8].
Delta‑neutrophil index The difference between the leukocyte differentials assayed in the MPO channel and those measured in the nuclear lobularity channel was designated as delta-neutrophil index (DNI) [9], which corresponds to the fraction of immature granulocytes (IG) in circulating blood. The automatic cell counter (ADVIA 120, Siemens, Inc.) measured DNI simultaneously by performing CBC without additional order or cost and reported it with the results of CBC. The same autoanalyzer was used for all the tests to detect the DNI during that period.
Statistical analysis All of the data were analyzed using IBM SPSS Statistics ver. 20.0 (IBM Co., Armonk, NY, USA). We checked the distribution of all parameters by Kolmogorov–Smirnov test. All data except the value of ESR and PMN were not normally distributed. So, the clinical characteristics and laboratory findings were statistically analyzed via a Mann–Whitney U test for continuous variables and Fisher’s exact test for categorical variables. Multivariable logistic regression analysis was performed using the factors that had been selected by univariable analysis. As our data were not normally distributed, quantitative variables were presented as the median (25th–75th percentiles). A P value
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