• Int J Lab Hematol · Feb 2021

    Evaluation of the accuracy of immature granulocyte percentage in predicting pediatric serious bacterial infection.

    • Ali Güngör, Aytaç Göktuğ, Aysun Tekeli, İlknur Bodur, Betül Öztürk, Muhammed Mustafa Güneylioğlu, Raziye Merve Yaradılmış, Ayla Akca Çağlar, Nilden Tuygun, and Can Demir Karacan.
    • Department of Pediatric Emergency Medicine, Dr. Sami Ulus Maternity and Child Health and Diseases Training and Research Hospital, Ankara, Turkey.
    • Int J Lab Hematol. 2021 Feb 1.

    IntroductionSerious bacterial infections (SBI) are major causes of mortality and morbidity in children. The aim of this study was to determine the accuracy of the immature granulocyte (IG) percentage in predicting SBI.MethodsPatients admitted to the pediatric emergency department with fever were divided into two groups: with SBI and with non-SBI. White blood cell (WBC) count, absolute neutrophil count (ANC), C-reactive protein (CRP), and the percentage of IG value were recorded, and their accuracy in predicting SBI was evaluated.ResultsSixty-one (14.3%) patients fell into the SBI group and 367 (85.7%) were with non-SBI. Mean IG percentage among SBI patients was 0.84 ± 1.21 and 0.27 ± 0.20 for with non-SBI patients (P = .001). Based on disease, the highest IG percentage was found in patients diagnosed with sepsis (IG 3.7 ± 3.5%) and with bacterial meningitis (IG 1.6 ± 1.3%). The area under the curve (AUC) of IG percentage to predict SBI was 0.83 with 95% confidence interval (CI) [0.78-0.88]; WBC was 0.76 (95% CI 0.70-0.83); ANC was 0.73 (95% CI 0.67-0.80), and CRP was 0.79 (95% CI 0.73-0.85). When infection markers were compared to the most appropriate cut-off values in predicting SBI, IG percentage showed the highest sensitivity and specificity. When the cut-off value was determined as >0.35 for IG percentage, sensitivity was 75.4% and specificity was 76.6% in predicting SBI.ConclusionPatients with SBI had a higher IG percentage. Compared to other biomarkers, IG percentage had higher sensitivity and specificity in predicting SBI.© 2021 John Wiley & Sons Ltd.

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