Indirectly determined hematology reference intervals for pediatric patients in Berlin and Brandenburg
Author:
Mrosewski Ingo1, Dähn Tobias1, Hehde Jörg1, Kalinowski Elena1, Lindner Ilona1, Meyer Thea Marie1, Olschinsky-Szermer Michael1, Pahl Jana1, Puls Monika1, Sachse Kristin1, Switkowski Rafael1
Affiliation:
1. Department of Laboratory Medicine , MDI Limbach Berlin GmbH , Berlin , Germany
Abstract
Abstract
Objectives
Establishing direct reference intervals (RIs) for pediatric patients is a very challenging endeavor. Indirectly determined RIs can address this problem by utilization of existing clinical laboratory databases. In order to provide better laboratory services to the local pediatric population, we established population-specific hematology RIs via data mining.
Methods
Our laboratory information system (LIS) was searched for pediatric blood counts of patients aged from 0 days to 18 years, performed from 1st of January 2018 until 31st of March 2021. In total, 27,554 blood counts on our SYSMEX XN-9000 were initially identified. After application of pre-defined exclusion criteria, 18,531 sample sets remained. Age- and sex-specific RIs were established in accordance with International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) and Clinical & Laboratory Standards Institute (CLSI) recommendations.
Results
When compared to pediatric RIs supplied by other authors, the RIs determined specifically for pediatric patients from Berlin and Brandenburg showed several relevant differences, especially with regard to white blood cell counts (WBCs), red blood cell counts (RBCs), red cell distribution widths (RDW) and platelet counts (PLTs) within the distinct age groups. Additionally, alterations to several published age-specific partitions had to be made, while new sex-specific partitions were introduced for WBCs and PLTs.
Conclusions
Generic RIs from textbooks, manufacturer information and medical publications – even from nationwide or multicenter studies – commonly used in many laboratories might not reflect the specifics of local patient populations properly. RIs should be tailored to the serviced patient population whenever possible. Careful data mining appears to be suitable for this task.
Publisher
Walter de Gruyter GmbH
Subject
Biochemistry (medical),Clinical Biochemistry,General Medicine
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