Indirectly determined reference intervals for automated white blood cell differentials of pediatric patients in Berlin and Brandenburg.

OBJECTIVES: Establishing direct reference intervals for pediatric patients is a costly, challenging, and time-consuming enterprise. Indirectly established reference intervals can help to ameliorate this situation. It was our objective to establish population-specific reference intervals for automated white blood cell differentials via data mining and non-parametric percentile method. METHODS: Blood counts and automated white blood cell differentials of patients aged 0 days to 18 years, performed from the 1st of January 2018 until the 30th of June 2022, were identified in our laboratory information system. Reference intervals were established in accordance with IFCC and CLSI recommendations as well as the propositions by Haeckel et al. RESULTS: Initially, 47,173 blood counts on our SYSMEX XN-9000 were identified. 11,707 data sets were excluded, leaving 35,466 sample sets for analysis. Of these, 17,616 contained automated white blood cell differentials. Due to insufficient patient numbers, no reference intervals for automated white blood cell differentials could be established for children aged <7 months. In comparison to the corresponding reference intervals published by Herklotz et al., reference intervals determined by us showed relevant differences throughout all age groups. CONCLUSIONS: The combination of non-parametric percentile method and the propositions by Haeckel et al. utilizing conscientious data mining appears to be potent alternative to direct reference interval determination.

Indirectly determined hematology reference intervals for pediatric patients in Berlin and Brandenburg.

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.