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Objectives: Assessment of children's laboratory test results requires consideration of the extensive changes that occur during physiological development and result in pronounced sex- and age-specific dynamics in many biochemical analytes. Pediatric reference intervals have to account for these dynamics, but ethical and practical challenges limit the availability of appropriate pediatric reference intervals that cover children from birth to adulthood. We have therefore initiated the multi-center data-driven PEDREF project (Next-Generation Pediatric Reference Intervals) to create pediatric reference intervals using data from laboratory information systems., Methods: We analyzed laboratory test results from 638,683 patients (217,883-982,548 samples per analyte, a median of 603,745 test results per analyte, and 10,298,067 test results in total) performed during patient care in 13 German centers. Test results from children with repeat measurements were discarded, and we estimated the distribution of physiological test results using a validated statistical approach ( kosmic )., Results: We report continuous pediatric reference intervals and percentile charts for alanine transaminase, aspartate transaminase, lactate dehydrogenase, alkaline phosphatase, γ-glutamyl-transferase, total protein, albumin, creatinine, urea, sodium, potassium, calcium, chloride, anorganic phosphate, and magnesium. Reference intervals are provided as tables and fractional polynomial functions (i.e., mathematical equations) that can be integrated into laboratory information systems. Additionally, Z -scores and percentiles enable the normalization of test results by age and sex to facilitate their interpretation across age groups., Conclusions: The provided reference intervals and percentile charts enable precise assessment of laboratory test results in children from birth to adulthood. Our findings highlight the pronounced dynamics in many biochemical analytes in neonates, which require particular consideration in reference intervals to support clinical decision making most effectively., (© 2021 Walter de Gruyter GmbH, Berlin/Boston.)

Background Interpreting hematology analytes in children is challenging due to the extensive changes in hematopoiesis that accompany physiological development and lead to pronounced sex- and age-specific dynamics. Continuous percentile charts from birth to adulthood allow accurate consideration of these dynamics. However, the ethical and practical challenges unique to pediatric reference intervals have restricted the creation of such percentile charts, and limitations in current approaches to laboratory test result displays restrict their use when guiding clinical decisions. Methods We employed an improved data-driven approach to create percentile charts from laboratory data collected during patient care in 10 German centers (9,576,910 samples from 358,292 patients, 412,905-1,278,987 samples per analyte). We demonstrate visualization of hematology test results using percentile charts and z-scores (www.pedref.org/hematology) and assess the potential of percentiles and z-scores to support diagnosis of different hematological diseases. Results We created percentile charts for hemoglobin, hematocrit, red cell indices, red cell count, red cell distribution width, white cell count and platelet count in girls and boys from birth to 18 years of age. Comparison of pediatricians evaluating complex clinical scenarios using percentile charts versus conventional/tabular representations shows that percentile charts can enhance physician assessment in selected example cases. Age-specific percentiles and z-scores, compared with absolute test results, improve the identification of children with blood count abnormalities and the discrimination between different hematological diseases. Conclusions The provided reference intervals enable precise assessment of pediatric hematology test results. Representation of test results using percentiles and z-scores facilitates their interpretation and demonstrates the potential of digital approaches to improve clinical decision-making.

Background Conventional establishment of reference intervals for hematological analytes is challenging due to the need to recruit healthy persons. Indirect methods address this by deriving reference intervals from clinical laboratory databases which contain large datasets of both physiological and pathological test results. Methods We used the "Reference Limit Estimator" (RLE) to establish reference intervals for common hematology analytes in adults aged 18-60 years. One hundred and ninety-five samples from 44,519 patients, measured on two different devices in a tertiary care center were analyzed. We examined the influence of patient cohorts with an increasing proportion of abnormal test results, compared sample selection strategies, explored inter-device differences, and analyzed the stability of reference intervals in simulated datasets with varying overlap of pathological and physiological test results. Results Reference intervals for hemoglobin, hematocrit, red cell count and platelet count remained stable, even if large numbers of pathological samples were included. Reference intervals for red cell indices, red cell distribution width and leukocyte count were sufficiently stable, if patient cohorts with the highest fraction of pathological samples were excluded. In simulated datasets, estimated reference limits shifted, if the pathological dataset contributed more than 15%-20% of total samples and approximated the physiological distribution. Advanced sample selection techniques did not improve the algorithm's performance. Inter-device differences were small except for red cell distribution width. Conclusions The RLE is well-suited to create reference intervals from clinical laboratory databases even in the challenging setting of a adult tertiary care center. The procedure can be used as a complement for reference interval determination where conventional approaches are limited.