Search

Capillary sampling of blood counts is a well-established alternative to venipuncture in paediatrics. However, the sampling method has to be considered when interpreting test results, as measurements differ. Ethical and practical considerations prevent simultaneous venous and capillary sample acquisition in comprehensive paediatric cohorts that span all ages for the purpose of a direct method comparison, resulting in uncertainty regarding the interpretation of capillary test results.We applied a data mining method to calculate the differences between capillary and venous blood count analytes using laboratory data collected during patient care. We examined 486 401 blood counts performed between 2010 and 2017 in two German paediatric tertiary care centers in children from birth to 18 years analysed on SYSMEX XE-2100 and SYSMEX XE-5000 devices, and analysed the differences between capillary and venous test results in 15 218 paired samples performed within 24 h.We identified the mean systematic differences between capillary and venous (capillary-venous) test results for haemoglobin (+6.5 g/L), haematocrit (+2.38%), platelet count (-7.01 × 10Our results improve guidance regarding the interpretation of capillary test results for children of all ages and in both physiological and pathological ranges.

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.

Background: Interpretation of alkaline phosphatase activity in children is challenging due to extensive changes with growth and puberty leading to distinct sex- and age-specific dynamics. Continuous percentile charts from birth to adulthood allow accurate consideration of these dynamics and seem reasonable for an analyte as closely linked to growth as alkaline phosphatase. However, the ethical and practical challenges unique to pediatric reference intervals have restricted the creation of such percentile charts, resulting in limitations when clinical decisions are based on alkaline phosphatase activity. Methods: We applied an indirect method to generate percentile charts for alkaline phosphatase activity using clinical laboratory data collected during the clinical care of patients. A total of 361,405 samples from 124,440 patients from six German tertiary care centers and one German laboratory service provider measured between January 2004 and June 2015 were analyzed. Measurement of alkaline phosphatase activity was performed on Roche Cobas analyzers using the IFCC’s photometric method. Results: We created percentile charts for alkaline phosphatase activity in girls and boys from birth to 18 years which can be used as reference intervals. Additionally, data tables of age- and sex-specific percentile values allow the incorporation of these results into laboratory information systems. Conclusions: The percentile charts provided enable the appropriate differential diagnosis of changes in alkaline phosphatase activity due to disease and changes due to physiological development. After local validation, integration of the provided percentile charts into result reporting facilitates precise assessment of alkaline phosphatase dynamics in pediatrics.

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.