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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.

Background Overcoming the COVID-19 crisis requires new ideas and strategies for online communication of personal medical information and patient empowerment. Rapid testing of a large number of subjects is essential for monitoring and delaying the spread of SARS-CoV-2 in order to mitigate the pandemic’s consequences. People who do not know that they are infected may not stay in quarantine and, thus, risk infecting others. Unfortunately, the massive number of COVID-19 tests performed is challenging for both laboratories and the units that conduct throat swabs and communicate the results. Objective The goal of this study was to reduce the communication burden for health care professionals. We developed a secure and easy-to-use tracking system to report COVID-19 test results online that is simple to understand for the tested subjects as soon as these results become available. Instead of personal calls, the system updates the status and the results of the tests automatically. This aims to reduce the delay when informing testees about their results and, consequently, to slow down the virus spread. Methods The application in this study draws on an existing tracking tool. With this open-source and browser-based online tracking system, we aim to minimize the time required to inform the tested person and the testing units (eg, hospitals or the public health care system). The system can be integrated into the clinical workflow with very modest effort and avoids excessive load to telephone hotlines. Results The test statuses and results are published on a secured webpage, enabling regular status checks by patients; status checks are performed without the use of smartphones, which has some importance, as smartphone usage diminishes with age. Stress tests and statistics show the performance of our software. CTest is currently running at two university hospitals in Germany—University Hospital Ulm and University Hospital Tübingen—with thousands of tests being performed each week. Results show a mean number of 10 (SD 2.8) views per testee. Conclusions CTest runs independently of existing infrastructures, aims at straightforward integration, and aims for the safe transmission of information. The system is easy to use for testees. QR (Quick Response) code links allow for quick access to the test results. The mean number of views per entry indicates a reduced amount of time for both health care professionals and testees. The system is quite generic and can be extended and adapted to other communication tasks.

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.