Next-generation reference intervals for pediatric hematology
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Next-generation reference intervals for pediatric hematology. / Zierk, Jakob; Hirschmann, Johannes; Toddenroth, Dennis; Arzideh, Farhad; Haeckel, Rainer; Bertram, Alexander; Cario, Holger; Frühwald, Michael C; Groß, Hans-Jürgen; Groening, Arndt; Grützner, Stefanie; Gscheidmeier, Thomas; Hoff, Torsten; Hoffmann, Reinhard; Klauke, Rainer; Krebs, Alexander; Lichtinghagen, Ralf; Mühlenbrock-Lenter, Sabine; Neumann, Michael; Nöllke, Peter; Niemeyer, Charlotte M; Razum, Oliver; Ruf, Hans-Georg; Steigerwald, Udo; Streichert, Thomas; Torge, Antje; Rascher, Wolfgang; Prokosch, Hans-Ulrich; Rauh, Manfred; Metzler, Markus.
In: CLIN CHEM LAB MED, Vol. 57, No. 10, 25.09.2019, p. 1595-1607.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
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TY - JOUR
T1 - Next-generation reference intervals for pediatric hematology
AU - Zierk, Jakob
AU - Hirschmann, Johannes
AU - Toddenroth, Dennis
AU - Arzideh, Farhad
AU - Haeckel, Rainer
AU - Bertram, Alexander
AU - Cario, Holger
AU - Frühwald, Michael C
AU - Groß, Hans-Jürgen
AU - Groening, Arndt
AU - Grützner, Stefanie
AU - Gscheidmeier, Thomas
AU - Hoff, Torsten
AU - Hoffmann, Reinhard
AU - Klauke, Rainer
AU - Krebs, Alexander
AU - Lichtinghagen, Ralf
AU - Mühlenbrock-Lenter, Sabine
AU - Neumann, Michael
AU - Nöllke, Peter
AU - Niemeyer, Charlotte M
AU - Razum, Oliver
AU - Ruf, Hans-Georg
AU - Steigerwald, Udo
AU - Streichert, Thomas
AU - Torge, Antje
AU - Rascher, Wolfgang
AU - Prokosch, Hans-Ulrich
AU - Rauh, Manfred
AU - Metzler, Markus
PY - 2019/9/25
Y1 - 2019/9/25
N2 - 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.
AB - 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.
U2 - 10.1515/cclm-2018-1236
DO - 10.1515/cclm-2018-1236
M3 - SCORING: Journal article
C2 - 31005947
VL - 57
SP - 1595
EP - 1607
JO - CLIN CHEM LAB MED
JF - CLIN CHEM LAB MED
SN - 1434-6621
IS - 10
ER -
