Complex biological patterns of hematology parameters in childhood necessitating age‐ and sex‐specific reference intervals for evidence‐based clinical interpretation
Bibliographic record
Abstract
INTRODUCTION: Hematology laboratory parameters are among the most routinely ordered tests in support of adult and pediatric care. However, appropriate interpretation of test results has been a challenge in pediatrics since accurate and up-to-date reference intervals that reflect the dynamic physiological changes associated with growth and development have not been available. Critical gaps continue to exist in pediatric hematology reference intervals for modern laboratory platforms. To address this gap, this study establishes age- and sex-specific reference intervals for 25 hematology parameters in the CALIPER cohort of healthy children and adolescents using a common platform, the Sysmex XN-3000 analytical system. METHODS: Fresh whole blood samples collected from a total of 641 healthy children and adolescents (birth to <21 years) with informed consent were analyzed for 25 hematological parameters on the Sysmex XN-3000 Hematology Analyzer. Age- and sex-specific reference standards were calculated based on Clinical and Laboratory Standards Institute guidelines. RESULTS: Of the 25 analytes assessed, 19 required age-partitioning and seven required sex-partitioning (ie, red blood cell count, hemoglobin, hematocrit, mean corpuscular volume, red blood cell distribution width-SD, red blood cell distribution width-CV, and monocyte percentage). Age- and sex-specific differences mostly coincided with the onset of puberty. CONCLUSION: This study establishes a comprehensive database of pediatric reference intervals for hematology parameters in the CALIPER cohort using the widely used Sysmex XN-3000 analytical platform. These data highlight the dynamic hematological profile observed in healthy children and adolescents and the need for reference interval stratification by age and sex.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".