Pediatric reference value distributions and covariate-stratified reference intervals for 29 endocrine and special chemistry biomarkers on the Beckman Coulter Immunoassay Systems: a CALIPER study of healthy community children
Bibliographic record
Abstract
BACKGROUND: The CALIPER program is a national research initiative aimed at closing the gaps in pediatric reference intervals. CALIPER previously reported reference intervals for endocrine and special chemistry markers on Abbott immunoassays. We now report new pediatric reference intervals for immunoassays on the Beckman Coulter Immunoassay Systems and assess platform-specific differences in reference values. METHODS: A total of 711 healthy children and adolescents from birth to <19 years of age were recruited from the community. Serum samples were collected for measurement of 29 biomarkers on the Beckman Coulter Immunoassay Systems. Statistically relevant age and/or gender-based partitions were determined, outliers removed, and reference intervals calculated in accordance with Clinical and Laboratory Standards Institute (CLSI) EP28-A3c guidelines. RESULTS: Complex profiles were observed for all 29 analytes, necessitating unique age and/or sex-specific partitions. Overall, changes in analyte concentrations observed over the course of development were similar to trends previously reported, and are consistent with biochemical and physiological changes that occur during childhood. Marked differences were observed for some assays including progesterone, luteinizing hormone and follicle-stimulating hormone where reference intervals were higher than those reported on Abbott immunoassays and parathyroid hormone where intervals were lower. CONCLUSIONS: This study highlights the importance of determining reference intervals specific for each analytical platform. The CALIPER Pediatric Reference Interval database will enable accurate diagnosis and laboratory assessment of children monitored by Beckman Coulter Immunoassay Systems in health care institutions worldwide. These reference intervals must however be validated by individual labs for the local pediatric population as recommended by CLSI.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".