Pediatric Reference Intervals for Transferrin Saturation in the CALIPER Cohort of Healthy Children and Adolescents.
Bibliographic record
Abstract
BACKGROUND: Transferrin saturation reference intervals specific for age and sex have not been previously reported for the pediatric population. The reference values for transferrin saturation have been previously reported to be lower in children compared to adults, caused by a combination of low serum iron and high serum transferrin levels in children, warranting specific reference intervals. Here we use the original iron and transferrin data from the CALIPER cohort to establish age- and sex-specific pediatric reference intervals for transferrin saturation. METHODS: Iron and transferrin concentrations were measured in serum samples from the CALIPER cohort of healthy children and adolescents on the Abbott Architect c8000. Transferrin saturation was subsequently calculated and statistically relevant age- and sex-partitions were determined. After removing outliers, age- and sex-specific reference intervals with corresponding 90% confidence intervals were calculated using CLSI C28-A3 guidelines. RESULTS: Transferrin saturation required 3 separate age partitions, with an additional sex partition for 14-<19 year olds. Transferrin saturation was more variable during the first year of life, evident by a wider reference interval, which subsequently narrowed at one year until adolescence. Upon adolescence, a sex difference was apparent with females having lower percent transferrin saturation than males. CONCLUSIONS: Age- and sex-specific pediatric reference intervals for transferrin saturation were established based on a large cohort of healthy pediatric subjects. Transference studies suggest that these intervals established using Abbott assays are comparable to those on Beckman, Ortho, Roche, and Siemens assays. Individual laboratories should however verify these reference intervals for their individual instrument and local population as per CLSI guidelines.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".