Complex Biological Pattern of Fertility Hormones in Children and Adolescents: A Study of Healthy Children from the CALIPER Cohort and Establishment of Pediatric Reference Intervals
Bibliographic record
Abstract
BACKGROUND: Pediatric endocrinopathies are commonly diagnosed and monitored by measuring hormones of the hypothalamic-pituitary-gonadal axis. Because growth and development can markedly influence normal circulating concentrations of fertility hormones, accurate reference intervals established on the basis of a healthy, nonhospitalized pediatric population and that reflect age-, gender-, and pubertal stage-specific changes are essential for test result interpretation. METHODS: Healthy children and adolescents (n = 1234) were recruited from a multiethnic population as part of the CALIPER study. After written informed parental consent was obtained, participants filled out a questionnaire including demographic and pubertal development information (assessed by self-reported Tanner stage) and provided a blood sample. We measured 7 fertility hormones including estradiol, testosterone (second generation), progesterone, sex hormone-binding globulin, prolactin, follicle-stimulating hormone, and luteinizing hormone by use of the Abbott Architect i2000 analyzer. We then used these data to calculate age-, gender-, and Tanner stage-specific reference intervals according to Clinical Laboratory Standards Institute C28-A3 guidelines. RESULTS: We observed a complex pattern of change in each analyte concentration from the neonatal period to adolescence. Consequently, many age and sex partitions were required to cover the changes in most fertility hormones over this period. An exception to this was prolactin, for which no sex partition and only 3 age partitions were necessary. CONCLUSIONS: This comprehensive database of pediatric reference intervals for fertility hormones will be of global benefit and should lead to improved diagnosis of pediatric endocrinopathies. The new database will need to be validated in local populations and for other immunoassay platforms as recommended by the Clinical Laboratory Standards Institute.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".