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Record W3159207886 · doi:10.1515/cclm-2021-0050

Pediatric reference intervals for endocrine markers and fertility hormones in healthy children and adolescents on the Siemens Healthineers Atellica immunoassay system

2021· article· en· W3159207886 on OpenAlexafffund
Mary Kathryn Bohn, Paul S. Horn, Donna League, Paul E. Steele, Alexandra Hall, Khosrow Adeli

Bibliographic record

VenueClinical Chemistry and Laboratory Medicine (CCLM) · 2021
Typearticle
Languageen
FieldMedicine
TopicClinical Laboratory Practices and Quality Control
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsMedicinePhysiologyLuteinizing hormoneHormoneImmunoassayDehydroepiandrosterone sulfateTestosterone (patch)Internal medicineEndocrinologyAndrogenImmunologyAntibody

Abstract

fetched live from OpenAlex

OBJECTIVES: Rapid development in childhood and adolescence combined with lack of immunoassay standardization necessitates the establishment of age-, sex-, and assay-specific reference intervals for immunochemical markers. This study established reference intervals for 11 immunoassays on the new Siemens Healthineers Atellica® IM Analyzer in the healthy CALIPER cohort. METHODS: A total of 600 healthy participants (birth to 18 years) were recruited from the community, and serum samples were collected with informed consent. After sample analysis, age- and sex-specific differences were assessed, and outliers were removed. Reference intervals were established using the robust method (40-<120 participants) or nonparametric method (≥120 participants). RESULTS: Of the 11 immunoassays studied, nine required age partitioning (i.e., dehydroepiandrosterone-sulfate, estradiol, ferritin, folate, follicle-stimulating hormone, luteinizing hormone, progesterone, testosterone, vitamin B12), and seven required sex partitioning. Free thyroxine and thyroid-stimulating hormone demonstrated no significant age- and/or sex-specific differences. CONCLUSIONS: Overall, the age- and sex-specific trends observed closely mirrored those previously reported by CALIPER on other platforms as well as other internationally recognized studies. However, established lower and upper limits demonstrated some discrepancies between published values from healthy cohorts on alternate analytical systems, highlighting differences between manufacturers and the need for platform-specific reference intervals for informed pediatric clinical decision-making.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.058
GPT teacher head0.383
Teacher spread0.325 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2021
Admission routes2
Has abstractyes

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