Reference intervals for thyroid biomarkers to enhance the assessment of thyroid status in childhood and adolescence
Bibliographic record
Abstract
OBJECTIVES: The determination of assay-dependent upper and lower reference limits (URL, LRL) of free triiodothyronine (FT3), free thyroxine (FT4), and thyroid stimulating hormone (TSH) during childhood and adolescence, is challenging. METHODS: Thyroid hormones were measured via the Abbott Alinity system in 502 euthyroid children partitioned in the following age groups: ≤2, 2.1-10, and 10.1-18 years. The 97.5th and 2.5th percentiles (URL and LRL) were derived according to CLSI EP28- A3c guidelines. Quantile regression models were used to assess: (a) 90% confidence intervals of the URL and LRL, (b) the effect of age on URL and LRL within each age class and on overall age range, (c) the difference between the URLs and LRLs estimated for each age partition with an estimate of the confidence interval divided by the reference interval being derived (CI/RI). RESULTS: The CI/RI for the LRLs are smaller as compared to the URLs, except for FT4 for the 2.1-10 years age group. Considering the CI/RI and the overlap between CIs across the three age groups, one single LRL might be considered for TSH, FT3 and FT4 between 0 and 18 years. However, for the URL, there was a noticeable decrease in the URL over the 3 age groups for all three biomarkers, with there being no overlap in CIs for the URL between the ≤2 vs. the 10.1-19 years age groups. CONCLUSIONS: A common LRL for TSH, FT4 and FT3 for patients aged ≤18 years may be utilized when these biomarkers are measured with the Alinity system. For the URLs the use of age-specific URLs for these biomarkers is recommended.
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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 | 0.018 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".