Laboratory Information Systems
Bibliographic record
Abstract
BACKGROUND-AIMAge and sex-specific reference intervals (RIs) for laboratory tests are necessary for the correct interpretation of test results.Biochemical parameters can be affected by growth and development, requiring age-and sex-specific RIs.We aimed to determine RIs for liver function tests (LFTs) in Iranian infants and children for the first time. METHODSA total of 344 healthy pediatrics aged 3 days to 30 months old were recruited.Biochemical markers including AST, ALT, and ALP were measured using enzymatic methods and commercial kits on an Alpha classic-AT plus auto-analyzer (TS-Technology, Isfahan, Iran).The assay coefficients of variation (CV%) and mean were 0.05 % and 41.57mg/dL for AST, 0.04 % and 29.21 mg/dL for ALT, and 0.02 % and 96.91 mg/dL for ALP, respectively.RIs were determined by age with 90% confidence intervals using CLSI Ep28-A3 guidelines. RESULTSSex partitioning was not required for any of the hepatic markers evaluated.AST was the only analyte that did not demonstrate any statistically significant age-specific differences, demonstrating a constant reference value distribution across the age continuum.ALT and ALP demonstrated significantly elevated levels in infants 0-<5 months relative to the remainder of the age range, requiring partitioning based on the Harris and Boyd method.ALP levels remained stable from 5-<30 months, while ALT levels decreased more slowly and required two additional partitions (i.e., 5-<12 and 12-<30 months). CONCLUSIONSIn this cross-sectional study, age-specific RIs for some routine LFTs were determined to address critical gaps in RIs in early life.These novel data will help improve the clinical interpretation of biochemical test results in young Iranian neonates and children and can be of value to clinical laboratories with similar populations.
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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 | 0.007 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.242 | 0.198 |
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".