Biochemical Marker Reference Values across Pediatric, Adult, and Geriatric Ages: Establishment of Robust Pediatric and Adult Reference Intervals on the Basis of the Canadian Health Measures Survey
Bibliographic record
Abstract
BACKGROUND: Biological covariates such as age and sex can markedly influence biochemical marker reference values, but no comprehensive study has examined such changes across pediatric, adult, and geriatric ages. The Canadian Health Measures Survey (CHMS) collected comprehensive nationwide health information and blood samples from children and adults in the household population and, in collaboration with the Canadian Laboratory Initiative on Pediatric Reference Intervals (CALIPER), examined biological changes in biochemical markers from pediatric to geriatric age, establishing a comprehensive reference interval database for routine disease biomarkers. METHODS: The CHMS collected health information, physical measurements, and biosamples (blood and urine) from approximately 12 000 Canadians aged 3-79 years and measured 24 biochemical markers with the Ortho Vitros 5600 FS analyzer or a manual microplate. By use of CLSI C28-A3 guidelines, we determined age- and sex-specific reference intervals, including corresponding 90% CIs, on the basis of specific exclusion criteria. RESULTS: Biochemical marker reference values exhibited dynamic changes from pediatric to geriatric age. Most biochemical markers required some combination of age and/or sex partitioning. Two or more age partitions were required for all analytes except bicarbonate, which remained constant throughout life. Additional sex partitioning was required for most biomarkers, except bicarbonate, total cholesterol, total protein, urine iodine, and potassium. CONCLUSIONS: Understanding the fluctuations in biochemical markers over a wide age range provides important insight into biological processes and facilitates clinical application of biochemical markers to monitor manifestation of various disease states. The CHMS-CALIPER collaboration addresses this important evidence gap and allows the establishment of robust pediatric and adult reference intervals.
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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 | 0.021 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".