Reference intervals for hemoglobin and mean corpuscular volume in an ethnically diverse community sample of Canadian children 2 to 36 months
Bibliographic record
Abstract
OBJECTIVE: To establish reference intervals for hemoglobin and mean corpuscular volume (MCV) in an ethnically diverse community sample of Canadian children 36 months and younger. METHODS: We collected blood samples from young children at scheduled primary care health supervision visits at 2 weeks, 2, 4, 6, 9, 12, 15, 18, 24, and 36 months of age. Samples were analyzed on the Sysmex XN-9000 Hematology Analyzer. We followed the Clinical and Laboratory Standards Institute guidelines in our analysis. Data were partitioned by sex and also combined. We considered large age partitions (3 and 6 months) as well as monthly partitions. Reference intervals (lower and upper limits) and 90% confidence intervals were calculated. RESULTS: Data from 2106 children were included. The age range was 2 weeks to 36 months, 46% were female, 48% were European and 23% were of mixed ethnicity. For hemoglobin, from 2 to 36 months of age, we found a wide reference interval and the 90% confidence intervals indicated little difference across age groups or according to sex. For MCV, from 2 to 7 months of age there was considerable decrease in the reference interval, which was lowest during the second year of life, followed by a slight increase in the last months of the third year of life. CONCLUSION: These findings suggest adoption of a single hemoglobin reference interval for children 2-36 months of age. Further studies in children under 4 months of age are needed. TRIAL REGISTRATION: TARGet Kids! cohort is registered at ClinicalTrials.gov. www.clinicaltrials.gov . Identifier: NCT01869530 .
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 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".