Race‐specific WBC and neutrophil count reference intervals
Bibliographic record
Abstract
Healthy African Americans are known to have reduced white blood cell counts (WBC) and absolute neutrophil counts (ANC) compared with European Americans, with little agreement about the levels in reference intervals. The objective is to establish race-specific reference intervals for WBC and ANC using US National Health and Nutrition Examination Survey (NHANES) of 2000-2003. A total of 14,184 civilian noninstitutionalized US citizens participated in NHANES 2000-2003 had complete blood count, red cell distribution width, platelet count and automated WBC differential determined on a Coulter MAXM. The exclusion criteria were used: ferritin <12 ng/ml, pregnancy, body mass index >30, diastolic blood pressure >100 mm Hg, creatinine >2.5 mg/dl, glucose >126 mg/dl. Data were separated into six sex/race categories: female non-Hispanic white, non-Hispanic black (NHBF)], Mexican American; male non-Hispanic white, non-Hispanic black (NHBM), Mexican American and two age groupings (12-18 and >18 years). NHB 2.5-97.5 percentile WBC and (ANC) limits follow (units: × 10⁹ /l): NHBM, ages 12-18: 3.2-9.3 (1.0-6.2); NHBF, ages 12-18: 3.7-10.1 (1.2-6.6); adult NHBM: 3.1-9.9 (1.3-6.6); adult NHBF: 3.4-11 (1.4-7.5). NHB limits are significantly lower than the NHW and MA limits. In most US healthcare organizations, insufficient agreement exists because of large differences in reference intervals for different ethnicities. In areas with peoples of African descent (>10--20%), race-specific WBC and ANC reference intervals must be provided for proper diagnosis and clinical research.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".