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Record W2016658076 · doi:10.1532/lh96.04010

Complete Blood Count Reference Interval Diagrams Derived from NHANES III: Stratification by Age, Sex, and Race

2004· article· en· W2016658076 on OpenAlexaff
Calvino Cheng, Julie Y.H. Chan, George S. Cembrowski, Onno W. van Assendelft

Bibliographic record

VenueLaboratory Hematology · 2004
Typearticle
Languageen
FieldMedicine
TopicInflammatory Biomarkers in Disease Prognosis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineNational Health and Nutrition Examination SurveyRed blood cell distribution widthBody mass indexWhite blood cellHematocritMean platelet volumeMean corpuscular hemoglobin concentrationInternal medicineMean corpuscular volumeAbsolute neutrophil countComplete blood countPhysiologyPlateletPopulationNeutropenia

Abstract

fetched live from OpenAlex

BACKGROUND: Comprehensive, up-to-date "health-associated" reference interval studies of North American populations are uncommon. The third US National Health and Nutrition Examination Survey (NHANES III) was concluded in 1994 and yielded important reference interval data. OBJECTIVE: To obtain health-associated Coulter counter reference interval data from NHANES III according to age, sex, and race. METHODS: Of the 29,314 civilian noninstitutionalized US citizens who participated in NHANES III, approximately 25,000 had a complete blood count, red cell distribution width (RDW), platelet count, and automated white blood cell (WBC) differential determined on a Coulter S-Plus Jr. To determine health-associated reference intervals, we used the following exclusion criteria: pregnancy, breast feeding, obesity (body mass index [BMI] >40 and >35 for females and males, respectively), diastolic blood pressure >100 mm Hg, any smoking, any drinking of alcohol, recent treatment for anemia, creatinine level >2.5 mg/dL, glucose level >126 mg/dL, excessive thinness (BMI <8), recent surgery or hospitalization, or having antibodies to hepatitis viruses A, B, or C. The Coulter counter data (hemoglobin, hematocrit, red blood cell count, mean corpuscular volume (MCV), mean cell hemoglobin concentration (MCHC), MCH, WBC count, platelet count, granulocyte count, monocyte count, lymphocyte count, RDW, platelet distribution width, and mean platelet volume) were separated into 6 sex/racial categories (female non-Hispanic white, female non-Hispanic black, female Mexican American, male non-Hispanic white, male non-Hispanic black, and male Mexican American) and 9 age groupings (10-14, 14-18, 18-25, 25-35, 35-45, 45-55, 55-65, 65-75, and >75 years). RESULTS: There was a high exclusion rate; for example, of the 20,685 individuals with measured hemoglobin levels, 12,688 (61.3%) were excluded. Percentile estimates could be derived accurately for almost all of the female age/sex categories. A few of the male Mexican American and non-Hispanic black categories contained observations for ages 45 to 75 years. CONCLUSIONS: There are age-dependent trends for many of the tests, notably in RDW, MCMV, platelet count, and granulocyte and lymphocyte percentages. Sex-dependent changes involved hemoglobin values, and race-related trends centered around mononuclear and lymphocyte percentages, hematocrit, MCHC, MCH, and hemoglobin. This study reveals the potential for using data mining of large samples to yield potentially useful reference ranges.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.018
GPT teacher head0.264
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations227
Published2004
Admission routes1
Has abstractyes

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