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Valores de referência para exames laboratoriais de hemograma da população adulta brasileira: Pesquisa Nacional de Saúde

2019· article· pt· W2978635396 on OpenAlexaff
Luiz Gastão Rosenfeld, Déborah Carvalho Malta, Célia Landmann Szwarcwald, Maria Alice Martins Cuder, Cimar Azeredo Pereira, André William Figueiredo, Alanna Gomes da Silva, Ísis Eloah Machado, Wanessa Almeida da Silva, Gonzalo Vecina Neto, Jarbas Barbosa da Silva Júnior

Bibliographic record

VenueRevista Brasileira de Epidemiologia · 2019
Typearticle
Languagept
FieldMedicine
TopicClinical Laboratory Practices and Quality Control
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsMedicineHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe reference values for blood counts obtained from laboratory tests in the Brazilian adult population according to laboratory results from the National Health Survey (Pesquisa Nacional de Saúde - PNS), by gender, age group and skin color. METHODS: The initial sample consisted of 8,952 adults. To determine the reference values, individuals with prior diseases and outliers were excluded. Mean values, standard deviation and limits were stratified by gender, age group and skin color. RESULTS: For red blood cells, men presented a mean value of 5.0 million per mm3 (limits: 4.3-5.8) and women, 4.5 million per mm3 (limits: 3.9-5.1). Hemoglobin levels were higher among men with a mean of 14.9 g/dL (13.0-16.9), and in women, 13.2 g/dL (11.5-14.9). The mean number of white blood cells among men was 6.142/mm3 (2.843-9.440) and 6.426/mm3 (2.883-9.969) for women. Other parameters showed close values between the genders. Regarding age groups and skin color, mean values, standard deviation and limits of the exams presented small variations. CONCLUSION: Hematological reference values based on the national survey allow for the establishment of specific reference limits for gender, age and skin color. The results presented here may contribute to the establishment of better evidence and criteria for the care, diagnosis and treatment of diseases.

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)0.008
metaresearch head score (Gemma)0.026
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.090
GPT teacher head0.396
Teacher spread0.305 · 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

Citations42
Published2019
Admission routes1
Has abstractyes

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