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Circunferência da cintura e relação cintura/estatura: úteis para identificar risco metabólico em adolescentes do sexo feminino?

2011· article· pt· W2053580596 on OpenAlexaff
Patrícia Feliciano Pereira, Hiara Miguel Stanciola Serrano, Gisele Queiroz Carvalho, Joel Alves Lamounier, Maria do Carmo Gouveia Pelúzio, Sylvia do Carmo Castro Franceschini, Sílvia Eloiza Priore

Bibliographic record

VenueRevista Paulista de Pediatria · 2011
Typearticle
Languagept
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsNutrasource
Fundersnot available
KeywordsMedicineWaistAbdominal obesityInsulin resistanceGynecologyInternal medicineObesity

Abstract

fetched live from OpenAlex

OBJETIVO: Avaliar se a medida da circunferência da cintura e a relação cintura/estatura (RCE) são preditoras de fatores de risco cardiovasculares em adolescentes do sexo feminino. MÉTODOS: Avaliaram-se 113 adolescentes de 14 a 19 anos quanto à antropometria (peso, estatura e circunferência da cintura), parâmetros bioquímicos e clínicos (colesterol total, LDL-C, HDL-C, triglicerídeos, glicemia de jejum, insulina, homeostasis model assessment to assess insulin resistance - HOMA-IR, leptina, homocisteína e pressão arterial). Considerou-se como ponto de corte de obesidade abdominal valores de cintura e RCE>percentil 90. RESULTADOS: As adolescentes com obesidade abdominal apresentaram valores significantemente maiores de triglicerídeos (exceto para a RCE), insulina, HOMA-IR, leptina, pressão arterial sistólica e diastólica; o HDL-C foi mais baixo no grupo com cintura >percentil 90, porém sem significância estatística (p=0,052). CONCLUSÕES: O presente estudo demonstrou que a cintura e a RCE são medidas úteis para identificar adolescentes do sexo feminino com maior risco cardiovascular; contudo, a circunferência da cintura, isoladamente, apresentou melhor desempenho.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.150
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0030.004

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 head0.050
GPT teacher head0.293
Teacher spread0.243 · 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; both teacher heads agree on what is shown here.

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

Citations29
Published2011
Admission routes1
Has abstractyes

Explore more

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