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Record W4322729120 · doi:10.46613/congastro2022-75

TLP 744 ADENOMAS COLORRECTALES Y MAFLD: UN ESTUDIO TRANSVERSAL EN UNA COHORTE HISPANA DE CRIBADO

2022· article· es· W4322729120 on OpenAlexaff
Díaz La, Arab Jp

Bibliographic record

Venuenot available
Typearticle
Languagees
FieldMedicine
TopicColorectal and Anal Carcinomas
Canadian institutionsWestern UniversityLondon Health Sciences Centre
Fundersnot available
KeywordsTransversal (combinatorics)MedicineMathematics

Abstract

fetched live from OpenAlex

Introduccin: Recientemente, se ha propuesto una nueva definicin de la enfermedad por hgado graso [i.e., enfermedad del hgado graso asociada a disfuncin metablica (MAFLD, por sus siglas en ingls)]. La presencia de enfermedad del hgado graso se asocia a un mayor riesgo de presentar adenomas colorrectales (ACR). No existe informacin respecto a la asociacin de ACR en pacientes hispanos con MAFLD. Objetivo: evaluar la relacin entre MAFLD y el riesgo de CRA en una cohorte chilena. Mtodos: Se estudi a pacientes sometidos a una colonoscopia de tamizaje con estudio imagenolgico abdominal disponible. Se realiz un anlisis de regresin (uni/multivariado de los datos sociodemogrficos y clnicos. Resultados: Se incluyeron 895 pacientes; (42% eran hombres; edad media de 59,9 9,3 aos). El 37,8% (338) tenan ACR. Comparados con los sujetos controles, los pacientes con ACR eran predominantemente hombres (48,2% vs. 38,2%, P = 0,002), tenan mayor edad (61,6 8,7 aos vs. 58,9 9,5 aos, P < 0,001) y presentaban un mayor peso corporal [75 (66-88) kg vs. 72 (63-82,3) kg, P = 0,002]. El 56% de los pacientes tena esteatosis heptica y el 54,4% presentaba MAFLD. Se detectaron ms ACR en el grupo MAFLD (46,4% vs. 27,5% en controles, P < 0,001). MAFLD se asoci significativamente con la presencia de CRA (OR = 2,32; IC 95%: 1,68-3,19, P < 0,0001). No hubo diferencias respecto de la histologa de los ACR segn la presencia de MAFLD. Conclusin: MAFLD se asocia con un mayor riesgo de ACR. Financiado Fondecyt #1191145 a M.A.,

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.000

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 head0.009
GPT teacher head0.248
Teacher spread0.239 · 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 teacher head, not a consensus.

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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