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Record W6957894954 · doi:10.60692/2kgt6-hh154

Síndrome de Wilkie: una Causa Poco Común de Obstrucción Gastrointestinal, Asociada a Pérdida de Peso por Covid-19. Reporte de Caso

2023· article· es· W6957894954 on OpenAlexaff

Bibliographic record

VenueGreater South Information System · 2023
Typearticle
Languagees
FieldMedicine
TopicVascular anomalies and interventions
Canadian institutionsQueen's University
Fundersnot available
KeywordsCoronary diseaseCoronary heart diseaseClinical Practice

Abstract

fetched live from OpenAlex

El Síndrome de la arteria mesentérica superior (SAMS), también conocido como Síndrome de Wilkie, es una condición médica poco frecuente caracterizada por la constricción de la tercera porción del duodeno, que se produce debido a la compresión ejercida por la arteria mesentérica superior y la aorta abdominal, generalmente asociado a pérdida de peso significativa. Presentamos el caso de una mujer de 70 años con antecedentes de dos años de evolución de dolor abdominal esporádico, pérdida importante de peso, náuseas y vómitos. Después de una evaluación exhaustiva, incluida una tomografía computarizada, a la paciente se le diagnosticó síndrome de Wilkie. La paciente fue sometida a una gastroyeyunostomía como parte del tratamiento, la cual alivió los síntomas; sin embargo, el desarrollo posterior de anemia se atribuyó a la presencia de una úlcera anastomótica y una infección causada por Helicobacter pylori. Estas condiciones subyacentes se manejaron adecuadamente, lo que llevó a la resolución de la anemia. Nuestro caso planteó un desafío a los patrones demográficos habituales vinculados típicamente con esta condición médica, que afecta principalmente a personas más jóvenes. Esto resalta la importancia de tener en cuenta distintos factores relacionados con la edad para un diagnóstico más preciso.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.043
GPT teacher head0.291
Teacher spread0.248 · 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 designCase report
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

Citations0
Published2023
Admission routes1
Has abstractyes

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