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Classificação de gravidade na pancreatite aguda

2013· article· pt· W2060037926 on OpenAlexaff
Tércio De Campos, José Gustavo Parreira, José Cesar Assef, Sandro Rizoli, Barto Nascimento, Gustavo Pereira Fraga

Bibliographic record

VenueRevista do Colégio Brasileiro de Cirurgiões · 2013
Typearticle
Languagept
FieldMedicine
TopicPancreatitis Pathology and Treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAcute pancreatitisMedicineIntensive care medicinePancreatitisSeverity of illnessInternal medicine

Abstract

fetched live from OpenAlex

Based on the Atlanta Classification, acute pancreatitis is classified according to its severity in either mild or severe acute pancreatitis. In recent years, several issues regarding acute pancreatitis have been discussed in the literature. These issues include how many categories of severity should be considered; whether or not a patient with organ failure holds similar holds severity of disease and prognosis of a patient with infected necrosis; the role of transient organ failure; and how to evaluate organ failure. The"Evidence-based Telemedicine - Trauma and Acute Care Surgery" (EBT-TACS) conducted a review of the recent literature on the topic, and critically appraised its most relevant pieces of evidence.. The articles discussed suggested classifying the severity of acute pancreatitis in three or four categories, rather than mild or severe only, and addressed which is the best score to assess organ failure. The following recommendations were proposed: (1) Acute pancreatitis should be classified into four categories: mild, moderate, severe and critical, which allows a better determination of the characteristics of patients, (2) Evaluation of organ failure with a severity score that preferably evaluate directly each organ failure, such as the SOFA and MODS (Marshall). The SOFA seems to have greater accuracy, but the MODS has better applicability due to its ease of use.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient 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 score0.031
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.005

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 head0.022
GPT teacher head0.284
Teacher spread0.262 · 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

Citations9
Published2013
Admission routes1
Has abstractyes

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Same venueRevista do Colégio Brasileiro de CirurgiõesSame topicPancreatitis Pathology and TreatmentFrench-language works237,207