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Record W3138914596 · doi:10.1002/jhbp.943

The “Two‐Step” approach for classifying the severity of acute pancreatitis: A retrospective study

2021· article· en· W3138914596 on OpenAlexaff
Yun Zhang, Cheng Zhang, Wenqiao Yu, Zhi‐En Wang, Jian Zhang, Tingbo Liang

Bibliographic record

VenueJournal of Hepato-Biliary-Pancreatic Sciences · 2021
Typearticle
Languageen
FieldMedicine
TopicPancreatitis Pathology and Treatment
Canadian institutionsPancreas Centre (Canada)
FundersNational Natural Science Foundation of China
KeywordsAcute pancreatitisMedicineRetrospective cohort studyIntensive care unitdBcSOFA scoreIntensive care medicineInternal medicineComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: The Revised Atlanta Classification (RAC) and Determinant-Based Classification (DBC) are currently two widely adopted systems for evaluating the severity of acute pancreatitis (AP). This study aimed to overcome the inaccuracies and limitations that existed in them. METHODS: We retrospectively analyzed 298 patients with AP. The "Two-Step" approach was divided into an early organ failure (OF) assessment: (I) none, (II) transient, (III) single persistent, and (IV) multiple persistent; and a later local complications assessment: (A) none, (B) sterile, and (C) infectious. Patients with AP who died before the second step were classified into category X. The "Two-Step" approach was then compared to the RAC and DBC. RESULTS: As the patients' grades increased (I to IV), organ support treatment rates, intensive care unit lengths of stay, and mortalities increased. Invasive intervention rates displayed increasing trends with local complications aggravated (A to C). Patients in category X were older and had higher Marshall scores with the highest grades of severity. CONCLUSIONS: By combining the early OF grades and the late local complications, the "Two-Step" approach represents an accurate classification system required for stratified studies of AP, and introduces the category X as the severest forms of AP.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.036
Threshold uncertainty score0.769

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.035
GPT teacher head0.325
Teacher spread0.291 · 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.

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

Citations4
Published2021
Admission routes1
Has abstractyes

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Same venueJournal of Hepato-Biliary-Pancreatic SciencesSame topicPancreatitis Pathology and TreatmentFrench-language works237,207