The “Two‐Step” approach for classifying the severity of acute pancreatitis: A retrospective study
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".