Acute cholecystitis management at a tertiary care center: are we following current guidelines?
Bibliographic record
Abstract
Abstract Purpose After the Tokyo 2018 guidelines (TG2018) were published, evidence from the 2018 CHOCOLATE RCT supported early cholecystectomy for acute cholecystitis (AC), even in high-risk patients. This study aims to investigate AC management at our tertiary care center in the years following these publications. Methods A retrospective cohort study was performed of patients admitted from 2018–2023. AC severity was graded using TG2018 definitions. Comorbidities were summarized using Charlson Comorbidity Index (CCI) and frailty using the 5-item modified Frailty Index (5mFI). Compliance with TG2018 recommendations for management strategy was investigated. Outcomes were compared between patients who underwent surgery versus NOM. Subset analysis based on patients’ age, frailty, and comorbidities was performed. Results Among 642 AC patients, 57% underwent cholecystectomy and 43% NOM (22% percutaneous cholecystostomy, 21% antibiotics only). NOM patients had greater length of stay (LOS), complications, deaths, readmissions, and discharge to nursing/rehab versus surgery patients. In 70% of patients managed non-operatively, TG2018 were not followed. Patients managed non-operatively despite TG2018 were more likely to undergo delayed cholecystectomy compared to those in whom guidelines were followed (17% vs 4%). In subset analysis, healthy octogenarians were significantly less likely to be managed according to TG2018 (9.4%); patients undergoing surgery had a trend towards shorter LOS (3.1 vs 4.8 days) than those managed non-operatively but no difference in other outcomes. Conclusion Most patients undergoing NOM could potentially undergo cholecystectomy if guidelines are considered. A more objective approach to risk assessment may optimize patient selection and outcomes.
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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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".