Diagnosis and management of acute cholecystitis: a single-centre audit of guideline adherence and patient outcomes
Bibliographic record
Abstract
Background: The Tokyo Guidelines were published in 2007 and updated in 2013 and 2018, with recommendations for the diagnosis and management of acute cholecystitis. We assessed guideline adherence at our academic centre and its impact on patient outcomes. Methods: This is a retrospective chart review of patients with acute calculous cholecystitis who underwent cholecystectomy at our institution between November 2013 and March 2015. Severity of cholecystitis was graded retrospectively if it had not been documented preoperatively. Compliance with the Tokyo Guidelines' recommendations on antibiotic use and time to operation was recorded. Cholecystitis severity groups were compared statistically, and logistic regression was used to determine predictors of complications. Results: One hundred and fifty patients were included in the study. Of these, 104 patients were graded as having mild cholecystitis, 45 as having moderate cholecystitis, and 1 as having severe cholecystitis. Severity was not documented preoperatively for any patient. Compliance with antibiotic recommendations was poor (18.0%) and did not differ by cholecystitis severity (p = 0.90). Compliance with the recommendation on time to operation was 86.0%, with no between-group differences (p = 0.63); it improved when an acute care surgery team was involved (91.0% v. 76.0%, p = 0.025). On multivariable analysis, comorbidities (odds ratio [OR] 1.47, 95% confidence interval [CI] 1.19-1.85, p < 0.001) and conversion to laparotomy (OR 13.45, 95% CI 2.16-125.49, p = 0.01) predicted postoperative complications, while severity of cholecystitis, antibiotic compliance and time to operation had no effect. Conclusion: In this study, compliance with the Tokyo Guidelines was acceptable only for time to operation. Although the poor compliance with recommendations relating to documentation of severity grading and antibiotic use did not have a negative affect on patient outcomes, these recommendations are important because they facilitate appropriate antibiotic use and patient risk stratification.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".