Evolving Practice Patterns in the Management of Acute Colonic Diverticulitis
Bibliographic record
Abstract
BACKGROUND: There is increasing evidence to support the use of percutaneous abscess drainage, laparoscopy, and primary anastomosis in managing acute diverticulitis. OBJECTIVE: The aim of this study was to evaluate how practices have evolved and to determine the effects on clinical outcomes. DESIGN: This is a population-based retrospective cohort study using administrative discharge data. SETTING: This study was conducted in Ontario, Canada. PATIENTS: All patients had been hospitalized for a first episode of acute diverticulitis (2002-2012). MAIN OUTCOME MEASURES: Temporal changes in treatment strategies and outcomes were evaluated by using the Cochran-Armitage test for trends. Multivariable logistic regression with generalized estimating equations was used to test for trends while adjusting for patient characteristics. RESULTS: There were 18,543 patients hospitalized with a first episode of diverticulitis, median age 60 years (interquartile range, 48-74). From 2002 to 2012, there was an increase in the proportion of patients admitted with complicated disease (abscess, perforation), 32% to 38%, yet a smaller proportion underwent urgent operation, 28% to 16% (all p < 0.001). The use of percutaneous drainage increased from 1.9% of admissions in 2002 to 3.3% in 2012 (p < 0.001). After adjusting for changes in patient and disease characteristics over time, the odds of urgent operation decreased by 0.87 per annum (95% CI, 0.85-0.89). In those undergoing urgent surgery (n = 3873), the use of laparoscopy increased (9% to 18%, p <0.001), whereas the use of the Hartmann procedure remained unchanged (64%). During this time, in-hospital mortality decreased (2.7% to 1.9%), as did the median length of stay (5 days, interquartile range, 3-9; to 3 days, interquartile range, 2-6; p <0.001). LIMITATIONS: There is the potential for residual confounding, because clinical parameters available for risk adjustment were limited to fields existing within administrative data. CONCLUSIONS: There has been an increase in the use of nonoperative and minimally invasive strategies in treating patients with a first episode of acute diverticulitis. However, the Hartmann procedure remains the most frequently used urgent operative approach. Mortality and length of stay have improved during this time.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".