The use of imaging studies and its association with surgical delays, costs and complications in patients with acute appendicitis: a population-based study in Ontario, Canada
Bibliographic record
Abstract
Appendicitis is commonly assessed with diagnostic imaging prior to intervention. The study objective was to describe practice patterns of diagnostic imaging for appendicitis and the associations with surgical delays, hospital costs, and complications. This was a population-based cohort study of patients with appendicitis between 2009 and 2015. Imaging was categorized into none, ultrasound, computed tomography (CT), or both. The outcomes were: 1) time from triage to surgery, 2) complication rate and 3) hospital costs. Logistic regression and hierarchical linear regression were used to estimate associations between imaging and outcomes. There were 50,369 study patients. Time to surgery was highest in patients requiring both CT and ultrasound (mean difference 5.0 h 95%CI 4.6–5.4) followed by patients requiring CT (2.7 h 95%CI 2.4–3.0) and ultrasound (mean difference 0.7 h, 95%CI 0.5–1.0), compared to no imaging. Hospital costs were highest in those with both ultrasound and CT ($256 95%CI $28–483) and CT alone ($234 95%CI $75–394), compared with no imaging. Complications were associated with the use of CT (OR 1.08 95%CI 1.00–1.17) and both CT and ultrasound (OR 1.21 95%CI 1.09–1.35) compared with no imaging, but not with ultrasound alone (OR 1.01 95%CI 0.93–1.09). This study demonstrated that type of diagnostic imaging is associated with delays to surgery, especially in those requiring CT scan. In addition, complications and hospital costs are increased in this group. Clinicians could consider ultrasound as the first imaging modality to facilitate more timely surgery and reduced costs.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".