Multicentre Analysis of Cost, Uptake and Safety of Canadian Multidisciplinary Pancreatic Cyst Guidelines
Bibliographic record
Abstract
Background: Pancreatic cystic lesions (PCLs) are common, with several guidelines providing surveillance recommendations. The Canadian Association of Radiologists published surveillance guidelines (CARGs) intended to provide simplified, cost-effective and safe recommendations. This study aimed to evaluate cost savings of CARGs compared to other North American guidelines including American Gastroenterology Association guidelines (AGAG) and American College of Radiology guidelines (ACRG), and to evaluate CARG safety and uptake. Methods: This is a multicentre retrospective study evaluating adults with PCL from a single health zone. MRIs completed from September 2018-2019, one year after local CARG guideline implementation, were reviewed to identify PCLs. All imaging following 3-4 years of CARG implementation was reviewed to evaluate true costs, missed malignancy and guideline uptake. Modelling, including MRI and consultation, predicted and compared costs associated with surveillance based on CARGs, AGAGs and ACRGs. Results: 6698 abdominal MRIs were reviewed with 1001 (14.9%) identifying PCL. Application of CARGs over 3.1 years demonstrated a >70% cost reduction compared to other guidelines. Similarly, the modelled cost of surveillance for 10-years for each guideline was $516,183, $1,908,425 and $1,924,607 for CARGs, AGAGs and ACRGs respectively. Of patients suggested to not require further surveillance per CARGs, approximately 1% develop malignancy with fewer being candidates for surgical resection. Overall, 44.8% of initial PCL reports provided CARG recommendations while 54.3% of PCLs were followed as per CARGs. Conclusions: CARGs are safe and offer substantial cost and opportunity savings for PCL surveillance. These findings support Canada-wide implementation with close monitoring of consultation requirements and missed diagnoses.
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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 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".