1 Multicenter analysis of uptake and cost of Canadian multidisciplinary pancreatic cyst guidelines
Bibliographic record
Abstract
Objectives Incidental pancreatic cystic lesion (PCL) prevalence is approximately 10%. PCL surveillance is required because a small subset have malignant potential. While several surveillance guidelines exist, utilization is variable. The Canadian Association of Radiologists Incidental Findings Working Group recently published guidelines intending to simplify and create cost-effective recommendations without compromising patient care. The purpose of this study was to calculate uptake and cost savings of these new CAR guidelines (CARG) in comparison to American Gastroenterology Association guidelines (AGAG) and American College of Radiology guidelines (ACRG). Methods This is a multicenter retrospective study of abdominal MRIs completed one-year after a single health zone’s CARG implementation. MRIs completed during one year were reviewed to identify those with PCL. Radiology reports were reviewed for appropriate CARG recommendations. Total costs, including MRI and subspecialty consultation, associated with surveillance based on CARG, AGAG, and ACRG were compared. Results 6,698 abdominal MRIs were reviewed with 1,001 (14.9%) identifying PCL. When PCLs were identified, 44.8% of reports provided CARG recommendations. The total cost of surveillance for 10-years for each guideline was $482,268, $1,894,745, and $1,901,237 for CARGs, AGAGs, and ACRGs respectively. Cost savings are recognized through fewer MRIs, while consultations may increase. CARGs can potentially save $1.4 million (CDN) in a single health zone over ten-years and increase MRI access. Conclusions Recently published CARGs offer substantial cost and opportunity savings for PCL surveillance. These findings support implementation of these guidelines 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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".