Choosing Wisely Canada-Top Five List in Hepatology: Official Position Statement of the Canadian Association for the Study of the Liver (CASL) and Choosing Wisely Canada (CWC)
Bibliographic record
Abstract
INTRODUCTION AND AIM: The prevalence and incidence of chronic liver disease is increasing resulting, in substantial direct and indirect medical costs. Overuse of investigations, treatments and procedures contribute to rising health care costs and can expose patients to unnecessary harm and delay in receiving care. The Choosing Wisely Canada (CWC) campaign has encouraged professional societies to develop statements that are directly actionable by their members in an effort to promote higher-value health care that will lead to downstream effect on how other practitioners make decisions. MATERIAL AND METHODS: The Canadian Association for the Study of the Liver (CASL) established its Choosing Wisely top five list of recommendations using the framework put forward by CWC. CASL convened a task force that developed a list of draft recommendations and shared this with CASL membership electronically with eventual ranking of the top five recommendations by consensus at Canadian Digestives Disease Week (CDDW) 2017. Following revisions, the CASL Executive Committee endorsed the final list, which was disseminated online by CWC (July 2017). RESULTS: The top five recommendations physicians and patients should question include: 1) Don't order serum ammonia to diagnose or manage hepatic encephalopathy (HE). 2) Don't routinely transfuse fresh frozen plasma, vitamin K, or platelets to reverse abnormal tests of coagulation in patients with cirrhosis prior to abdominal paracentesis, endoscopic variceal band ligation, or any other minor invasive procedures. 3) Don't order HFE genotyping based on serum ferritin values alone to diagnose hereditary hemochromatosis. 4) Don't perform computed tomography (CT) or magnetic resonance imaging (MRI) routinely to monitor benign focal liver lesions. 5) Don't repeat hepatitis C viral load testing in an individual who has established chronic infection, outside of anti-viral treatment. CONCLUSION: The Choosing Wisely recommendations will foster patient-physician discussions, reduce unnecessary treatment and testing, avert adverse effects from testing and treatment along with reducing medical expenditure in hepatology.
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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 | 0.029 | 0.111 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.013 | 0.016 |
| Insufficient payload (model declined to judge) | 0.022 | 0.012 |
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".