Physicians’ Practices for Diagnosing Liver Fibrosis in Chronic Liver Diseases: A Nationwide, Canadian Survey
Bibliographic record
Abstract
OBJECTIVE: To determine practices among physicians in Canada for the assessment of liver fibrosis in patients with chronic liver diseases. METHODS: Hepatologists, gastroenterologists, infectious diseases specialists, members of the Canadian Gastroenterology Association and⁄or the Canadian HIV Trials Network who manage patients with liver diseases were invited to participate in a web-based, national survey. RESULTS: Of the 237 physicians invited, 104 (43.9%) completed the survey. Routine assessment of liver fibrosis was requested by the surveyed physicians mostly for chronic hepatitis C (76.5%), followed by autoimmune⁄cholestatic liver disease (59.6%) and chronic hepatitis B (52.9%). Liver biopsy was the main diagnostic tool for 46.2% of the respondents, Fibroscan (Echosens, France) for 39.4% and Fibrotest (LabCorp, USA) for 7.7%. Etiology-specific differences were observed: noninvasive methods were mostly used for hepatitis C (63% versus 37% liver biopsy) and hepatitis B (62.9% versus 37.1% liver biopsy). For 42.7% of respondents, the use of noninvasive methods reduced the need for liver biopsy by >50%. Physicians' characteristics associated with higher use of noninvasive methods were older age and being based at a university hospital or in private practice versus community hospital. Physicians' main concerns regarding noninvasive fibrosis assessment methods were access⁄availability (42.3%), lack of guidelines for clinical use (26.9%) and cost⁄lack of reimbursement (14.4%). CONCLUSIONS: Physicians who manage patients with chronic liver diseases in Canada require routine assessment of liver fibrosis stage. Although biopsy remains the primary diagnostic tool for almost one-half of respondents, noninvasive methods, particularly Fibroscan, have significantly reduced the need for liver biopsy in Canada. Limitations in access to and availability of the noninvasive methods represent a significant barrier. Finally, there is a need for clinical guidelines and a better reimbursement policy to implement noninvasive tools to assess liver fibrosis.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".