Optimizing clinic consultations in primary biliary cholangitis: International consensus recommendations
Bibliographic record
Abstract
BACKGROUND: There is variability in primary biliary cholangitis (PBC) care delivery in practice, which can negatively impact disease management and patients' quality of life. Patient-provider consultations are key to ensure optimal and comprehensive disease management; however, the quality and substance of this interaction may vary. A Delphi study was carried out to provide consensus recommendations to improve and standardize consultations between providers and patients with PBC. METHODS: An international survey of 151 healthcare professionals was conducted with input from 9 PBC experts (6 physicians, 1 patient, 1 patient advocate, and 1 nurse practitioner) who formed the Delphi panel. Informed by findings of the survey, the panel used Delphi methodology to develop best practice recommendations with the aim of informing the broader care framework. Consensus was defined as ≥75% agreement among panel members. RESULTS: We identified 15 best practice recommendations across 3 principal areas: "patient-provider discussions at diagnosis/first consultation," "symptom assessment and ongoing management," and "wider care and support." These consensus-based recommendations are a resource for providers to help address patient needs around symptom burden, referrals to specialists other than hepatologists, and connection to patient support organizations. CONCLUSION: We provide specific recommendations for providers to optimize consultation for patients with PBC with the aim of improving care and patient satisfaction.
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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 | 0.195 | 0.275 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.010 | 0.012 |
| Research integrity | 0.013 | 0.011 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".