Impact of specialized multidisciplinary care on cirrhosis outcomes and acute care utilization
Bibliographic record
Abstract
Background: Multidisciplinary care has the potential to improve outcomes among patients with cirrhosis, yet its impact on this population remains unclear, with existing studies demonstrating discrepant results. Using data from the multidisciplinary outpatient Cirrhosis Care Clinic (CCC) at the University of Alberta Hospital, we aimed to evaluate acute care utilization and survival outcomes of patients followed by the CCC compared with those receiving standard care (SC). Methods: We performed a retrospective chart review of 212 patients with cirrhosis admitted to University of Alberta Hospital between 2014 and 2015. CCC patients ( n = 36) were followed through the CCC before index admission. SC patients ( n = 176) were managed outside of the CCC. Readmission time in hospital was collected until 1 year, death, or liver transplant. Results: CCC patients had more advanced liver disease (higher prevalence of ascites, encephalopathy, and varices). Despite this, acute care utilization was significantly lower among CCC patients (adjusted length of stay lower by 3 days, p = 0.03, and adjusted survival days spent in hospital lower by 9%, p = 0.02). CCC patients also had improved 1-year transplant-free survival, with an adjusted 1-year relative risk reduction of 53% ( p = 0.03). Total mean cost of care was lower in the CCC group by $2,280 per patient-month of life. Discussion: For patients admitted with cirrhosis, specialized post-discharge multidisciplinary outpatient care is associated with decreased acute care utilization, improved 1-year transplant-free survival probability, and the potential for cost savings to the system.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".