S2023 Readmission Rates for Patients with Cirrhosis at Royal University Hospital
Bibliographic record
Abstract
Introduction: Cirrhosis is one of the leading global cause of hospitalization, readmission, and death, with 1.5 million attributed deaths in 2019. Cirrhosis-related deaths in the US have increased by 65% from 1999 to 2016. Canadian projections indicate a doubling of cirrhosis cases by 2040, largely due to metabolic-associated and alcohol-related liver disease. Patients with cirrhosis require frequent admissions due to portal hypertension-related complications, including ascites, hepatic encephalopathy, variceal bleeding, infection, and renal failure. A US study found a 20.7% readmission rate at 30 days and a 30.1% rate at 90 days. Cirrhosis-related readmissions increase the economic burden, and is associated with increased morbidity and mortality. Methods: The aim of this project was to determine readmission rates at 30, 60, and 90-day intervals. A retrospective chart review was conducted to ascertain the cirrhosis readmission rate among adult patients at the Royal University Hospital (RUH) between 2016 and 2022. Patients were identified based on their admission diagnostic codes. Exclusion criteria included patients with hepatocellular carcinoma and those receiving palliative care for end-stage liver disease. Of 375 charts reviewed,115 participants were included in the study. Results: Readmission rates at RUH match or surpass previously cited rates. As shown in (Figure 1), readmission rates were 24% at 30 days, 28% at 60 days, 34% at 90 days, and 46% at 91+ days. Almost half of the patients (53/115) had cirrhosis secondary to alcohol use. Other etiologies included hepatitis C (24/115), metabolic steatosis (9/115), autoimmune causes (5/115), primary biliary cholangitis (4/115), and primary sclerosing cholangitis (1/115), and 19/115 had cryptogenic cirrhosis. Patients with underlying alcohol-related liver disease and those with 2 or more portal hypertension-related complications had higher readmission rates. The population with a higher readmission rate had a greater than 40% mortality within one year. Conclusion: Our preliminary data analysis shows rates in accordance with the literature. As expected, advanced disease and alcohol-related liver disease predict increased readmission risk. Our study highlights areas for intervention to reduce readmission, improve patient outcomes, and reduce healthcare costs. Our hope is to implement inpatient and outpatient intervention to reduce readmission rate in this patient population.Figure 1.: Number of patients readmitted (blue) compared to number not readmitted (orange) at intervals of 30 days, 60 days, 90 days and 91+ days post-admission.
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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) | 0.010 | 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".