A206 PREDICTORS OF HOSPITAL READMISSION FOLLOWING LIVER TRANSPLANTATION: A SINGLE CENTRE EXPERIENCE
Bibliographic record
Abstract
Liver transplantation is a life saving procedure for patients with end stage liver disease or hepatocellular carcinoma. Morbidity and mortality rates have dramatically declined with the evolution of the procedure. However, hospital readmission after discharge is still common and increases healthcare costs. The purpose of this study is to determine predictors of hospital readmission in patients that underwent liver transplantation. This is a retrospective study conducted at London Health Sciences Centre, a tertiary care centre, in London, Ontario, Canada. All patient who underwent liver transplantation between 2012 and 2016 were included in this study. Charts were reviewed to collect patient demographics, donor organ variables, readmission rates, and post-operative complications. Statistical analysis was performed with multivariable logistic regression. A p value <0.05 was statistically significant. There were 255 patients that underwent liver transplantation with a median age of 60 years old and 31% were female. The most common cause of liver disease was hepatitis C and alcohol. The median MELD score was 21. Of the liver transplants performed, 83% were from brain dead donors, 15% were from donors after cardiac death, and 2% were from living donors. The mean donor risk index was 1.68. Patients required readmission in 17% of cases after being discharged post-liver transplant. The most common cause of readmission was elevated liver enzymes in 6%, graft failure in 5%, and infection in 3%. The most common post-operative complications were surgical in 72%, infection in 20% and nutrition in 10%. Death occurred in 9% during the follow up period. On multivariable logistic regression the only significant predictor of readmission within 90 days of liver transplant was surgical complications with an odds ratio of 3.0 (95% confidence interval of 1.2–7.5, p-value of 0.02). Hospital readmission post-liver transplantation is common which leads to increased healthcare utilization. Post-operative surgical complications were the only clinical predictor of readmission within 90 days of discharge. None
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".