When is the optimal time to discharge patients after liver transplantation with respect to short‐term outcomes? A systematic review of the literature and expert panel recommendations
Bibliographic record
Abstract
BACKGROUND: Several factors associated with prolonged hospital stay have been described. A recent study demonstrated that hospital length of stay (LOS) is directly associated with an increased cost for liver transplantation (LT) and may be associated with greater mortality; however, the factors associated with post-LT mortality are also related to a prolonged hospital stay, that is, those factors are confounders. Thus, the actual impact of the length of post-LT hospital stay on both short-term and long-term patient and graft survival remains uncertain. OBJECTIVES: To identify the optimal time to discharge patients after LT with respect to short-term outcomes; readmission rate, 30-90-mortality and morbidity. METHODS: Systematic review following PRISMA guidelines and recommendations using the GRADE approach derived from an international expert panel. Initial search keywords for screening were as follows; ((discharge AND (time OR "time point" OR "time-point")) OR "length of hospital stay" OR "length of stay") AND ((liver OR hepatic) AND (transplant OR transplantation)). PROSPERO ID: CRD42021245598 RESULTS: The strength of recommendation was rated as Weak, and we did not identify the direction of recommendations regarding the optimal timing after LT concerning short-term outcomes, including "Readmission rate," six studies on 30- and/or 90-day mortality, and five studies on "30- and/or 90-day morbidity rate." CONCLUSIONS: Evidence is scarce to judge the optimal timing to discharge patients after LT with respect to short-term outcomes. In centers with robust outpatient follow-up, discharge can occur safely as early as post-transplant 6-8 days (Quality of Evidence [QOE]; Low | Grade of Recommendation; Weak).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".