PAs and NPs in liver transplantation
Bibliographic record
Abstract
OBJECTIVES: This study assessed the use and perceptions of physician associates/assistants (PAs) and NPs at liver transplant centers and sought to determine their financial effect. METHODS: Leaders of liver transplant programs performing 25 or more transplants in 2020 were contacted to complete an 11-question survey about the role and effect of PAs and NPs in liver transplant. A single-center retrospective analysis compared length of stay (LOS) and readmission rates for primary liver transplants and simultaneous liver-kidney transplants before and after a dedicated PA team was established. Chi-square and t -test analyses were performed. RESULTS: The survey achieved a 77% response rate, and 98% of institutions reported using PAs and NPs. The single-center study found the mean LOS post-transplant was significantly shorter in the post-PA cohort ( P = .0005). No significant difference was found in 30-day readmission rates. CONCLUSIONS: PAs and NPs are used broadly across the post-liver transplant care continuum. Using LOS as a surrogate financial marker suggests that a dedicated PA and NP team may contribute to cost savings.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".