Implications of preoperative pulmonary function testing for post liver transplant outcomes
Bibliographic record
Abstract
ABSTRACT Pulmonary complications are common post-transplant and may lead to increased mortality. Pulmonary function tests (PFTs) are routinely obtained preoperatively, but their usefulness in liver transplantation is unknown. The objective of this study was to assess the impact of preoperative PFTs on postoperative pulmonary complications (PPCs), ICU stay, and death post-liver transplant. This single site historical cohort study encompassed all 531 liver transplants performed in 462 patients at the Royal Victoria Hospital through June 30, 2006. Outcomes included death, PPCs, and length of intubation and ICU stay. Independent variables including PFTs, age, gender, race, smoking history, etiology of liver disease, MELD score, and ischemia time were used in logistic regression and Cox proportional hazards models to assess their impact on the outcomes listed above. 205 patients had complete PFT data. Decreased total lung capacity (TLC) was a predictor of increased length of ICU stay, duration of intubation, and mortality. A 10% decrease in TLC increased the mortality risk by 43%. Increased residual volume (RV), cold ischemia time, and age were predictors of mortality. Predictors of prolonged ICU stay or intubation were TLC, MELD score, male gender and cold ischemia time. PFTs were not significant predictors of PPCs. PFTs do not predict pulmonary complications but predict length of ICU stay and intubation, as well as mortality. PFTs may reflect the severity of underlying liver disease as well as intrinsic lung disease.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".