Immediate versus conventional postoperative tracheal extubation for enhanced recovery after liver transplantation
Bibliographic record
Abstract
INTRODUCTION: To systematically compare immediate postoperative tracheal extubation (IPTE) with conventional tracheal extubation (CTE) and to determine whether IPTE can achieve an enhanced recovery for adult patients underwent liver transplantation (LT) without additional risks. We designed a systematic review and meta-analysis. METHODS: The RCTs, cohorts, case-controls, or case series that explored outcomes of IPTE after LT for adults were involved in our study. The Newcastle-Ottawa scale was used to assess the risk of bias. RESULTS: A total of 15 studies (n = 4144) were included, consisting of 10 studies (retrospective cohorts; n = 3387) for quantitative synthesis and 5 studies (1 prospective cohort, and 4 case series; n = 757) for qualitative synthesis. The pooled estimates suggested IPTE could reduce time to discharge from ICU stay (TDICU) (mean difference [MD] -2.12 days, 95% confidence interval [CI] -3.04 to -1.19 days), time to discharge from the hospital (TDH) (MD -6.43 days, 95% CI -9.53 to -3.33 days), re-intubation rate (RI) (odds ratio [OR] 0.29, 95% CI 0.22-0.39), morbidity rate (MR) (OR 0.15, 95% CI 0.08-0.30) and graft dysfunction rate (GD) (IPTE vs CTE: 0.3% vs 3.8%, P < .01), and had comparable ICU survival rate (ICUS) (OR 6.67 95% CI 1.34-33.35) when compared with CTE after LT. CONCLUSIONS: IPTE can achieve an enhanced recovery for adult patients underwent LT without additional re-intubation, morbidity, and mortality risks. However, further work needs to be done to establish the extent definitively through carefully designed and conducted RCTs.
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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 | 0.014 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.014 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".