Review of outcomes of delayed chest closure following lung transplantation: a meta-analysis
Bibliographic record
Abstract
PURPOSE: The clinical outcomes of delayed chest closure (DCC) compared with primary chest closure (PCC) following lung transplantation, including perioperative outcomes and long-term survival, remained controversial. This was the first systematic review and meta-analysis aimed to identify the short- and long-term outcomes of DCC following lung transplantation. METHODS: We comprehensively searched electronic literature from 4 databases up to April 1st, 2022. Dichotomous data and continuous data were pooled with odds ratio and weighted mean difference, respectively. The quality of included studies was assessed with the Newcastle-Ottawa Scale. RESULTS: Ten studies were included in the systematic review and 4 studies were included in the meta-analysis. Pooled analysis showed that DCC was associated with an increased risk of surgical site infection, prolonged hospital stays, and higher risk of primary graft dysfunction compared to PCC. The 30 day and 5 year survival were higher in PCC cohort compared with DCC cohort while differences in survival at 6 months was insignificant. CONCLUSION: Our findings do not support the aggressive application of DCC. DCC should be cautiously applied since its association with worse perioperative outcomes and higher mortality. But it remains the life-saving steps under dangerous circumstances.
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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 | 0.007 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.024 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 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".