Clinical outcomes of polymeric sealant use in pulmonary resection: a systematic review and meta-analysis of randomized controlled trials
Bibliographic record
Abstract
BACKGROUND: Prolonged alveolar air leak (PAL) is the most common adverse event following pulmonary resection. It carries morbidity for patients by increasing empyema risk, and for hospital administration with the cost of prolonged length of hospital stay (LOS). Intra-operative sealant technology is available to surgeons, and may decrease PAL. Our aim was to conduct a systematic review and meta-analysis of randomized controlled trials (RCTs) on the effect of intraoperative polymeric sealant use on PAL, empyema, and LOS. METHODS: Standard PRISMA (Preferred Reporting Items for Systematic reviews and Meta-analysis and methods) protocol was adhered to. For qualitative review the search strategy yielded 21 RCTs reporting polymeric sealant use in lung resection, 19 of which were included in meta-analyses. The control arm in the two excluded RCTs was not "standard care." Random-effects meta-analyses were conducted. Inter-trial heterogeneity was assessed with the I2 statistic. Publication bias was assessed with a funnel plot and Egger statistic for small study effects. RESULTS: Pooled analysis was derived from 2,537 randomized participants. They were allocated to the intervention arm of lung resection with intra-operative application of a polymeric sealant (n=1,292), or the control arm of standard care involving pulmonary resection with pneumostasis by sutures and/or stapler (n=1,245). Participants came from 10 different countries, with mean (SD) age of 62.5 (4.2) years, and 31.6% (95% CI: 30.0-33.5) female. Pooled estimates revealed polymeric sealant decreased odds of PAL (OR 0.55, 95% CI: 0.35-0.87), and decreased LOS by one day (mean difference -0.96, 95% CI: -1.74 to -0.18), without increasing odds of pleural sepsis (OR 1.134, 95% CI: 0.343-3.748). There was evidence of publication bias in the LOS meta-analysis. CONCLUSIONS: Pooled analysis revealed decreased odds of PAL, and decreased LOS by one day with intraoperative use of polymeric sealants. There was no associated increase in odds of adverse events, including empyema.
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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 | 0.020 | 0.052 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.045 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".