Comparing Patency of Pulmonary Stent Implantation and Balloon Angioplasty in Pulmonary Vein Stenosis: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
ABSTRACT Pulmonary vein stenosis (PVS) is an insidious diagnosis associated with morbidity and mortality. Pharmacologic therapy may suffice initially, but advanced stages demand mechanical intervention. Pulmonary stent implantation (PSI) and pulmonary balloon angioplasty (PBA) are common strategies, both carrying restenosis risks. This meta‐analysis compares PSI and PBA to determine the superior revascularization strategy. We systematically searched databases until November 2023, identifying 11 studies with 780 patients. Studies, including those involving patients undergoing balloon angioplasty (BA) or stent angioplasty (SA) for PVS, were selected. Case reports, editorials, and cross‐sectional studies were omitted. Primary outcomes included restenosis requiring reintervention, 5‐year freedom from restenosis, and procedure‐related complications. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using a random‐effects model. Meta‐regression analysis assessed factors like age and stent size. Study quality was evaluated using the Newcastle–Ottawa scale. This Systematic review and meta‐analysis incorporated 11 observational studies. PSI exhibited a lower risk of restenosis requiring reintervention (OR 0.34, 95% CI 0.13, 0.87, p = 0.02) and significantly higher 5‐year freedom from restenosis (OR 4.42, 95% CI 1.11, 17.62, p = 0.04) compared to PBA, with no significant difference in procedure‐related complications. Meta‐regression analysis showed age and stent size insignificantly affecting restenosis risk. Our review supports PSI as the preferred revascularization strategy for PVS due to superior patency benefits, emphasizing its role as the initial treatment choice. Further research is warranted for validation, considering individual patient factors in treatment selection.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.033 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".