Bleomycin for Head and Neck Venolymphatic Malformations: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Venolymphatic malformations are rare benign vascular lesions of the head and neck. Sclerotherapy has become the first-line therapy of these lesions with bleomycin being a sclerosing agent commonly used. PURPOSE: To perform a systematic review of the published literature to synthesize evidence on the safety and efficacy of bleomycin for the treatment of head and neck venolymphatic malformations. DATA SOURCES: A systematic review of the literature (January 1995-May 2019) was performed in PubMed, Embase, and Cochrane Library databases to identify studies on sclerotherapy of venolymphatic malformations of the head and neck. STUDY SELECTION: A total of 32 studies with participants met the inclusion criteria among which 1121 patients were included in the systematic review. DATA ANALYSIS: Two reviewers independently screened and extracted data and assessed the risk of bias. The primary outcome was the subjective or objective reduction of lesion size as well as minor and major complications. DATA SYNTHESIS: The bleomycin/pingyangmycin sclerotherapy achieved subjective or objective lesion size reduction in 96.3% (95% CI 94.1%-98.5%) of patients. Minor complications were observed in 16.2% and major complications in 1.1%. CONCLUSION: Bleomycin is a highly effective treatment of venolymphatic malformations of the head and neck with a low rate of major adverse events. This study represents an update on the "available" evidence, but only low-to-moderate quality studies were available. LIMITATIONS: This study reviewed 32 studies performed in different parts of the world, but there was heterogeneity of the study designs and interventions.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".