Is radiofrequency ablation of varicose veins a valuable option? A systematic review of the literature with a cost analysis
Bibliographic record
Abstract
BACKGROUND: Since the 1990s, new techniques for the treatment of varicose veins have emerged, including radiofrequency ablation (RFA) and laser treatment. We performed a study to compare the safety, efficacy and outcomes of RFA compared to those of open surgery and laser ablation for the treatment of varicose veins. We also carried out a cost analysis of RFA compared to open surgery to assess whether RFA could help free up operating room time by being performed in an outpatient context. METHODS: We conducted a systematic literature review (publication date May 2010-September 2013 for articles in English, January 1991-September 2013 for those in French). We used several checklists to measure the quality of the studies. We also collected data on costing. RESULTS: The literature search identified 924 publications, of which 38 were retained for analysis: 15 literature reviews, 1 good-practice guideline and 22 new primary studies. The overall level of evidence was low to moderate owing to the limited sample sizes, lack of information on patient characteristics and lack of standardization of the outcome measures. However, the results obtained are consistent from study to study. In the short and medium term, RFA is considered as effective as open surgery or laser treatment (moderate level of evidence) and presents fewer major and minor complications than open surgery (low level of evidence). Radiofrequency ablation can be performed on an outpatient basis. We calculated that RFA would be about $110-$220 more expensive per patient than open surgery. CONCLUSION: Radiofrequency ablation is a valuable alternative to open surgery and would free up operating room time in a context of low accessibility.
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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 | 0.023 | 0.104 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.016 |
| Bibliometrics | 0.024 | 0.022 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".