Recurrent Varices after Surgery (REVAS), a Consensus Document
Bibliographic record
Abstract
Report of the meeting† held in Paris on 17th & 18th July 1998 with participation oft: Ugo Baccaglini, Italy; Pierre Barthelemy. France; Jean-Claude Couffinhal. France: Denis Creton. France: Simon Darke, United Kingdom; Ralph De Palma, United States of America; Bo Eklof, United States of America; Ermenegildo Enrici, Argentina; Gilbert Franco, France; Jean Pierre Gobin, France; Louis Grondin, Canada; Jean-Jerome Guex. France; Georges Jantet. France; Claude Juhan. France; Jordi Maeso y Lebrun. Spain; Philippe Nicolini. France; Andreas Oesch, Switzerland; Marcelo Paramo-Diaz. Mexico; Michel Perrin. France; Paul Puppinck, France; Eberhard Rabe, Germany: Rene Rettori, France; John Royle, Australia; Vaughan Ruckley, United Kingdom; Michel Schadeck, France; Jean Claude Schovaerdts, Belgium; John Scurr, United Kingdom; Georgio Spreafico, Italy; Jan Struckman, Denmark; Frederic Vin, France Recurrent varicose veins after surgery (REVAS) are a common, complex and costly problem. The frequency of REVAS is stated to be between 20 and 80% depending on the definition of the condition. A consensus meeting on the topic (Paris 1998, July) decided to adopt a clinical definition: the presence of varicose veins in a lower limb previously operated on for varices. The pathology of recurrent varicose veins has been poorly correlated with clinical examination and operative findings. Clinical diagnosis remains essential but does not allow a precise assessment of REVAS. Consequently, the use of imaging investigations is essential. Duplex scan is considered as the method of choice. Both clinical diagnosis and imaging investigations allow the development of a classification for every day usage and future studies. This new classification of CEAP needs to be expanded to define the sites, nature and sources of recurrence, the magnitude of the reflux and other (possible) contributory factors. Methods for REVAS treatment include compression, drugs, sclerotherapy and redo surgery. There was no general consensus in favour of sclerotherapy, surgery or both to treat REVAS. Very few data were available to assess the results of treatment. Factors responsible for recurrence and recommendations for primary prevention were debated and are presented in this article. Guidelines for well-planned prospective studies have been produced.
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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 | 0.028 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".