Variability in the Management of Superficial Venous Thrombophlebitis Among Phlebologists and Vascular Surgeons
Bibliographic record
Abstract
INTRODUCTION: This study aimed to compare management patterns of patients with superficial venous thrombophlebitis (SVT) among phlebologists and vascular surgeons. METHODS: A survey was provided to practitioners who attended the American Venous Forum meeting in 2011. Statistical analysis included descriptive statistics, unpaired t tests, and Friedman's test for correlation. RESULTS: There were 354 US or Canadian health care providers of whom 169 were phlebologists and 185 were vascular surgeons. There was a significant different in anticoagulation administration and duration (P = .034, P = .032, respectively). Friedman's test for correlation between multiple surgical treatments showed no correlation between surgical treatments tested with all treatments having an equal distribution in our data. Follow-up differed between groups with vascular surgeons following up with imaging more than phlebologists (P = .03). CONCLUSION: Our data indicate that there is no consensus between or among phlebologists or vascular surgeons as to the surgical management of superficial venous thrombophlebitis, duration of follow-up, and anticoagulation parameters.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".