The Effect of Varicose Vein Surgery on Varicose Ulcers
Bibliographic record
Abstract
Background: Despite of the growing trend of varicose ulcers, the effect of vascular surgery is not clear exactly on the treatment of these ulcers. The present study aimed to compare the clinical features of patients before and after the varicose vein surgery. Methods: In a cross-sectional study during 2016, the outcomes of 50 patients who were referred to Alzahra Hospital in Isfahan, Iran, for varicose veins surgery were examined before and after surgery in terms of patients’ opinions, the mean of Vancouver score, and ulcer complications. Findings: The mean Vancouver score was 7.9 ± 2.0 and 5.1 ± 1.5 before and after surgery, respectively. The relative frequency of wound healing was 35.1 ± 19.2 percent, postoperatively. The mean score of varicose ulcer was 9.20 ± 0.67 one week before the surgery, and 4.76 ± 1.33 and 2.50 ± 0.74, one week and one month after it, respectively. Mean Vancouver score before and after treatment was different statistically (P < 0.001). The wounds and varicose veins complications were reduced statistically (P = 0.015). Conclusion: The mean Vancouver score, ulcer complications, and varicose ulcers decreased after surgery. Surgery was most effective in patients with active edema or scarring, while those in multiple complications were less likely to recover.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".