SmartClamp circumcision versus conventional dissection technique in terms of parental anxiety: A prospective clinical study
Bibliographic record
Abstract
INTRODUCTION: We prospectively analyzed parental anxiety and outcomes of the SmartClamp circumcision and the classic surgical dissection technique. METHODS: A total of 250 boys underwent circumcision between 2009 and 2012 at Kars State Hospital and Kafkas University Faculty of Medicine in Turkey. The initial 125 children were circumcised by conventional dissection method and the remaining children were operated on with a SmartClamp device. Children in both groups were compared in terms of bleeding, infection, penile edema, operative time, cosmetic result, length of the inner mucosal layer, and parental anxiety. We used a State-Trait Anxiety Inventory (STAI) form to gauge how the circumcision affected parental anxiety. This form was completed by parents on postoperative day 2. RESULTS: There were no statistically significant differences among the 2 groups in terms of age, bleeding, infection, and cosmetic displeasure (p > 0.05). The STAI scores of the parents from the SmartClamp group were statistically higher than that of the other group (p < 0.001). Penile edema was more common in the SmartClamp group (p = 0.039). However, the mean operative time was statistically shorter (p < 0.001) and the inner mucosal length was significantly longer in the SmartClamp group (p < 0.001). CONCLUSION: Circumcision with the SmartClamp device was faster. Cosmetic results and complication rates were similar. Unfortunately, this technique seemed to entail the disadvantages of longer mucosal length, penile edema, and higher parental anxiety. Urologists should keep these points in mind when choosing a technique.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".