Preoperative Hair Removal on the Male Genitalia: Clippers vs. Razors
Bibliographic record
Abstract
INTRODUCTION: In an effort to reduce the incidence of postoperative surgical site infections (SSIs), many hospitals have adopted a strict practice of preoperative hair removal using clippers, as opposed to razors. However, the skin of the male genitalia is delicate, elastic with irregular skin folds and may be ill-suited for clippers. AIM: To compare shave quality and the degree of skin trauma using two methods of preoperative hair removal on the scrotal skin: clippers vs. razors. METHODS: Patients undergoing surgery involving the male genitalia requiring preoperative hair removal were randomized to hair removal using clippers or a razor. Immediately following hair removal, a standardized digital photograph was taken of the male genitalia. All digital photos were evaluated in a blinded fashion by groups of urologic surgeons and surgical nurses using a standardized five-point global rating scale. The incidence of SSIs was monitored. MAIN OUTCOME MEASURES: Primary outcomes included blinded global ratings of (i) the completeness of the preoperative hair removal within the surgical field and (ii) degree of skin trauma following hair removal. The incidence of SSIs within 3 months of surgery was monitored throughout the study period. RESULTS: Two hundred fifteen consecutive patients were randomized (107 clipper, 108 razor). Overall, preoperative hair removal on the male genitalia using a razor resulted in significantly less skin trauma (P = 2.5E-10) and a more complete hair removal within the surgical field (P = 0.017) compared with clippers. SSIs were identified in four patients during follow-up (1.8%--two using clippers; two, razors). CONCLUSIONS: Our data suggest that preoperative hair removal on the scrotal skin using a razor results in less skin trauma and improved overall shave quality with no apparent increased risk of SSIs. Based on these findings, surgeons should be permitted their choice of razors or clippers for preoperative preparation of the male genitalia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| 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 | 0.001 |
| 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 teacher head, 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".