Interpolation Flaps in the Outpatient Mohs Surgery Setting: A Prospective Cohort Study of Patient Pain, Anxiety, and Satisfaction
Bibliographic record
Abstract
BACKGROUND: Staged interpolation flaps (SIFs) have historically been performed under general anesthesia by specialties outside of dermatologic surgery. However, SIFs performed under local anesthesia by dermatologic surgeons have shown lower or equal complication rates. OBJECTIVE: To date, no studies have evaluated pain, anxiety, satisfaction, and use of perioperative analgesics in patients undergoing SIFs in an outpatient setting under local anesthesia. METHODS/MATERIALS: This is a prospective cohort study of 39 patients who received Mohs micrographic surgery and subsequent SIF repair in an outpatient setting under local anesthesia. Pain, anxiety, and satisfaction scores were recorded using 100-point validated visual analog scales. Perioperative analgesic use was quantified. RESULTS: The defect size was ≥4 cm2 in 72% of patients; 41% had full-thickness (skin/cartilage/mucosa) defects. All pain and anxiety measures were minimal to mild. Pain scores ranged from highest (mean = 39 ± 4.1) on postoperative Day (POD) 1 to lowest (mean = 12.3 ± 2.0) on POD 7. Anxiety scores ranged from highest (mean = 42 ± 4.5) on POD 1 to lowest (mean = 18.5 ± 3.7) on POD 7. Perioperative patient satisfaction was high (mean = 95 ± 1.7). Postoperative narcotic analgesics were prescribed in 15% of patients. CONCLUSION: Staged interpolation flaps performed under local anesthesia in the outpatient setting are well tolerated with low pain and anxiety, high patient satisfaction, and minimal analgesic use.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".