Ambulatory buccal mucosal graft urethroplasty in geriatric population: A practice change experience
Bibliographic record
Abstract
ABSTRACT Context: Due to the overwhelming burden of coronavirus disease 2019, buccal mucosal graft (BMG) urethroplasty in the elderly has been shifted from inpatient to ambulatory at our center in early 2020. Aim: This study aims to describe our experience with ambulatory BMG urethroplasty in the elderly and compare its feasibility and safety to inpatient urethroplasty before and after the practice change. Setting and Design: A pre and postpractice change retrospective cohort study of patients aged 65 years or above with BMG urethroplasty performed at our center between March 2018 and May 2022. Materials and Methods: Demographics, clinical characteristics, postoperative course, and complications were compared in ambulatory (discharged within 6 h) versus inpatient BMG urethroplasty groups. Statistical Analysis: A pre-and post-practice change retrospective cohort study of patients aged 65 or older with BMG urethroplasty performed at our centre between March 2018 and May 2022. Results: Of 37 BMG urethroplasties, 15 (40.5%) were inpatient, whereas 22 (59.5%) were ambulatory. Immediate complication rate was comparable in inpatient (2/15, 13.3%) and ambulatory cases (1/22, 4.5%): one wound infection in both groups and one recurrent urinary tract infection in the inpatient group. No oral cavity complications, bleeding/hematoma, or anesthesia-related morbidity were observed. There was no statistically significant difference in recurrence (13.3% vs. 9.6%; P = 0.98) and success rates (90.9% vs. 86.7%; P = 0.53) over a median of 53 (inpatient) and 34 (ambulatory) months follow-up. Conclusions: Ambulatory BMG urethroplasty, discharge within 6 hours of surgery, appears safe and feasible in geriatric populations (>65), with no increased adverse outcomes. Factors like healthcare access, caregiver availability, and patient education play roles in discharge time. However, more robust studies are warranted for conclusive evidence.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".