Improving communication of post-holmium laser enucleation of the prostate recovery using a surgeon-patient handout
Bibliographic record
Abstract
INTRODUCTION: To improve surgeon-patient communication of postoperative expectations, a multidisciplinary team created and evaluated a holmium laser enucleation of the prostate (HoLEP) expectations handout. Although an effective benign prostatic hyperplasia (BPH) surgery, it is crucial that patients understand the HoLEP recovery. A quality assessment previously performed at our center revealed 11% of patients were not aware of potential ejaculate volume changes. METHODS: Patients presenting for consultation prior to HoLEP were assessed with post-procedure patient-reported outcomes (PRO) questionnaires before (n=50) and after (n=50) the implementation of a surgeon-patient expectations handout. Patient demographics and perioperative course were examined in the context of responses. Comparisons were made with a Chi-squared test (p<0.05). RESULTS: We observed a response rate of 96% (pre-handout: 46/50 vs. post-handout: 50/50). Overall, 89/96 (93%) patients felt they had a reasonable understanding of HoLEP expectations, with no difference between cohorts (45/46 vs. 48/50, p=0.71). There was no difference in reporting an understanding of post-HoLEP hematuria (p=0.12) or urinary incontinence (UI) (p=0.99). The implementation of the handout improved understanding of retrograde ejaculation (pre-handout: 41/46 vs. post-handout: 50/50, p=0.022) and dysuria (pre-handout: 35/46 vs. post-handout: 46/50, p=0.048). Fifty-five patients experienced any dysuria postoperatively, with 89% reporting less than or equal to what they expected. Close to 30% (28/94) of respondents offering ways to improve communication suggested an educational website. CONCLUSIONS: The implementation of a surgeon-patient handout during HoLEP consultation improved understanding of postoperative retrograde ejaculation and dysuria at our center. We identified areas for future technology-aided improvements in post-HoLEP communication.
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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 | 0.003 | 0.012 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".