Peri-prostatic nerve block using Clarius EC7 HD₃ handheld ultrasound guidance.
Bibliographic record
Abstract
Transrectal ultrasound (TRUS) is a common modality used during urological procedures that require real-time visualization of the prostate, such as prostate biopsy and peri-prostatic nerve blocks (PNB) for surgical procedures. Current practice for TRUS-guided PNB requires use of costly, fixed, and non-portable ultrasound machinery that can often limit workflow. The Clarius endocavity EC7 probe, a digital, handheld and pocket-sized endocavity ultrasound (US) device, is an alternative, portable technology which was recently shown to accurately visualize and measure prostate dimensions and volume. Moreover, in recent years, there has been a renaissance of office-based treatments for minimally invasive surgical therapies (MIST) for the treatment of benign prostate hyperplasia (BPH). More specifically, the Rezūm procedure has been demonstrated to offer men a short, outpatient therapy with excellent 5-year outcomes in durability and preservation of antegrade ejaculation. While other anesthetic techniques have been described for Rezūm, including inhaled methoxyflurane (Penthrox), nitrous oxide, IV sedation and general anesthesia (which often mandate the presence of an anesthesiology team), US-guided local blocks offer the urologist an independent method for pain management. While most urologists may not have direct access to expensive, cart-based ultrasound systems, point of care ultrasound (POCUS) technology, such as Clarius (Vancouver, BC, Canada) and Butterfly (Butterfly Network, Inc, Guilford, CT, USA), can provide high-resolution imaging in combination with smart phone technology. Herein, we sought to describe the technique for using Clarius EC7 for TRUS-guided PNB and its use in urological application with the Rezūm BPH procedure.
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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 | 0.000 |
| 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) | 0.010 | 0.003 |
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".