The Transurethral Suprapubic endo-Cystostomy (T-SPeC): A Novel Suprapubic Catheter Insertion Device
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Current methods of suprapubic cystostomy (SPC) catheter insertion may be difficult for patients in poor health and can result in significant morbidity and mortality. These include a highly invasive open procedure, as well as the use of the percutaneous trocar punch methods, commonly associated with short-term SPC. We present the first human experience with the Transurethral Suprapubic endo-Cystostomy (T-SPeC(®)) device, a novel disposable device used for introducing a suprapubic catheter via a retrourethral (inside-to-out) approach similar to the Lowsley technique. PATIENTS AND METHODS: Four men at St. Mary's General Hospital in Kitchener Ontario, Canada, received the T-SPeC device (model T7) under general anesthesia. RESULTS: Patients had no complications from catheterization using the T-SPeC T7 Surgical System. The mean surgical time of the four procedures was 9.7 minutes, with a range of 7.9 to 13.5 minutes, including instrument preparation and cystoscopy. All four procedures were highly accurate and rapid. There were no complications and minimal blood loss from the procedure. CONCLUSIONS: We found that the T-SPeC device allows for efficient and safe insertion of a suprapubic catheter in an outpatient setting and may be a useful addition to the urologic armamentarium. The T-SPeC Surgical System facilitates rapid and precise suprapubic catheter placement.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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 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".