Simple prostatectomy using the open and robotic approaches for lower urinary tract symptoms: A retrospective, case-control series
Bibliographic record
Abstract
INTRODUCTION: We aimed to assess the outcome of our series of simple prostatectomy at our institution using the open simple prostatectomy (OSP) and robotic-assisted simple prostatectomy (RASP) approaches. METHODS: We conducted a retrospective chart review of men who underwent OSP and RASP at Western University, in London, ON. Preoperative, intraoperative, and postoperative data were collected and analyzed. RESULTS: From 2012-2020, 29 men underwent a simple prostatectomy at our institution. Eight patients underwent an OSP and 21 patients underwent a RASP. The median age was 69 years. Preoperative median prostate volume was 153 cm3 (range 80-432). The surgical indications were failed medical treatment, urinary retention, hydronephrosis, cystolithiasis, and recurrent hematuria. The median operative time was 137.5 minutes in OSP and 185 minutes in RASP (p=0.04). Median estimated blood loss was 2300 ml (range 600-4000) and 100 ml (range 50-400) in the open and robotic procedures, respectively (p=0.4). The mean length of hospital stay was shorter in the RASP group, one day vs. three days (z=4.152, p<0.005). Perioperative complication rates were significantly lower in the group undergoing RASP, with no complications recorded in this group (p=0.004). Both groups demonstrated excellent functional results, with most patients reporting complete urinary continence (p=0.8). CONCLUSIONS: We report very good perioperative outcomes, with a minimal risk profile and excellent functional results, leading to marked improvement in patients' symptoms at followup after both the OSP and RASP approaches. RASP was associated with a shorter length of hospital stay, decreased blood loss, and a lower complication rate.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".