Bibliographic record
Abstract
urgical innovation in urology has seen a revolution over the last 20 years.With Dr. Ralph Clayman performing the first laparoscopic nephrectomy in 1991 at Washington University in St. Louis, minimally invasive surgical innovation had begun.Canadian surgical pioneers, Dr. Donald Fentie and Dr. Peter Barrett in Saskatoon, were among the first Canadian urologists to perform laparoscopic nephrectomy in the mid-1990s.Over the subsequent 10 years, laparoscopic urology exploded across Canada, with laparoscopy quickly incorporated into residency training programs and across community and academic centres.The benefits of laparoscopic urology compared to open surgery have been demonstrated in numerous studies: less intraoperative blood loss, less analgesic use, comparable operative times, better cosmesis, less hospital stay and quicker return to work.1-4 We now routinely perform laparoscopic nephrectomy, and have expanded to laparoscopic partial nephrectomy, pyeloplasty, radical prostatectomy, and cystectomy.Laparoscopic prostatectomy may have a steeper learning curve, and is arguably one of the more difficult laparoscopic urologic procedures to learn.5 Nonetheless, our patients across Canada have benefited from these technologic innovations.Then came the Robots.The first da Vinci (Intuitive Surgical Inc.) robotic-assisted laparoscopic prostatectomy (RALP) was performed in 2000 by Binder.6 Since then, the robots have taken over radical prostatectomy surgery in the United States, and have also gradually invaded Canada.In 2007, only Edmonton, Alberta; London, Ontario; and Montreal, Quebec were performing RALP.7 So far in 2014, there are over 23 active daVinci surgical robots in Canada.In this month's CUAJ, Tholomier and colleagues 8 published the largest 5-year Canadian experience to date, with over 720 RALP performed with excellent oncologic outcomes.The benefits of robotic surgery include magnified, high definition visualization, excellent range of motion and elimination of tremor, and surgeon comfort at a seated console.9 Having performed a number of robotic surgeries, I can attest to these benefits.It's much more comfortable to sit at a robotic console enjoying the ergonomic and range of motion benefits, rather than twisted like a pretzel performing the surgery laparoscopically.But, there is a lack of good data demonstrating the clinical benefit of robotic prostatectomy over laparoscopic prostatectomy, and most data show that RALP is "as good as" laparoscopic prostatectomy.Ho and colleagues, in conjunction with the Canadian Agency for Drugs and Technologies in Health (CADTH), examined the clinical effectiveness and economic modelling of RALP compared with open and laparoscopic surgery.10 RALP had a shorter hospital stay, fewer complications, less blood loss than open surgery (19 retrospective studies), and shorter operative time and less blood loss than laparoscopic surgery (9 retrospective studies), but the authors qualified these results with no randomized trials, retrospective studies, inconsistent findings and methods.A recent article in the Journal of Clinical Oncology demonstrated RALP had similar odds of overall complications, re-admission, and additional cancer therapies compared to patients undergoing open radical prostatectomy.RALP was associated with a higher probability of 30-day and 90-day genitourinary complications compared to open surgery, and overall costs were significantly higher for RALP.11 At what cost?In Canada, the initial purchase price is $2.8 million , with annual maintenance costs of $180 000, and cost per case of $3500.Currently, outside of Alberta and Quebec, these costs in most provinces are covered through philanthropy.The UBC experience published last month in CUAJ 12 showed similar outcomes in hospital length of stay, transfusion rates, and positive surgical margin rates, but an additional cost of $5629 per robotic case over open surgery.With surgical robots popping up all over Ontario and other provinces, eventually the public will be asked to cover the costs of these
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.016 | 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".