Lessons learned from <scp>A</scp> sian <scp>U</scp> rology
Bibliographic record
Abstract
Glasgow has been in the news a lot this year. The fantastic Commonwealth Games were followed by an excellent Société Internationale d'Urologie (SIU) meeting with its unique Scottish flavour. This month we move our attention to two other nations that have hosted the SIU – China and India. We present two large studies, which are well worth your reading pleasure, not just because of their sheer size but also for their messages and citability. Since the initial discovery in 2007 of ketamine-associated cystitis by Shahani et al. 1 in Canada, scattered cases had also been reported in some European countries including the UK. However, the gravity of this ketamine problem was subsequently found to be far greater in Asian countries, particularly Hong Kong, Taiwan, Mainland China and Malaysia. Although ketamine-associated uropathy is a medical problem, it takes root in much deeper social problems, and in turn perpetuates these problems and produces new issues. As the devastating effect of ketamine abuse on the society is unveiled, there are numerous collaborations between Hong Kong and Mainland China to combat it. Government and non-government organisations join hands in educating the public, youths in particular, on the irreversible damage that ketamine can cause to body and mind. More stringent laws have been enacted against drug traffickers, with high-profile enforcements. Abundant funds have also been set up to encourage research in this field. With all these concerted efforts, according to official statistics in Hong Kong and Mainland China, the number of ketamine abusers is on the decline. However, this is no reason for complacency, as the numbers of abusers we capture probably represent only the ‘tip of the iceberg’. More and more evidence is indicating a substantial population of undiscovered ketamine abusers, who sniff ketamine stealthily at home for years without being noticed by their families. Any effective solution to ketamine-associated uropathy 2 must involve identifying and extending help to this vast hidden group of abusers. The problem is daunting by its sheer magnitude. There are in addition, delicate issues of privacy, rights and self-esteem that require great sensitivity and patience. It is a job that requires experts from different specialties to cooperate. Urologists must work with social workers, teachers, paediatricians, psychiatrists, psychologists, nurses, occupational therapists and others. Last but not least, parental and family support is paramount in helping our youth to win this fight. For those endourologists busily treating stone disease we highlight the evolution of shockwave lithotripsy (SWL) over 25 years in >5000 patients 3. In many parts of the world, not just Asia, extracorporeal SWL (ESWL) has seen a drop in its popularity in parallel with an increase in the use of percutaneous nephrolithotomy (PCNL) and ureteroscopy. Patients seem to be more inclined to be stone-free with fewer interventions even if these are of an invasive nature. For those readers more interested in immediacy through our web journal, the Best of China virtual supplement is the one not to miss. There have been many calls for a BJUI Android app from our friends in the East. We are almost there! None disclosed.
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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 | 0.007 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.007 | 0.015 |
| Insufficient payload (model declined to judge) | 0.032 | 0.013 |
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".