Urological surveillance and management of patients with neurogenic bladder: Results of a survey among practicing urologists in Canada.
Bibliographic record
Abstract
OBJECTIVE: To determine current trends in management and surveillance of the neurogenic bladder population by Canadian urologists who routinely work with and provide care for these patients. METHODS: A questionnaire was mailed to members of the Canadian Urological Association. The assessment and follow-up of upper and lower urinary tract function in neurogenic bladder patients, their optimal frequency and management of related infections were the topics of inquiry. RESULTS: One hundred and five of 602 urologists responded, for a response rate of 18%. Twenty-three (22%) of the respondents did not treat neurogenic bladder patients. Four out of five urologists who treated these patients favored a yearly renal ultrasound for routine surveillance of the upper urinary tract and routinely performed urodynamic studies for evaluation of the lower tract. Only a relatively small percentage used videourodynamics. Clean intermittent catheterization (CIC) was preferred for the management of neurogenic bladder in patients with emptying difficulties. Asymptomatic urinary tract infection (UTI) was preferably not treated. Symptomatic UTI was treated with antibiotics for 7 to 10 days by about 75% of the responding urologists, while 23% of female patients and 9% of male patients were treated for less than 7 days. Although most of the urologists had access to established treatment modalities, like CIC education and bladder augmentation, only 30% made use of botulinum toxin injections. CONCLUSIONS: This study confirms that most urologists in Canada, working with neurogenic bladder patients, follow principles reported in the literature regarding the need for evaluation, surveillance, and management of the urinary tract. However, there is no consensus on the specific methods used for surveillance of the urinary system. The results emphasize the need for clear guidelines in this field of urology in Canada.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".