How should bladder sensation be measured?: ICI‐RS 2011
Bibliographic record
Abstract
AIMS: Disturbed bladder sensations, or in broader terms, sensory dysfunctions are increasingly recognized as key elements in the origin and manifestation of symptom syndromes of urinary dysfunction. Adequate assessment of bladder sensation is crucial to improve our understanding of the pathophysiology and treatment of urinary dysfunction. This manuscript summarizes the discussions of a think tank on "How to measure bladder sensation" held at the ICI-RS meeting in 2011. METHODS: Based upon literature reviews on bladder sensation presented at the think tank in the ICI-RS meeting, discussions evolved which were summarized in the ICI-RS report. Different physicians/researchers further elaborated on this report, which is presented in this manuscript. RESULTS: Bladder sensations are not merely the result of bladder distension. Other factors inside the bladder or bladder wall: central processing and/or cognitive manipulation may play an important role. Current methods to measure sensations such as urodynamics, voiding diaries, forced diuresis, electrical stimulation and brain imaging are likely sub-optimal as they only consider part of these factors in isolation. CONCLUSIONS: Different methods to measure bladder sensations have been described and are used in clinical practice. Current methods only address part of the parameters responsible for the generation and perception of urinary sensations. Further focused research is required, and several recommendations are provided.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".