Improving the global management of the neurogenic bladder patient: part II.Future treatment strategies
Bibliographic record
Abstract
BACKGROUND: Patients with neurogenic bladder represent a small fraction of the total overactive bladder population. As a consequence, development of new therapies in this area has largely focused on idiopathic urinary incontinence. The absence of data for patients with neurological disease has far-reaching implications, affecting reimbursement and physicians' willingness to prescribe therapies, and limiting access of potential valuable treatments to patients whose lives are significantly impaired by inadequately managed bladder symptoms. SCOPE: The range of new therapies is increasing. Although many reviews of the overall safety, efficacy and mode of action of such treatments are available, there is limited information on how these treatments will best be used in clinical practice. We considered the current benefits and limitations of the various new licensed and unlicensed therapies and what role each would have in the future management of neurogenic urinary incontinence. CONCLUSIONS: A wide range of new treatments have been investigated for the management of overactive bladder; few, however, have been evaluated extensively in neurogenic urinary incontinence. Further studies are required to determine the optimal dosing regimes and formulations for individual sub-populations of neurogenic bladder patients and to determine the cost-effectiveness of these interventions. With the current experience available, two treatment algorithms for a subset of patients with neurological disease have also been proposed, which suggest at which stage of management and in which patients individual therapies for neurogenic urinary incontinence could be used.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".