Treatment of lower urinary tract symptoms in multiple sclerosis patients: Review of the literature and current guidelines
Bibliographic record
Abstract
Multiple sclerosis (MS) is a unique neurological disease with a broad spectrum of clinical presentations that are time- and disease course-related. Lower urinary tract symptoms (LUTS) are highly prevalent in this patient population, with approximately 90% showing some degree of voiding dysfunction and/or incontinence 6-8 years after the initial MS diagnosis. Major therapeutic goals include quality of life improvement and the avoidance of urological complications Owing to the wide divergence of clinical symptoms and disease course, evaluation and treatment differ between patients. Treatment must be customized for each patient based on disease phase, patient independence, manual dexterity, social support, and other medical- or MS-related issues. Ablative or irreversible therapies are indicated only when the disease course is stable. In most cases of "safe" bladder, behavioural treatment is considered first-line defense. Antimuscarinic drugs, alone or in combination with intermittent self-catheterization, are currently the mainstay of conservative treatment, and several other medications may help in specific disease conditions. Second-line treatment includes botulinum toxin A injection, neuromodulation, indwelling catheters, and surgery in well-selected cases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".