Multiple sclerosis and lower urinary tract symptoms: A survey of prevalence, characteristic and urological evaluations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objective: Most multiple sclerosis patients have urological complications such as lower urinary tract symptoms. This study was conducted to evaluate the prevalence of these symptoms and whether they result in a urological evaluation. Methods: A cross-sectional study of 517 multiple sclerosis patients at Tehran’s referral multiple sclerosis center and neurology clinics between 2018 and 2022 was performed. Data were collected through interviews after patients completed informed consent forms. Urological examinations, including urine analysis and ultrasonography, were evaluated as final assessments. The data were analyzed using descriptive and inferential statistical tests in Statistical Package for Social Science. Results: Among all participants, the prevalence of lower urinary tract symptoms was 73% ( n = 384), with urgency (44.8% n = 232) being the most common symptom. The prevalence of intermittency was significantly higher among women ( p = 0.004). There was no gender-significant difference in terms of the prevalence of other symptoms ( p > 0.050). Lower urinary tract symptoms were significantly correlated with age, clinical course, disease duration, and disability ( p < 0.001). Additionally, 37.3% and 18.7% of patients with lower urinary tract symptoms, as well as 17.9% and 37.5% of patients with multiple sclerosis attacks, respectively, had undergone urine analysis and ultrasonography. Conclusion: Multiple sclerosis patients rarely undergo urological evaluations during the course of their disease. Proper assessment is essential as these symptoms are among the most detrimental manifestations of this disease.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 it